DEV Community: Sangmin Lee

Claude Agents for DevOps: Monitoring, Alerting, Remediation

Sangmin Lee — Wed, 17 Jun 2026 01:31:36 +0000

Originally published at claudeguide.io/claude-devops-agent

Claude Agents for DevOps: Monitoring, Alerting, and Automated Remediation

A Claude DevOps agent bridges the gap between raw monitoring alerts and actionable response — it reads metrics, interprets what's happening, generates a plain-English explanation, and proposes (or executes) remediation steps in 2026. The key architectural constraint: the agent always stops before destructive actions and requests approval. This guide builds an incident analysis agent, an alert triage agent, and a safe remediation agent with explicit approval gates.

What Claude Adds to DevOps Tooling

Existing monitoring tools (Datadog, Grafana, PagerDuty) are good at detecting anomalies. They're poor at:

Explaining what's happening in context ("this memory spike correlates with the 14:30 deploy")
Correlating across signals (CPU + latency + error rate → single root cause hypothesis)
Generating runbooks for novel incidents that aren't in the playbook
Communicating to stakeholders who don't read dashboards

Claude agents fill these gaps without replacing your monitoring stack.

Architecture

Alert fires → Agent reads metrics/logs → Analysis → 
Explanation (Slack/PagerDuty) → Proposed remediation → 
Approval gate → Safe execution → Post-incident summary

Destructive actions (restarts, rollbacks, scale-downs) always have an approval gate. Read-only actions (metric queries, log tails, config reads) are automatic.

Setup

import anthropic
import json
import subprocess
from typing import Optional

client = anthropic.Anthropic()

Tool Definitions

DEVOPS_TOOLS = [
    {
        "name": "query_metrics",
        "description": "Query time-series metrics from monitoring system",
        "input_schema": {
            "type": "object",
            "properties": {
                "metric": {"type": "string", "description": "e.g., 'cpu_usage', 'memory_usage', 'http_error_rate'"},
                "service": {"type": "string"},
                "time_range": {"type": "string", "description": "e.g., '30m', '1h', '24h'"},
                "aggregation": {"type": "string", "enum": ["avg", "max", "min", "p95", "p99"]}
            },
            "required": ["metric", "service", "time_range"]
        }
    },
    {
        "name": "tail_logs",
        "description": "Get recent log lines for a service",
        "input_schema": {
            "type": "object",
            "properties": {
                "service": {"type": "string"},
                "lines": {"type": "integer", "default": 50},
                "filter": {"type": "string", "description": "grep-style filter pattern (optional)"}
            },
            "required": ["service"]
        }
    },
    {
        "name": "get_deployment_history",
        "description": "Get recent deployments for a service",
        "input_schema": {
            "type": "object",
            "properties": {
                "service": {"type": "string"},
                "limit": {"type": "integer", "default": 5}
            },
            "required": ["service"]
        }
    },
    {
        "name": "propose_remediation",
        "description": "Propose remediation steps. REQUIRES human approval before execution.",
        "input_schema": {
            "type": "object",
            "properties": {
                "diagnosis": {"type": "string", "description": "What's wrong and why"},
                "severity": {"type": "string", "enum": ["low", "medium", "high", "critical"]},
                "steps": {
                    "type": "array",
                    "items": {
                        "type": "object",
                        "properties": {
                            "action": {"type": "string"},
                            "command": {"type": "string", "description": "Actual command to run (if applicable)"},
                            "risk": {"type": "string", "enum": ["safe", "moderate", "destructive"]},
                            "reversible": {"type": "boolean"}
                        }
                    }
                }
            },
            "required": ["diagnosis", "severity", "steps"]
        }
    }
]

Tool Execution


python
# Simulate metric/log queries — replace with real Datadog/Prometheus/CloudWatch calls
def execute_devops_tool(tool_name: str, tool_input: dict) -

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Building a Content Generation Agent with Quality Checks

Sangmin Lee — Wed, 17 Jun 2026 01:30:52 +0000

Originally published at claudeguide.io/claude-content-generation-agent

Building a Content Generation Agent with Quality Checks

A content generation agent without quality checks produces high volume and inconsistent quality — the opposite of what content teams need. A production content agent runs output through a multi-stage pipeline: draft generation, self-review, fact extraction, format validation, and a human approval gate before anything reaches your CMS in 2026. This guide builds that full pipeline with Claude Agent SDK, including the quality check patterns that prevent bad content from shipping.

The Architecture

A naive content agent writes and publishes in one step. A production agent has stages with validation gates between them.

Input spec → Draft generation → Self-review → Structure validation → Fact extraction → [Human gate] → CMS publish

Each stage can reject and retry the previous stage's output. Human gates are optional — use them for high-stakes content, skip them for lower-stakes bulk generation.

Stage 1: Draft Generation


python
import anthropic
import json
from dataclasses import dataclass
from typing import Optional

client = anthropic.Anthropic()


@dataclass
class ContentSpec:
    title: str
    primary_keyword: str
    target_length: int  # words
    audience: str  # "junior developers", "CTOs", etc.
    tone: str  # "technical", "conversational", "authoritative"
    required_sections: list[str]
    cta_product: Optional[str] = None


@dataclass
class DraftResult:
    content: str
    word_count: int
    sections_found: list[str]
    metadata: dict


def generate_draft(spec: ContentSpec) -

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Worktree Isolation in Claude Code: Parallel Work Without Conflicts

Sangmin Lee — Wed, 17 Jun 2026 01:30:50 +0000

Originally published at claudeguide.io/claude-code-worktree

Worktree Isolation in Claude Code: Parallel Work Without Conflicts

Git worktrees let you check out multiple branches of the same repository in separate directories simultaneously — and Claude Code's --isolation worktree flag automates this for agentic tasks. Instead of stashing your work or switching branches, each Claude agent gets its own isolated copy to work in, then you review the diff and merge in 2026. This guide covers manual worktree patterns and the automated isolation built into Claude Code.

Why Worktrees Matter for AI-Assisted Development

Without worktrees, running Claude on a long refactor means your working branch is dirty while Claude works. You can't switch to a bug fix without either waiting or stashing. With worktrees:

repo/
├── main/           (your current working branch)
├── feature-auth/   (Claude working on auth refactor)
└── hotfix-404/     (you fixing a production bug)

Three branches, three directories, all simultaneously. No switching, no stashing, no conflicts.

Manual Worktree Pattern

# Create a new worktree for a feature branch
git worktree add ../my-repo-feature-auth feature/auth-refactor

# Claude works in the isolated directory
cd ../my-repo-feature-auth
claude "Refactor the entire auth module to use JWT tokens.
Use the patterns in src/auth/current-implementation.ts as reference.
Run bun run typecheck after each file change."

# Review the diff from your main directory
cd ../my-repo
git diff HEAD..feature/auth-refactor

# Merge if satisfied
git merge feature/auth-refactor

# Clean up
git worktree remove ../my-repo-feature-auth

Claude Code's Built-In Worktree Isolation

The Agent tool supports isolation: "worktree" which automates this pattern:

# When spawning a sub-agent with worktree isolation
Agent({
    "description": "Auth refactor",
    "prompt": "Refactor the auth module to use JWT tokens.",
    "isolation": "worktree"
})

What happens automatically:

Claude creates a new git branch: claude/[task-slug]-[timestamp]
Creates a worktree for that branch
Agent runs all changes in the isolated worktree
If the agent makes no changes, the worktree is cleaned up
If changes are made, the branch and worktree path are returned for review

Parallel Feature Development

Run multiple Claude agents on independent features simultaneously:

# Terminal 1: Backend API
git worktree add ../repo-api-work feature/user-api
cd ../repo-api-work
claude --print "Implement the user CRUD API endpoints following CLAUDE.md conventions"

# Terminal 2: Frontend components (simultaneously)
git worktree add ../repo-ui-work feature/user-ui
cd ../repo-ui-work
claude --print "Implement the user management React components"

# Terminal 3: Tests (simultaneously)
git worktree add ../repo-tests-work feature/user-tests
cd ../repo-tests-work
claude --print "Write integration tests for the user management feature"

All three run at the same time. When done, review each diff and merge in order.

Risky Refactor Pattern

When attempting a large refactor you're not sure will work out:

# Create isolation branch before attempting
git worktree add ../repo-experiment experiment/large-refactor

cd ../repo-experiment
claude "Refactor all database calls to use the new Repository pattern.
Files to change: all files in src/db/ and any file that imports from src/db/.
If any typecheck fails, stop and report the error rather than continuing."

# Evaluate the result
cd ../repo-experiment
git diff HEAD  # See what changed
bun run typecheck  # Verify it works
bun run test  # Run tests

# If it looks good, bring it to main
cd ../repo-main
git merge experiment/large-refactor

# If it doesn't work, discard cleanly
git worktree remove ../repo-experiment
git branch -D experiment/large-refactor

No mess on your main working branch.

Worktree with CLAUDE.md Inheritance

Worktrees inherit CLAUDE.md from the root repository since they share the same git history. You don't need to copy or symlink CLAUDE.md — it's automatically present in every worktree.

# Main repo has CLAUDE.md at root
ls my-repo/CLAUDE.md  # exists

# Worktree automatically has it
ls my-repo-worktree/CLAUDE.md  # same file, same content

This means all your project conventions apply consistently whether you're working in the main checkout or a worktree.

Common Patterns

Pattern: Safe dependency upgrade

git worktree add ../repo-deps-upgrade test/dependency-upgrade
cd ../repo-deps-upgrade

claude "Upgrade all dependencies to their latest versions.
Run bun update.
Then run bun run typecheck and bun run test.
Report any breaking changes and either fix them or document what would need to change."

Pattern: A/B implementation comparison

# Implementation A
git worktree add ../repo-impl-a experiment/approach-a feature/new-search
cd ../repo-impl-a
claude "Implement search using Elasticsearch approach"

# Implementation B (simultaneously)
git worktree add ../repo-impl-b experiment/approach-b feature/new-search
cd ../repo-impl-b
claude "Implement search using PostgreSQL full-text search approach"

# Compare both
git diff experiment/approach-a..experiment/approach-b

Pattern: Hotfix while feature work is in progress

# Claude is working on a big feature in worktree
# Production bug comes in — handle it without disturbing feature work
git worktree add ../repo-hotfix hotfix/critical-bug main

cd ../repo-hotfix
claude "Fix the null pointer error in UserService.findById.
The error is in src/services/user.service.ts line 84.
Run the unit tests after fixing."

# Deploy hotfix
cd ../repo-hotfix
git push origin hotfix/critical-bug
gh pr create --base main --title "hotfix: null pointer in UserService"

Cleaning Up Worktrees

# List all worktrees
git worktree list

# Remove a specific worktree
git worktree remove ../repo-feature-auth

# Remove worktree and its branch
git worktree remove ../repo-feature-auth
git branch -D feature/auth-refactor

# Prune stale worktree references
git worktree prune

Frequently Asked Questions

Do worktrees use double the disk space?
No — worktrees share the .git directory and object storage. The overhead is only the working tree files (source code), not the git history. For a 100MB repository, a worktree adds roughly 100MB of working files.

Can I run npm install or bun install in a worktree?
Yes, but you need to run it separately in each worktree since node_modules isn't shared. This adds disk usage but ensures dependency isolation between branches.

What's the difference between a worktree and a fresh clone?
Worktrees share the same .git directory — they see the same branches, remotes, and history. Clones are fully independent. Worktrees are faster to create, use less disk, and stay in sync automatically.

Can two worktrees be on the same branch?
No — git prevents two worktrees from checking out the same branch simultaneously. This is a feature: it prevents you from accidentally having two different states of the same branch.

Does Claude Code's --isolation worktree push the branch automatically?
No — it creates a local worktree and branch. You review the changes and push/merge manually. This is intentional: you stay in control of what enters your main branch.

Related Guides

Background Tasks in Claude Code: The Complete Playbook — Parallel agent execution
Git Workflows in Claude Code: Branching, PRs, and Commits — Git integration
Claude Code Complete Guide — Full Claude Code reference

Go Deeper

Power Prompts 300 — $29 — Worktree workflow prompts including parallel feature development coordination, risky refactor patterns with validation gates, and the A/B implementation comparison template.

→ Get Power Prompts 300 — $29

30-day money-back guarantee. Instant download.

Claude Code IDE Extensions: VS Code vs JetBrains (2026 Comparison)

Sangmin Lee — Wed, 17 Jun 2026 01:30:06 +0000

Originally published at claudeguide.io/claude-code-vs-code-jetbrains

Claude Code IDE Extensions: VS Code vs JetBrains (2026 Comparison)

Claude Code works best with VS Code — the official extension is more mature, has tighter integration with the Claude Code CLI, and is the primary development target for Anthropic's IDE features. The JetBrains extension (IntelliJ, PyCharm, WebStorm, etc.) works but lags in features and update frequency in 2026. If you use JetBrains and aren't willing to switch, the best workflow is JetBrains for editing + Claude Code CLI in a terminal alongside. This guide explains what each extension does, how to set them up, and what you're giving up on each platform.

What the IDE Extensions Actually Do

First, an important clarification: Claude Code's primary interface is the terminal CLI (claude command). The IDE extensions are companions that improve the integration but don't replace the CLI.

What both extensions provide:

Run Claude Code commands without switching to a terminal
See Claude's file changes highlighted in the editor
Click to accept/reject individual edits
View Claude's output alongside your code

What neither extension provides:

Claude Code's full capability — the CLI is always more capable
Inline autocomplete (that's GitHub Copilot's domain)
Multi-file diffs in a dedicated review pane (CLI is better)

VS Code Extension

Setup

# Install Claude Code CLI first
npm install -g @anthropic-ai/claude-code

# Install the VS Code extension
# Method 1: VS Code marketplace
# Search "Claude Code" by Anthropic — install the official extension

# Method 2: CLI install
code --install-extension anthropic.claude-code

Features

Integrated terminal pane: Claude Code runs inside VS Code's terminal. You get the full CLI experience without switching windows.

File diff viewer: When Claude modifies files, VS Code's native diff view shows exactly what changed. You can accept all changes, reject all, or review file by file.

@workspace context: The VS Code extension can pass your entire open workspace as context to Claude Code, providing awareness of open files and the project structure.

Status bar indicator: Shows when Claude Code is thinking/running. Useful for long operations.

Settings sync: Respects VS Code's settings sync — your Claude Code configuration follows you across machines.

Keyboard shortcuts (VS Code)

Action	Default shortcut
Open Claude Code panel	`Cmd+Shift+C` (Mac) / `Ctrl+Shift+C` (Windows)
Accept all changes	`Cmd+Shift+A`
Reject all changes	`Cmd+Shift+R`
Focus terminal	`Ctrl+\``

JetBrains Extension

Supported IDEs

The JetBrains extension supports:

IntelliJ IDEA
PyCharm
WebStorm
GoLand
PhpStorm
Rider

Setup

`bash

Install Claude Code CLI first

npm install -g @anthropic-ai/claude-code

Install via JetBrains Marketplace

Settings → Plugins → Marketplace → Search "Claude Code"

Install the official Anthropic plugin

Or via CLI:

`bash

IntelliJ / PyCharm

idea installPlugin anthropic.claude-code

WebStorm

webstorm installPlugin anthropic.claude-code
`

Features

Embedded terminal: Claude Code runs in the JetBrains built-in terminal. Less polished than VS Code integration but functional.

File change notifications: When Claude modifies files, JetBrains detects changes and prompts reload. Not as smooth as VS Code's diff viewer.

Project context: The plugin provides basic project structure context to Claude Code, but the @workspace integration is less developed than VS Code's.

Feature Comparison

Feature	VS Code	JetBrains
Official support tier	Primary	Secondary
Update frequency	Frequent	Less frequent
Diff viewer integration	Native, excellent	File-reload based
@workspace context	Full integration	Basic
Terminal integration	Native pane	Built-in terminal
Extension stability	Mature	Beta-quality
Language-specific features	Language Server Protocol	JetBrains language intelligence
Refactoring tool integration	Limited	Strong (JetBrains advantage)
Remote development	via VS Code Remote	via JetBrains Gateway

When JetBrains Actually Wins

Despite VS Code being better for Claude Code integration, JetBrains has genuine advantages:

Deep language intelligence

For Java, Kotlin, and Scala development, IntelliJ's language intelligence is significantly better than VS Code's. The type inference, refactoring tools, and debugger integration are more mature.

Workflow: Use IntelliJ for navigation, refactoring, and debugging. Use Claude Code CLI in an external terminal (or JetBrains's built-in terminal) for generation and multi-file tasks.

Python data science

PyCharm's notebook integration, virtual environment management, and scientific tools are more developed than VS Code's.

Workflow: PyCharm for notebook work and data exploration. Claude Code CLI in the terminal for script generation and refactoring.

Android development

Android Studio (JetBrains-based) has no real VS Code equivalent. Claude Code CLI works fine alongside it.

The Best Hybrid Setup

Many developers — especially those coming from JetBrains — use a hybrid approach:

Setup:

Keep your JetBrains IDE open for editing, navigation, and debugging
Open a terminal window alongside (or use JetBrains's built-in terminal)
Run Claude Code in that terminal
When Claude modifies files, JetBrains detects the external changes and refreshes

`bash

In JetBrains terminal or external terminal

cd /path/to/your-project
claude

Work normally — Claude's changes appear in JetBrains file tree

This gives you JetBrains's language intelligence plus Claude Code's full capability. The main friction is accepting file changes through JetBrains's "File Changed Externally" dialog instead of a unified diff view.

The CLI-First Approach (Recommended)

Both extension experiences are secondary to the CLI. The most productive Claude Code developers use:

`bash

Terminal (standalone or in any IDE)

claude

Then use editor only for reviewing changes and making manual edits

Accept/reject from the CLI, not the extension

The CLI gives you:

Full feature parity (some features are CLI-only)
Better control over multi-file changes
Works identically regardless of your editor

Setting Up CLAUDE.md in Either IDE

Regardless of which IDE you use, CLAUDE.md is how you configure Claude Code for your project:

`markdown

Project Name

Development Commands

npm run dev — dev server
npm run typecheck — type check (run before marking done)
npm run build — verify build

Editor

[Optional: note your IDE if there are editor-specific conventions]

Architecture

[Your project structure and key patterns]
`

Frequently Asked Questions

Does Claude Code work better with VS Code or JetBrains?
VS Code. The Claude Code extension for VS Code is more mature, updates more frequently, and has tighter integration with the CLI. If you're starting fresh with Claude Code, choose VS Code. If you're committed to JetBrains, use Claude Code CLI in the terminal alongside JetBrains.

Can I use Claude Code with Cursor?
Yes. Cursor is VS Code-based, so the Claude Code CLI works inside Cursor's terminal. Cursor also has its own AI features — many developers use both Cursor (for inline editing) and Claude Code CLI (for multi-file tasks) simultaneously.

Is there a Vim or Neovim plugin for Claude Code?
Claude Code works in any terminal, including inside Vim's :terminal or Neovim's terminal mode. There's no dedicated Neovim plugin as of April 2026, but the CLI workflow is fully functional from any terminal.

Does the JetBrains extension support all JetBrains IDEs?
The extension supports IntelliJ, PyCharm, WebStorm, GoLand, PhpStorm, and Rider. Android Studio (which is JetBrains-based) may work but has less official support.

What's the minimum VS Code version for the Claude Code extension?
VS Code 1.85 or later. Most users are well above this threshold. Update VS Code if you're having installation issues.

Related Guides

Claude Code Complete Guide — All features including CLI reference
Why Dev Teams Are Moving From Copilot to Claude Code — IDE context comparison
The 2026 Developer Tool Stack — Where Claude Code fits

Go Deeper

Power Prompts 300 — $29 — 300 tested prompts optimized for the Claude Code CLI workflow, including IDE-agnostic patterns that work whether you're running the CLI from VS Code, JetBrains, or a standalone terminal.

→ Get Power Prompts 300 — $29

30-day money-back guarantee. Instant download.

The Todo System in Claude Code: When and How to Use It

Sangmin Lee — Wed, 17 Jun 2026 01:30:03 +0000

Originally published at claudeguide.io/claude-code-todo-system

The Todo System in Claude Code: When and How to Use It

Claude Code has a built-in todo system that tracks multi-step tasks within a session. Claude creates and updates todos automatically for complex work — you don't have to manage them. The system shines for tasks with 4+ sequential steps, where losing track of where you left off would cost meaningful time in 2026. This guide covers how the todo system works and when to engage it explicitly.

How Claude Code Todos Work

When you ask Claude Code for something that requires multiple steps, it can create a todo list internally and check off items as it completes them. You see this as a running task panel in the UI.

Todos are:

Session-scoped: They exist for the duration of a conversation, not across sessions
Auto-created: Claude decides when to create them based on task complexity
Visible in real-time: You watch items get checked off as Claude works
Interruptible: You can ask Claude to stop, reprioritize, or add items

When Claude Creates Todos Automatically

Claude creates a todo list when:

The task has 4+ distinct steps — "Add auth, update the API, add tests, update docs"
Steps have dependencies — Step B requires Step A to be done first
The task will take many tool calls — Reading multiple files, running multiple commands
There's a risk of losing context — Long session where the original goal might drift

Example that triggers auto-todo:

claude "Refactor the authentication system:
- Replace custom JWT with Clerk
- Update all API routes to use Clerk's auth()
- Remove old jwt library and types
- Update CLAUDE.md with new auth pattern
- Run typecheck and fix errors"

Claude will automatically create a 5-item todo list and work through it systematically.

Asking for a Todo List Explicitly

For complex tasks, you can request a todo list before Claude starts working:

# Show me the plan before executing
claude "Before you start: create a todo list for migrating our Prisma schema
to use soft deletes on User, Product, and Order models. 
Show me the list and wait for my approval."

Claude responds with something like:

Here's my plan:

1. [ ] Add `deletedAt DateTime?` to User model in schema.prisma
2. [ ] Add `deletedAt DateTime?` to Product model
3. [ ] Add `deletedAt DateTime?` to Order model
4. [ ] Create migration: `prisma migrate dev --name add_soft_delete`
5. [ ] Update findMany queries in lib/db/users.ts to filter deletedAt IS NULL
6. [ ] Update findMany queries in lib/db/products.ts
7. [ ] Update findMany queries in lib/db/orders.ts
8. [ ] Run typecheck and fix errors
9. [ ] Update CLAUDE.md with soft delete pattern

Proceed?

This lets you spot problems in the plan (wrong file paths, missing steps) before any code is written.

Managing Todos During a Session

Adding items mid-task

# While Claude is working
"Add to the list: also update the admin panel queries in lib/db/admin.ts"

Reprioritizing

# Stop current work and shift focus
"Put the CLAUDE.md update last — focus on the database migrations first"

Checking status

# Ask what's left
"What's still on the list?"

Stopping at a checkpoint

# Complete current item and stop
"Finish what you're doing on step 3, then pause. 
I want to review before you continue."

Pattern: Large Codebase Refactors

Todo lists are most useful for refactors that touch many files:

claude "Todo list for this refactor:
We're renaming `organizationId` to `orgId` everywhere in the codebase.

Generate a comprehensive todo list covering:
1. Find all occurrences (TypeScript files, schema, env vars, docs)
2. Order by dependency (schema first, then DB queries, then components)
3. Include typecheck after each major section
4. Flag anything that might break tests separately

Don't start yet — just the list."

Claude will audit the codebase first, then produce a sequenced list like:

Refactor Plan: organizationId → orgId

Schema and DB layer:
1. [ ] Update schema.prisma: rename organizationId field on all models
2. [ ] Run prisma migrate dev --name rename_org_id
3. [ ] Update all queries in lib/db/ (12 files)
4. [ ] Run: bun run typecheck

API layer:
5. [ ] Update API routes in app/api/ (8 files)
6. [ ] Update server actions in app/actions/ (4 files)
7. [ ] Run: bun run typecheck

Frontend:
8. [ ] Update component props and hooks (15 components)
9. [ ] Update types in types/api.ts
10. [ ] Run: bun run typecheck

Cleanup:
11. [ ] Search for any remaining references: rg "organizationId"
12. [ ] Update CLAUDE.md with new naming convention
13. [ ] Run full test suite

Pattern: Feature Implementation

claude "Create a todo list for implementing product reviews:
- Users can leave a 1-5 star rating + text review on any product
- Reviews require purchase verification
- Products show average rating
- Admin can delete reviews

Generate the implementation todo list. I'll approve, then you execute."

Good todo lists include:

DB schema first
API layer second
Frontend last
Typechecks between layers
Test coverage as explicit items

What Todos Are NOT Good For

Don't use todos for:

Single-step tasks: "Fix this bug" doesn't need a list
Short sessions: If it takes 3 minutes, the list adds overhead
Exploratory work: "Investigate why this is slow" — exploration doesn't have predefined steps
Pair debugging: When you're iterating interactively, todos slow the conversation

The rule of thumb: if you could describe the work as a numbered list before asking, todos help. If the work is more "figure out what's wrong," skip them.

Todos and Session Context

Todos are session-scoped. When you start a new session, the todo list is gone. For tasks that span multiple sessions:

End each session with a status update: "Summarize what we completed and what's left"
Save the remaining items to a file or CLAUDE.md:

claude "We're stopping for today. Write the remaining items from our todo list 
to a file called TODO-refactor.md in the project root."

Start the next session by reading that file:

claude "@TODO-refactor.md Continue from where we left off. 
Show me what's remaining before you start."

Frequently Asked Questions

Can I see the todo list as a file somewhere?
No — todos are in-session state, not persisted to disk. The only way to save them is to ask Claude to write them out.

What's the difference between Claude Code todos and my own TODO comments in code?
Claude Code todos are task-tracking for the current session. Code TODO: comments are development notes in source. They're unrelated — Claude doesn't automatically track code TODO comments as session tasks.

Can I use todos to delegate to another Claude session?
Not directly. But you can write the todo list to a file and reference that file in a new session — effectively passing the task state.

Does Claude always show todos for multi-step tasks?
Not always. Shorter multi-step tasks may get done without showing a todo list. The visual todo panel appears when the task is complex enough that Claude explicitly creates one. You can always ask: "Show me your plan as a todo list first."

Related Guides

Claude Code Plan Mode Deep Dive — Planning before executing
Claude Code Complete Guide — Full reference
Context Engineering for Claude — CLAUDE.md optimization

Go Deeper

Power Prompts 300 — $29 — Includes task orchestration prompts: how to structure long multi-day refactors, review-gate patterns, and session handoff templates.

→ Get Power Prompts 300 — $29

30-day money-back guarantee. Instant download.

Claude Code for Teams: Best Practices for Shared Projects (2026)

Sangmin Lee — Tue, 16 Jun 2026 01:31:37 +0000

Originally published at claudeguide.io/claude-code-team-setup

Claude Code for Teams: Best Practices for Shared Projects (2026)

The single most important step for Claude Code team adoption is committing a well-maintained CLAUDE.md to your repo — it becomes living onboarding documentation that every developer's Claude instance reads automatically, ensuring AI-generated code follows team conventions instead of Claude's defaults in 2026. This guide covers the full team setup: shared context, API key management, cost allocation, and the workflow patterns that prevent the biggest team AI problem: inconsistent code quality across developers.

The Team AI Problem

When Claude Code is used inconsistently across a team:

Developer A has a detailed CLAUDE.md → Claude generates convention-following code
Developer B uses Claude Code cold → Claude generates generic code
Developer C prompts carelessly → Claude makes architectural choices inconsistently

The result: an AI-assisted codebase that's harder to maintain than a human-only one, because the AI made different implicit decisions for each developer.

The solution is centralized context management.

Step 1: The Shared CLAUDE.md

Every team member's Claude Code instance reads CLAUDE.md at session start. A well-crafted team CLAUDE.md means every developer gets the same "briefed" Claude.

What to include in a team CLAUDE.md

# [Project Name] — Claude Code Guide

## Project Context
[2-3 sentences: what the product does, who uses it, what stack we're on]

## Development Commands

bash

Required before every PR

npm run typecheck # Zero type errors expected
npm run test # All tests must pass
npm run lint # Zero lint errors
npm run build # Build must succeed


## Architecture Rules
- All DB queries go through `lib/db/queries/` — no inline SQL or Prisma calls in routes
- All server mutations go through Server Actions in `app/actions/` — no direct DB access from components
- Every API route validates the session: see `middleware.ts` for the pattern
- All monetary values stored as integers (cents) — never floats

## File Organization
- New feature? Follow the structure in `src/features/[existing-feature]/`
- New API route? Follow the pattern in `app/api/[existing-route]/route.ts`
- New component? Check `components/ui/` — don't recreate what's already there

## Code Style Rules
- TypeScript strict mode — no `any`, no `as unknown as`
- Functional components only — no class components
- Error handling: use our `AppError` class from `lib/errors.ts`, not raw Error
- Logging: use `lib/logger.ts`, not `console.log`

## Anti-patterns (These Cause Production Issues)
- NEVER filter by `userId` alone — always include `organizationId` (multi-tenant security)
- NEVER commit `.env` files or hardcoded API keys
- NEVER use `Date.now()` for timestamps — use server-side `new Date()` in DB inserts
- NEVER skip migrations — if you change schema.ts, always run `npm run db:migrate`

## When You're Unsure
Ask before implementing. Use the convention in the most recently modified similar file.
If no precedent exists, propose in a PR comment rather than picking arbitrarily.

What NOT to put in team CLAUDE.md

General programming advice Claude already knows
Technology descriptions (e.g., "React is a UI library")
Things obvious from the code (e.g., "we use TypeScript" — Claude can see that)
Personal preferences that aren't team conventions

Target length: 300-600 tokens. Short enough that every line carries weight.

Step 2: API Key and Account Setup

Option A: Individual Claude.ai Pro subscriptions (small teams)

Best for teams of 2-5 where each developer uses Claude Code independently:

Each developer has their own Claude.ai Pro at $20/month
Claude Code is included in the Pro plan
No shared API key, no cost allocation needed
Simple to set up, easy to onboard

Limitation: No centralized usage visibility.

Option B: Shared API key with usage tracking (larger teams)

For teams where you need cost control and visibility:

Create a team workspace in Anthropic Console
Create a shared API key (or per-developer keys under the workspace)
Set spending limits per key


bash
# Team members configure the API key:
export ANTHROPIC_API_KEY=sk-ant-api03-[team-key]

# Or add to ~/.zshrc / ~/.bashrc:
echo 'export ANTHROPIC_API_KEY=sk-ant-api03-[team-key]' 

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Claude Code for Teams: Self-Host, Shared Config, Enterprise

Sangmin Lee — Tue, 16 Jun 2026 01:30:54 +0000

Originally published at claudeguide.io/claude-code-self-host-team

Claude Code for Teams: Self-Hosting, Shared Config, and Enterprise Setup

There is no "self-hosted" Claude Code in the traditional sense — the model runs on Anthropic's API, not your servers. "Team setup" means: shared CLAUDE.md conventions in the repo, centralized API key management, model routing to control costs, and consistent tooling across developers' machines. This guide covers what it takes to run Claude Code effectively across a team of 2–50 developers.

What "Team Claude Code" Actually Means

Three things to get right:

Shared context — every developer's Claude session knows the project conventions (CLAUDE.md in the repo)
Centralized API access — one billing account, keys distributed securely, usage visible
Consistent tooling — same Claude Code version and settings across machines

What it does NOT mean:

Running a Claude model on your own servers (not available; Anthropic API only)
A shared Claude Code "server" that multiple developers connect to (each developer runs their own Claude Code CLI)

Step 1: Shared CLAUDE.md in the Repository

The most important team setup is CLAUDE.md committed to the repo. Every developer who runs Claude Code in the project directory gets the same context automatically.

# ProjectName — Claude Code Team Config

## Stack
- Node.js 20, TypeScript strict
- Next.js 15 App Router
- Prisma + PostgreSQL (Neon)
- Clerk auth
- Bun as package manager

## Architecture Rules
1. Every DB query must include organizationId filter (multi-tenant)
2. No direct Prisma calls in components — use server actions or API routes
3. All API routes: validate auth first, then DB access
4. Errors: throw AppError from @/lib/errors, never plain Error

## Testing
- Unit tests: vitest
- Integration: tests/integration/ (run with bun run test:integration)
- Pre-commit: bun run typecheck && bun run lint

## Naming
- Files: kebab-case
- Components: PascalCase
- DB columns: snake_case

## What NOT to do
- No any type (use unknown or specific types)
- No console.log in production code (use @/lib/logger)
- No hardcoded strings for user-facing copy (use i18n keys)

## Commands
- dev: bun run dev
- typecheck: bun run typecheck
- test: bun run test
- lint: bun run lint

Commit this file to the repo root:

git add CLAUDE.md
git commit -m "docs: add Claude Code team configuration"

Every team member benefits automatically — no manual setup needed on their machine.

Step 2: API Key Management

Option A: Individual API keys (small teams, < 5 developers)

Each developer gets their own Anthropic API key. Simple, no shared cost visibility.

# Each developer sets their own key
export ANTHROPIC_API_KEY="sk-ant-..."
# Or add to ~/.zshrc / ~/.bashrc

Downside: no centralized billing, no usage visibility per developer.

Option B: Shared key via secrets manager (recommended for 5+ developers)

Use a secrets manager (1Password, AWS Secrets Manager, Doppler) to distribute a shared key:

# With Doppler
doppler setup
export ANTHROPIC_API_KEY=$(doppler secrets get ANTHROPIC_API_KEY --plain)

# With AWS SSM
export ANTHROPIC_API_KEY=$(aws ssm get-parameter --name /team/anthropic-api-key --with-decryption --query Parameter.Value --output text)

Advantage: rotate the key in one place, everyone gets the update.

Option C: Enterprise Anthropic agreement

For teams

→ Get Power Prompts 300 — $29

30-day money-back guarantee. Instant download.

How to Use Scheduled Tasks in Claude Code for Automation (2026)

Sangmin Lee — Tue, 16 Jun 2026 01:30:51 +0000

Originally published at claudeguide.io/claude-code-scheduled-tasks

How to Use Scheduled Tasks in Claude Code for Automation (2026)

Claude Code supports scheduled and recurring tasks through the /schedule slash command and the Agent SDK's CronCreate tool, letting you run autonomous AI workflows on a timer — from daily content audits to hourly data processing pipelines in 2026. This guide covers every scheduling option available in Claude Code and the Agent SDK, with practical patterns for macOS (launchd), Linux (cron), and cloud (GitHub Actions).

What "Scheduled Tasks" Means in Claude Code Context

There are three distinct scheduling patterns:

Claude Code CLI scheduled sessions — use /schedule to queue a Claude Code session to run at a specific time; Claude picks up where you left off
Agent SDK CronCreate tool — inside a Claude Code session, use the CronCreate tool to schedule recurring autonomous actions
External scheduling + Claude Code CLI — use cron/launchd/GitHub Actions to launch claude -p "..." on a schedule

Each pattern suits different use cases. This guide covers all three.

Pattern 1: Claude Code CLI `/schedule`

The /schedule command schedules a follow-up Claude Code task to run later in the same project context.

Basic Usage

Inside a Claude Code session:

/schedule in 2 hours: run bun run typecheck and report any errors

/schedule tomorrow at 9am: check if the Vercel deployment is healthy and summarize the last 24h of logs

/schedule every weekday at 8am: pull latest git changes, check for dependency updates, summarize in DAILY_SUMMARY.md

What Gets Scheduled

When you use /schedule, Claude Code:

Records the task and time
Launches a new session at the scheduled time (requires Claude Code to be running or a background daemon)
Executes the task with full project context from CLAUDE.md
Writes results to a file or sends a desktop notification

Prerequisites

For /schedule to fire reliably:

Mac: Claude Code background service must be enabled (claude service start)
The project directory must be accessible at scheduled time
For server-side scheduling, use Pattern 3 instead

Pattern 2: Agent SDK `CronCreate` Tool

Inside any Claude Code session, the CronCreate tool schedules recurring autonomous tasks that persist across sessions.

Creating a Recurring Task

Use CronCreate to schedule a daily health check:
- Name: "daily-health-check"
- Schedule: every day at 6am
- Task: check site uptime, count new articles in content/, verify build passes
- Output: append to logs/daily-health.log

Claude Code will call CronCreate with the appropriate parameters. The scheduled task runs as an autonomous agent — no human in the loop.

Listing and Managing Scheduled Tasks

# See all scheduled tasks
Use CronList to show all active scheduled tasks

# Update a task
Use CronCreate with the same name to overwrite the existing schedule

# Remove a task
Use CronDelete to remove "daily-health-check"

Real Example: Daily Content Audit

I want to schedule a daily content quality check for claudeguide.io.
Use CronCreate to set this up:
- Name: "content-daily-audit"
- Schedule: every day at 7am UTC
- Task:
  1. Count articles in claudeguide-io/content/
  2. Find any article missing an FAQ section
  3. Check last commit was within 48 hours (content velocity)
  4. Write summary to logs/audit-YYYY-MM-DD.md

Pattern 3: External Scheduling + Claude Code CLI

The most reliable approach for production use: external schedulers call the Claude Code CLI directly.

macOS: launchd

Create a plist file at ~/Library/LaunchAgents/com.myapp.claude-task.plist:


xml
<?xml version="1.0" encoding="UTF-8"?

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Claude Code for Frontend: Next.js, Tailwind, shadcn/ui Patterns

Sangmin Lee — Tue, 16 Jun 2026 01:30:08 +0000

Originally published at claudeguide.io/claude-code-nextjs-frontend

Claude Code for Frontend: Next.js, Tailwind, shadcn/ui Patterns

Claude Code accelerates Next.js 15 App Router development by generating complete page components, wiring server data fetching, and handling Tailwind + shadcn/ui patterns accurately. The key is giving Claude Code a well-structured CLAUDE.md with your stack details, then using targeted component prompts. This guide covers the CLAUDE.md setup, component generation patterns, server vs client component decisions, and the common pitfalls.

CLAUDE.md Setup for Next.js Projects

A good CLAUDE.md makes every prompt 3× more accurate — Claude Code knows your routing conventions, component library, and type patterns without you having to repeat them.

# Project: [Your App Name]

Next.js 15 App Router, TypeScript strict, Tailwind CSS, shadcn/ui.

## Tech Stack
- Framework: Next.js 15 (App Router, no Pages Router)
- Language: TypeScript strict mode (no `any`)
- Styling: Tailwind CSS v4
- Components: shadcn/ui (components in `components/ui/`)
- Icons: Lucide React
- DB: Drizzle ORM + Neon PostgreSQL
- Auth: Clerk
- State: React Query (server state) + Zustand (client state)

## Component Conventions
- Server Components by default; add `"use client"` only when needed
- shadcn components are pre-installed — import from `@/components/ui/`
- Custom components in `components/` (not `components/ui/`)
- Page files: `app/[route]/page.tsx`
- Layout files: `app/[route]/layout.tsx`

## Data Fetching
- Server Components: `async/await` directly with Drizzle
- Client Components: React Query (`useQuery`, `useMutation`)
- API routes in `app/api/`

## TypeScript Patterns
- Infer types from Drizzle schema (don't redeclare)
- Use `type` not `interface` for simple objects
- Error types: `{ code: string; message: string }`

## Dev Commands

bash
bun run dev # Dev server
bun run build # Production build
bun run typecheck # Type check
npx shadcn add [component] # Add shadcn component

plaintext

Generating Complete Page Components

The pattern that works

Claude Code generates better components when you specify: route, data source, UI components, and behavior.

Weak prompt:

"Create a dashboard page"

plaintext

Strong prompt:

"Create app/dashboard/page.tsx — a server component that:
- Fetches user's last 30 days of API usage from the usageRecords table via Drizzle
- Shows a summary card row: total cost, total calls, top model (3 Cards)
- Shows a line chart of daily cost (Recharts LineChart, client component in separate file)
- Shows a data table of recent calls (shadcn/ui Table, last 20 rows)
- Uses Suspense boundaries with skeleton loading states
- Handles empty state (no data yet)"

plaintext

Claude Code generates the full page, a separate CostChart.tsx client component, and skeleton placeholders.

Server vs Client Component Decisions

Claude Code handles this well if you establish the pattern in CLAUDE.md. For clarity, you can also state it explicitly in prompts:

"The parent page is a server component. Extract only the interactive parts 
(the date picker, the filter dropdown) into a 'use client' component."

plaintext

Quick decision guide for your prompts

Needs	Component type
DB query, auth check	Server Component
`useState`, `useEffect`	Client Component
onClick handlers	Client Component
Static display	Server Component
External API fetch at request time	Server Component
Browser APIs (localStorage, etc.)	Client Component

Best practice prompt pattern:

"Keep this as a server component. Put the toggle button logic in a 
separate ClientToggle.tsx with 'use client'."

plaintext

shadcn/ui Component Patterns

Installing before prompting

Claude Code generates shadcn imports but won't run npx shadcn add unless you tell it to. If you know you need a new component:

"I need a DataTable with sorting and pagination. First run 
`npx shadcn add table` if it's not installed, then generate 
app/users/components/UsersTable.tsx using shadcn Table."

plaintext

Commonly used shadcn components with Claude Code

Forms with validation:

"Create a settings form at components/SettingsForm.tsx:
- shadcn Form + Input + Select + Button
- Zod schema: name (string, min 2), email (email), plan (enum: free, pro)
- React Hook Form with zodResolver
- onSubmit calls updateSettings() mutation
- Show toast on success/error (shadcn useToast)"

plaintext

Data tables:

"Create a users data table with:
- shadcn Table, sorted by createdAt descending
- Columns: name, email, plan, joined date, actions (View, Delete)
- Row click navigates to /users/[id]
- Delete shows shadcn AlertDialog confirmation
- Pagination (25 rows per page)"

plaintext

Modals/dialogs:

"Add an invite team member dialog to app/team/page.tsx:
- shadcn Dialog triggered by 'Invite Member' button
- Form: email input + role Select (Admin/Member)
- Submit calls inviteTeamMember() server action
- Close on success, show error inline on failure"

plaintext

Tailwind Patterns That Work Well

Be specific about layout

Vague styling prompts get inconsistent results:

Weak:

"Make the layout look nice"

plaintext

Strong:

"Two-column layout: sticky left sidebar (w-64, border-r) with nav links,
main content area (flex-1, overflow-y-auto, p-6).
On mobile (< md), hide sidebar and show hamburger menu."

plaintext

Responsive design prompts

"Responsive card grid:
- Mobile: single column
- tablet (md): 2 columns  
- desktop (lg+): 3 columns
- Each card: white background, rounded-lg, border, shadow-sm, p-6
- Hover: shadow-md transition"

markdown

Dark mode support

If your project uses dark mode, add to CLAUDE.md:

## Styling Conventions
Dark mode is enabled via `class` strategy.
Always add dark: variants: `bg-white dark:bg-gray-900`
Use semantic color tokens from tailwind.config.ts when possible.

Then prompts like "add dark mode support to this component" work accurately.

Data Fetching Patterns

Server Component data fetching

"Create app/orders/page.tsx as a server component:
- Query orders table with Drizzle: last 50 orders, joined with users table
- Pass data to OrdersTable client component as props
- Wrap OrdersTable in Suspense with OrdersTableSkeleton fallback
- No useEffect — all fetching happens at the page level"

React Query for client-side data

"Add real-time polling to the dashboard:
- useQuery hook to fetch /api/usage/current every 30 seconds
- Show 'Last updated: X seconds ago' in the card footer
- Invalidate query on manual refresh button click"

Server Actions for mutations

"Replace the API route handler with a server action:
- Move POST /api/users/create logic to actions/users.ts
- Export `createUser` async function with 'use server'
- Form submits using useActionState hook
- Return { success: boolean; error?: string } shape"

Common Pitfalls and Fixes

Pitfall 1: "use client" at the wrong level

Claude Code sometimes adds "use client" to parent components unnecessarily, making server data fetching impossible.

Fix prompt:

"Remove 'use client' from the page component. Keep the parent a server 
component. Only the [ComponentName] that uses onClick needs 'use client' —
extract it to a separate file."

Pitfall 2: Missing Suspense boundaries

Generated components sometimes render without loading states.

Preventive prompt:

"For every async data fetch, add a corresponding Suspense boundary with
a skeleton component. Generate the skeleton too."

Pitfall 3: Incorrect shadcn import paths

Occasionally Claude Code imports from the wrong path.

Preventive CLAUDE.md addition:

## shadcn Import Paths
All shadcn components: `import { X } from "@/components/ui/x"`
Never import from "shadcn/ui" directly.

Pitfall 4: Forgetting error boundaries

"Add an error boundary to the data fetching section:
create app/dashboard/error.tsx with a simple 'Something went wrong' 
retry UI."

Full Page Generation Example

This prompt generates a complete, production-ready page:



"Create the billing management page at app/dashboard/billing/page.tsx:

Server Component. Fetch:
- Current subscription plan from users.plan column
- Usage this billing period (sum of usageRecords.totalCost for current month)
- Next billing date from Polar subscription API

UI Layout:
- Page header: 'Billing & Usage' with Plan badge (Free/Starter/Pro)
- Current Plan card: plan name, monthly price, features list, Upgrade CTA
  (if Free: Upgrade button linking to Polar checkout)
  (if paid: Manage Subscription button)
- Usage this period card: bar showing $X of $Y limit
- Payment history table: last 6 invoices (date, amount, status, download PDF link)
  (mock data if Polar integration not available)

Components:
- Extract <UsageMeter /

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*30-day money-back guarantee. Instant download.*

Claude Code 완벽 가이드: 설치부터 고급 활용까지 (2026)

Sangmin Lee — Tue, 16 Jun 2026 01:30:05 +0000

Originally published at claudeguide.io/claude-code-korean-guide

Claude Code 완벽 가이드: 설치부터 고급 활용까지 (2026)

Claude Code는 터미널에서 실행하는 AI 코딩 에이전트다 (2026 기준). npm install -g @anthropic-ai/claude-code 한 줄로 설치하고, 프로젝트 폴더에서 claude 명령어를 입력하면 즉시 사용 가능하다. 단순한 코드 자동완성이 아니라, 파일을 직접 읽고 수정하고 터미널 명령어를 실행하는 자율 에이전트다. 이 가이드는 설치부터 CLAUDE.md 고급 설정, MCP 서버 연동, 서브에이전트 병렬 작업까지 모든 것을 다룬다.

설치 및 초기 설정

1단계: Node.js 확인

Claude Code는 Node.js 18 이상이 필요하다.

node --version   # v18.0.0 이상이어야 함

Node.js가 없거나 버전이 낮으면 nodejs.org에서 최신 LTS 버전을 설치한다.

2단계: Claude Code 설치

npm install -g @anthropic-ai/claude-code

설치 후 버전 확인:

claude --version

3단계: Anthropic 계정 인증

claude

첫 실행 시 브라우저가 열리면서 Anthropic 계정 로그인을 요청한다. Claude.ai Pro 또는 Max 구독이 있거나, Anthropic API 키가 있으면 인증된다.

API 키로 직접 인증하려면:

export ANTHROPIC_API_KEY="sk-ant-api03-..."
claude

기본 사용법

대화형 모드

프로젝트 폴더에서 claude를 입력하면 대화형 모드가 시작된다:

프로젝트 루트에서:
$ cd ~/projects/my-app
$ claude

주요 슬래시 커맨드

명령어	기능
`/help`	사용 가능한 모든 커맨드 목록
`/clear`	현재 대화 컨텍스트 초기화
`/compact`	컨텍스트 압축 (긴 세션용)
`/doctor`	환경 진단 (권한, MCP 상태 등)
`/init`	CLAUDE.md 초기화
`/model`	사용 모델 전환 (Haiku/Sonnet/Opus)

비대화형 1회성 실행

# 코드 리뷰 요청
claude "이 PR의 diff를 검토하고 보안 이슈를 찾아줘"

# 파일 분석
claude "src/auth/login.ts 파일의 취약점을 찾아줘"

# 테스트 작성
claude "UserService 클래스에 대한 unit test를 작성해줘"

CLAUDE.md — 프로젝트 설정 파일

CLAUDE.md는 Claude Code에게 프로젝트 컨텍스트를 알려주는 설정 파일이다. 프로젝트 루트에 CLAUDE.md를 만들면 모든 세션에서 자동으로 로드된다.

기본 템플릿

# 프로젝트 개요

이 프로젝트는 Next.js 15 + TypeScript로 만든 SaaS 앱입니다.
DB: PostgreSQL (Drizzle ORM), 인증: Clerk, 배포: Vercel.

## 코드 스타일

- TypeScript strict 모드 사용
- 컴포넌트: App Router (서버 컴포넌트 우선)
- CSS: Tailwind CSS (shadcn/ui 컴포넌트)
- 테스트: Vitest + Testing Library
- 절대 `console.log` 커밋 금지

## 디렉토리 구조

- `app/` — Next.js 라우터 (App Router)
- `lib/` — 공유 유틸리티 및 DB 클라이언트
- `components/` — 재사용 가능한 UI 컴포넌트

## 개발 명령어

bash
bun run dev # 개발 서버
bun run build # 프로덕션 빌드
bun run test # 테스트 실행
bun run typecheck # 타입 체크


## 중요 제약사항

- DB 마이그레이션은 항상 `bun run db:migrate` 사용
- API 키는 절대 코드에 하드코딩 금지
- Prisma 대신 Drizzle ORM 사용

markdown

CLAUDE.md 고급 활용

자주 쓰는 패턴 기록:

## 반복 패턴

새 API 라우트 추가 시 이 파일을 참고: `app/api/_template/route.ts`
새 DB 테이블 추가 시: schema.ts에 추가 → `bun run db:generate` → `bun run db:migrate`

외부 문서 참조:

## 관련 문서

- API 스펙: docs/api-spec.md
- DB 스키마: docs/schema.md
- 배포 가이드: docs/deploy.md

권한 설정 (`.claude/settings.json`)

Claude Code는 파일 수정, 터미널 실행, 웹 검색 등 강력한 권한을 요청한다. .claude/settings.json으로 세밀하게 제어할 수 있다.

{
  "permissions": {
    "allow": [
      "Bash(bun run *)",
      "Bash(git log *)",
      "Bash(git diff *)",
      "Bash(cat *)",
      "Bash(ls *)"
    ],
    "deny": [
      "Bash(rm -rf *)",
      "Bash(git push --force *)"
    ]
  }
}

팁: /doctor 명령어로 현재 권한 상태를 확인할 수 있다.

MCP 서버 연동

MCP(Model Context Protocol)는 Claude Code가 외부 서비스와 연동할 수 있게 해주는 프로토콜이다. GitHub, Slack, 데이터베이스, 웹 검색 등을 Claude Code에서 직접 제어할 수 있다.

MCP 서버 추가 방법

# GitHub MCP 서버 추가
claude mcp add github npx @modelcontextprotocol/server-github

# Filesystem MCP 서버 (로컬 파일 접근)
claude mcp add filesystem npx @modelcontextprotocol/server-filesystem /path/to/dir

또는 ~/.claude/settings.json에 직접 추가:

{
  "mcpServers": {
    "github": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"],
      "env": {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_..."
      }
    },
    "sqlite": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-sqlite", "database.db"]
    }
  }
}

한국 개발자에게 유용한 MCP 서버

MCP 서버	용도	설치 명령
`@modelcontextprotocol/server-github`	PR 리뷰, 이슈 관리	`npx @modelcontextprotocol/server-github`
`@modelcontextprotocol/server-filesystem`	대용량 파일 접근	`npx @modelcontextprotocol/server-filesystem`
`@modelcontextprotocol/server-postgres`	DB 직접 쿼리	`npx @modelcontextprotocol/server-postgres`
`@modelcontextprotocol/server-brave-search`	웹 검색	`npx @modelcontextprotocol/server-brave-search`

서브에이전트 활용 (병렬 작업)

Claude Code의 가장 강력한 기능 중 하나다. 서브에이전트를 사용하면 여러 작업을 동시에 실행할 수 있다.

기본 서브에이전트 패턴

Claude Code에게 지시:
"다음 3개 모듈을 동시에 리팩토링해줘:
1. src/auth/login.ts — 타입 안전성 개선
2. src/db/queries.ts — N+1 쿼리 제거
3. src/api/users.ts — 에러 핸들링 추가
각각 별도 서브에이전트로 실행해줘"

Claude Code는 3개의 서브에이전트를 병렬로 생성해 동시에 작업한다. 순차 실행 대비 3배 빠르다.

서브에이전트 실전 활용 사례

테스트 병렬 작성:

"UserService, AuthService, PaymentService 각각의 unit test를 
별도 서브에이전트로 동시에 작성해줘. Vitest 사용."

멀티 파일 리팩토링:

"app/api/ 폴더의 모든 라우트에 Zod 입력 검증을 추가해줘.
파일당 서브에이전트 하나씩 병렬로 처리해줘."

코드베이스 분석:

"다음을 병렬로 분석해줘:
- 보안 취약점 (SQL injection, XSS)
- 성능 문제 (N+1 쿼리, 불필요한 렌더링)
- 타입 에러 (strict 모드 기준)"

Plan Mode (계획 모드)

복잡한 작업 전에 Plan Mode로 실행 계획을 미리 검토할 수 있다.

# Plan Mode 진입
claude --plan

# 또는 대화 중
/plan

Plan Mode에서 Claude Code는:

변경할 파일 목록을 먼저 보여준다
각 파일에서 할 작업을 설명한다
예상되는 부작용을 경고한다

사용자가 승인하면 실제 실행한다. 대규모 리팩토링이나 DB 마이그레이션 전에 반드시 Plan Mode 사용을 권장한다.

실전 워크플로우 — 한국 스타트업 개발자 패턴

아침 코드 리뷰

cd ~/projects/my-app
claude "어제 생성된 PR들의 diff를 요약하고 리뷰 포인트를 알려줘"

버그 수정

claude "에러 로그: 'Cannot read property of undefined at UserService.ts:42'
이 에러를 찾아서 수정하고 관련 테스트도 추가해줘"

새 기능 개발

claude "결제 이력 페이지를 만들어줘:
- app/dashboard/payments/page.tsx
- Drizzle로 payments 테이블 조회
- 페이지네이션 (페이지당 20개)
- 날짜 필터 (이번 달/지난 달/전체)
- shadcn/ui Table 컴포넌트 사용"

배포 전 체크

claude "배포 전 체크리스트 실행:
1. 타입 에러 없는지 확인
2. 테스트 전체 통과 확인
3. 환경 변수 누락 없는지 확인
4. 보안 취약점 스캔"

비용 관리 팁

Claude Code는 Anthropic API를 사용하므로 비용이 발생한다. 효율적으로 사용하려면:

모델 선택:

/model haiku    # 빠르고 저렴 (단순 작업)
/model sonnet   # 기본값 (대부분의 작업)
/model opus     # 복잡한 설계 결정 (비쌈)

컨텍스트 최적화:

/clear — 불필요한 컨텍스트 초기화
/compact — 긴 세션 압축
CLAUDE.md — 반복 설명 제거

비용 절감 추정:

Haiku: 작업당 ~$0.002
Sonnet: 작업당 ~$0.02
Opus: 작업당 ~$0.10-0.30

하루 50번 작업 기준: Sonnet $1/일, Haiku $0.10/일.

자주 묻는 질문

Q: Claude Code와 일반 Claude 채팅의 차이는?
Claude 채팅은 코드를 보여주기만 하지만, Claude Code는 실제로 파일을 수정하고 명령어를 실행한다. 코드를 복사-붙여넣기할 필요가 없다.

Q: 회사 코드베이스에서 사용해도 안전한가?
Anthropic은 API 요청을 학습 데이터로 사용하지 않는다. 단, 민감한 시크릿(API 키, 비밀번호)이 코드에 있으면 컨텍스트로 전송되므로 주의해야 한다.

Q: VS Code에서 사용할 수 있나?
VS Code 터미널에서 claude 명령어를 실행하면 된다. 별도 Extension은 없지만, 터미널 통합으로 충분히 사용 가능하다.

Q: Cursor와의 차이는?
Cursor는 VS Code UI 내에서 인라인 코드 수정에 강하다. Claude Code는 터미널 기반으로 자율 에이전트 작업(여러 파일 동시 수정, 명령어 실행, 장기 작업)에 강하다. 상세 비교 참고.

Q: macOS가 아닌 Windows/Linux에서도 되나?
된다. Windows는 WSL2(Windows Subsystem for Linux)에서 사용을 권장한다. Linux는 그냥 터미널에서 사용.

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Claude Code for Data Science: Jupyter and Notebook Workflows

Sangmin Lee — Mon, 15 Jun 2026 01:31:37 +0000

Originally published at claudeguide.io/claude-code-jupyter

Claude Code for Data Science: Jupyter and Notebook Workflows

Claude Code works with Jupyter notebooks through two paths: the CLI that can read and run notebook cells, and direct .ipynb file editing that treats notebook JSON as structured data. For most data science workflows, the most effective pattern is using Claude Code in the terminal alongside an open notebook — Claude generates code, you paste and run, iterate in 2026. This guide covers the patterns that work for EDA, visualization, and model development.

Setup: CLAUDE.md for Data Science Projects

# data-project CLAUDE.md

## Environment
- Python 3.12, Jupyter Lab
- Package manager: uv or pip
- Key packages: pandas, numpy, matplotlib, seaborn, scikit-learn, polars

## Data Conventions
- Raw data: data/raw/ (read-only, never modified)
- Processed: data/processed/
- Outputs: data/outputs/ (figures, reports)
- Column naming: snake_case
- Date columns: always parse as datetime, store UTC

## Code Style
- Type hints on functions
- Docstrings on public functions
- No magic numbers — name your constants
- DataFrames: prefer method chaining over intermediate variables

## Notebook Conventions
- First cell: imports only
- Second cell: configuration/constants
- Each analysis section: one markdown cell explaining what/why, then code cell(s)
- Save figures: always save to data/outputs/ in addition to displaying

## Testing
- Tests for data transformation functions: tests/
- Use pytest

Pattern 1: EDA (Exploratory Data Analysis)

# Generate a complete EDA notebook for a dataset
claude "Write Jupyter notebook cells for EDA on this dataset:
File: data/raw/sales_2026.csv
Known columns: date, product_id, quantity, price, region, customer_id

Generate cells for:
1. Load and basic info (shape, dtypes, head)
2. Missing value analysis (heatmap + counts)
3. Distribution of numeric columns (histograms)
4. Time series: monthly revenue trend
5. Top 10 products by revenue
6. Regional breakdown (bar chart)

Use seaborn for plots, save each figure to data/outputs/.
Each section: markdown explanation cell + code cell."

Generated output (example of one section):


python
# Cell: Missing Value Analysis
import missingno as msno
import matplotlib.pyplot as plt

# Count missing values
missing = df.isnull().sum()
missing_pct = (missing / len(df) * 100).sort_values(ascending=False)
missing_df = pd.DataFrame({'count': missing, 'pct': missing_pct})
print(missing_df[missing_df['count'] 

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Context Window Management in Claude Code: Long Sessions Guide

Sangmin Lee — Mon, 15 Jun 2026 01:30:54 +0000

Originally published at claudeguide.io/claude-code-context-window-management

Context Window Management in Claude Code: Keep Performance Sharp in Long Sessions

Claude Code's context window holds everything it can "see" — your CLAUDE.md, the files it has read, your conversation history, and its responses. When the context fills up, quality degrades before you hit the hard limit, and the fix is knowing when to prune, redirect, or start fresh in 2026. Claude's 200k token window is large, but multi-hour development sessions can consume it. This guide explains what fills the context, how to detect degradation, and the concrete steps to manage it.

What Goes into the Context Window

In a Claude Code session, the context accumulates:

Source	Tokens (typical)	Notes
CLAUDE.md	300-1,000	Loaded at session start
Files read	500-2,000 per file	Stays in context after reading
Your messages	50-300 per message	Accumulates across turns
Claude's responses	200-2,000 per response	Accumulates across turns
Tool output (bash, read)	Variable	Large outputs stay in context
System prompt	~500	Claude Code's internal instructions

A typical 2-hour session uses: 40,000-100,000 tokens. A very long session (4+ hours, large codebase, many files read): 150,000-190,000 tokens — approaching the limit.

Signs the Context Is Getting Full

Sign 1: Claude "forgets" earlier instructions

If Claude stops following a rule you established 30 messages ago, the context is likely too full. Earlier messages get less attention as context grows — they're not deleted, but their effective influence decreases.

# Early in session:
You: "Always use the cursor pagination pattern from lib/db/pagination.ts"

# 40 messages later:
Claude generates offset-based pagination instead

→ Context saturation sign

Sign 2: Responses become more generic

Claude starts giving solutions that don't fit your specific codebase — using patterns it knows generally rather than patterns from your files.

Sign 3: Claude asks for information it already has

"Could you share the relevant schema?" when it read schema.ts two hours ago — the file is still technically in context but below the effective attention threshold.

Sign 4: Slower, longer responses

As context fills, the model has more to process per token generated. Noticeable latency increase is a soft signal.

Strategy 1: Proactive Context Pruning

Tell Claude what context is no longer relevant:

We've finished implementing the auth changes. That's complete.
For the rest of this session, focus on the payment module.
The auth-related files and discussion are no longer relevant — don't reference them.

@app/api/webhooks/route.ts @lib/stripe/

Let's now implement the subscription upgrade flow.

This doesn't delete the old context — it's still there — but explicitly directing Claude's attention helps it weight recent, relevant context more heavily.

Strategy 2: Summarize Before Pivoting

At natural pivot points, ask Claude to summarize what's been decided before you redirect:

Before we move to the next feature, give me a summary of:
1. What we implemented in this session
2. Any decisions we made that should be in CLAUDE.md
3. Any unresolved questions or TODOs

I'll use this to update CLAUDE.md, then we'll start fresh for the next feature.

Copy the important decisions into CLAUDE.md, then either start a new session or redirect.

Strategy 3: Fresh Sessions for Distinct Features

The cleanest context management strategy: separate sessions for separate features.

Session 1: Implement user authentication (2 hours)
→ Update CLAUDE.md with any new decisions
→ End session

Session 2: Implement billing (2 hours)
→ Starts with full 200k window
→ CLAUDE.md has all the decisions from Session 1

This is better than one 4-hour session because:

Full context attention for each feature
No cross-contamination between feature implementations
Each session's CLAUDE.md reading is more effective with a fresh window

Strategy 4: Reference Files Instead of Pasting

When you need Claude to see code, reference it rather than pasting:

# Worse — fills context immediately with the full file
Here's our entire user service: [paste 500 lines]

# Better — Claude reads what it needs, can re-read if needed
@lib/services/user.ts — look at the getUserById function specifically

@file references tell Claude to read the file, which it does once and caches. Pasting code puts the full content into your message history permanently.

Strategy 5: Use `--max-turns` for Bounded Tasks

When running Claude Code for automated or background tasks, limit turns to prevent unbounded context accumulation:

# Limit to 10 turns maximum for this task
claude --print --max-turns 10 \
  "Run tests, identify failures, fix the failing tests. Stop after 10 turns."

This prevents runaway sessions that fill the context and loop unnecessarily.

The Checkpoint Pattern

For long development sessions, checkpoint at the end of each logical unit:

Checkpoint: We've completed the user profile feature.
Please do the following:
1. List every file you modified this session
2. Summarize the key decisions and patterns we established
3. List any TODOs or follow-ups we identified

I'll commit these changes and update CLAUDE.md before continuing.

This forces a useful summary, helps you catch anything missed, and gives you a clean break point.

When to Start a New Session vs. Continue

Continue the session when:

You're in the middle of implementing something coherent
The files you've loaded are still relevant
Claude is still following your conventions correctly
Session is under 2 hours old

Start a new session when:

You're starting a genuinely new feature unrelated to current context
Claude has stopped following conventions consistently
The session has been running 3+ hours
You've just completed a logical unit (feature, bug fix, refactor sprint)

Quick test: Ask Claude to repeat a rule you established early in the session. If it gets it right, context is fine. If it fumbles or responds generically, start fresh.

Token Budget Estimation

Rough math for planning:

# Rough context budget for a Claude Code session

CLAUDE_MD = 800          # Typical CLAUDE.md
SYSTEM_PROMPT = 500      # Claude Code internals
FILES_LOADED = 1500 * 10 # 10 files × 1,500 tokens each
CONVERSATION = 300 * 30  # 30 turns × 300 tokens average per exchange

total = CLAUDE_MD + SYSTEM_PROMPT + FILES_LOADED + CONVERSATION
# = 800 + 500 + 15,000 + 9,000 = ~25,300 tokens

# Still have ~175,000 tokens available at this point
# At this rate (30 turns, 10 files) you could go ~7x longer
# = about 210 turns or 70 files before nearing limits

For most developers, hitting context limits in a single session is rare unless you're loading large files repeatedly or having very long conversations. The degradation in quality usually matters before the hard limit.

Frequently Asked Questions

What happens when Claude Code hits the context limit?
Claude Code will give an error or truncate gracefully, depending on the implementation. Before hitting the hard limit, you'll see quality degradation — Claude ignoring earlier instructions or giving generic responses.

Can I see how many tokens I've used in a session?
Not directly in the Claude Code CLI interface. You can estimate based on files loaded and message count using the rough math above. The Anthropic API returns token usage in responses if you're using the SDK directly.

Does starting a new session lose my project context?
No — CLAUDE.md persists between sessions. Only the conversation history and dynamically read files are lost. This is why CLAUDE.md is valuable: it's your "save state" that every new session starts with.

Should I keep CLAUDE.md short to save context?
Yes, but not at the expense of important information. 300-800 tokens is a good target. Every token in CLAUDE.md is read on every session start — make each token count. Trim generalities; keep specifics.

Does Claude Code compress conversation history automatically?
Claude Code does not automatically compress or summarize conversation history. This is intentional — you control what's in context. Use the checkpoint and prune strategies manually.

Related Guides

Context Engineering for Claude — Designing what goes into context
Claude Code Complete Guide — All Claude Code features
Token Counting: Why Your Estimates Are Wrong — Token math deep dive

Go Deeper

Power Prompts 300 — $29 — Includes session management patterns, CLAUDE.md templates for different project types, and checkpoint prompt templates that extract maximum value at each session end.

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