AGENT SKILL

agent-development

Design and build custom Claude Code agents with effective descriptions, tool access patterns, and self-documenting prompts. Covers Task tool delegation, model selection, memory limits, and declarative instruction design. Use when: creating custom agents, designing agent descriptions for auto-delegation, troubleshooting agent memory issues, or building agent pipelines.

License 许可
MIT
最近更新
2026-03-07
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★ 674
Forks
102

01 前言 Front Matter

name
agent-development
license
MIT
description
Design and build custom Claude Code agents with effective descriptions, tool access patterns, and self-documenting prompts. Covers Task tool delegation, model selection, memory limits, and declarative instruction design. Use when: creating custom agents, designing agent descriptions for auto-delegation, troubleshooting agent memory issues, or building agent pipelines.

02 资源文件 7

03 SKILL.md 正文

Agent Development for Claude Code

Build effective custom agents for Claude Code with proper delegation, tool access, and prompt design.

Agent Description Pattern

The description field determines whether Claude will automatically delegate tasks.

Strong Trigger Pattern

---
name: agent-name
description: |
  [Role] specialist. MUST BE USED when [specific triggers].
  Use PROACTIVELY for [task category].
  Keywords: [trigger words]
tools: Read, Write, Edit, Glob, Grep, Bash
model: sonnet
---

Weak vs Strong Descriptions

Weak (won't auto-delegate) Strong (auto-delegates)
"Analyzes screenshots for issues" "Visual QA specialist. MUST BE USED when analyzing screenshots. Use PROACTIVELY for visual QA."
"Runs Playwright scripts" "Playwright specialist. MUST BE USED when running Playwright scripts. Use PROACTIVELY for browser automation."

Key phrases:

  • "MUST BE USED when..."
  • "Use PROACTIVELY for..."
  • Include trigger keywords

Delegation Mechanisms

  1. Explicit: Task tool subagent_type: "agent-name" - always works
  2. Automatic: Claude matches task to agent description - requires strong phrasing

Session restart required after creating/modifying agents.

Tool Access Principle

If an agent doesn't need Bash, don't give it Bash.

Agent needs to... Give tools Don't give
Create files only Read, Write, Edit, Glob, Grep Bash
Run scripts/CLIs Read, Write, Edit, Glob, Grep, Bash —
Read/audit only Read, Glob, Grep Write, Edit, Bash

Why? Models default to cat > file << 'EOF' heredocs instead of Write tool. Each bash command requires approval, causing dozens of prompts per agent run.

Allowlist Pattern

Instead of restricting Bash, allowlist safe commands in .claude/settings.json:

{
  "permissions": {
    "allow": [
      "Write", "Edit", "WebFetch(domain:*)",
      "Bash(cd *)", "Bash(cp *)", "Bash(mkdir *)", "Bash(ls *)",
      "Bash(cat *)", "Bash(head *)", "Bash(tail *)", "Bash(grep *)",
      "Bash(diff *)", "Bash(mv *)", "Bash(touch *)", "Bash(file *)"
    ]
  }
}

Model Selection (Quality First)

Don't downgrade quality to work around issues - fix root causes instead.

Model Use For
Opus Creative work (page building, design, content) - quality matters
Sonnet Most agents - content, code, research (default)
Haiku Only script runners where quality doesn't matter

Memory Limits

Root Cause Fix (REQUIRED)

Add to ~/.bashrc or ~/.zshrc:

export NODE_OPTIONS="--max-old-space-size=16384"

Increases Node.js heap from 4GB to 16GB.

Parallel Limits (Even With Fix)

Agent Type Max Parallel Notes
Any agents 2-3 Context accumulates; batch then pause
Heavy creative (Opus) 1-2 Uses more memory

Recovery

  1. source ~/.bashrc or restart terminal
  2. NODE_OPTIONS="--max-old-space-size=16384" claude
  3. Check what files exist, continue from there

Sub-Agent vs Remote API

Always prefer Task sub-agents over remote API calls.

Aspect Remote API Call Task Sub-Agent
Tool access None Full (Read, Grep, Write, Bash)
File reading Must pass all content in prompt Can read files iteratively
Cross-referencing Single context window Can reason across documents
Decision quality Generic suggestions Specific decisions with rationale
Output quality ~100 lines typical 600+ lines with specifics
// ❌ WRONG - Remote API call
const response = await fetch('https://api.anthropic.com/v1/messages', {...})

// ✅ CORRECT - Use Task tool
// Invoke Task with subagent_type: "general-purpose"

Declarative Over Imperative

Describe what to accomplish, not how to use tools.

Wrong (Imperative)

### Check for placeholders
```bash
grep -r "PLACEHOLDER:" build/*.html

### Right (Declarative)

```markdown
### Check for placeholders
Search all HTML files in build/ for:
- PLACEHOLDER: comments
- TODO or TBD markers
- Template brackets like [Client Name]

Any match = incomplete content.

What to Include

Include Skip
Task goal and context Explicit bash/tool commands
Input file paths "Use X tool to..."
Output file paths and format Step-by-step tool invocations
Success/failure criteria Shell pipeline syntax
Blocking checks (prerequisites) Micromanaged workflows
Quality checklists

Self-Documentation Principle

"Agents that won't have your context must be able to reproduce the behaviour independently."

Every improvement must be encoded into the agent's prompt, not left as implicit knowledge.

What to Encode

Discovery Where to Capture
Bug fix pattern Agent's "Corrections" or "Common Issues" section
Quality requirement Agent's "Quality Checklist" section
File path convention Agent's "Output" section
Tool usage pattern Agent's "Process" section
Blocking prerequisite Agent's "Blocking Check" section

Test: Would a Fresh Agent Succeed?

Before completing any agent improvement:

  1. Read the agent prompt as if you have no context
  2. Ask: Could a new session follow this and produce the same quality?
  3. If no: Add missing instructions, patterns, or references

Anti-Patterns

Anti-Pattern Why It Fails
"As we discussed earlier..." No prior context exists
Relying on files read during dev Agent may not read same files
Assuming knowledge from errors Agent won't see your debugging
"Just like the home page" Agent hasn't built home page

Agent Prompt Structure

Effective agent prompts include:

## Your Role
[What the agent does]

## Blocking Check
[Prerequisites that must exist]

## Input
[What files to read]

## Process
[Step-by-step with encoded learnings]

## Output
[Exact file paths and formats]

## Quality Checklist
[Verification steps including learned gotchas]

## Common Issues
[Patterns discovered during development]

Pipeline Agents

When inserting a new agent into a numbered pipeline (e.g., HTML-01 → HTML-05 → HTML-11):

Must Update What
New agent "Workflow Position" diagram + "Next" field
Predecessor agent Its "Next" field to point to new agent

Common bug: New agent is "orphaned" because predecessor still points to old next agent.

Verification:

grep -n "Next:.*→\|Then.*runs next" .claude/agents/*.md

The Sweet Spot

Best use case: Tasks that are repetitive but require judgment.

Example: Auditing 70 skills manually = tedious. But each audit needs intelligence (check docs, compare versions, decide what to fix). Perfect for parallel agents with clear instructions.

Not good for:

  • Simple tasks (just do them)
  • Highly creative tasks (need human direction)
  • Tasks requiring cross-file coordination (agents work independently)

Effective Prompt Template

For each [item]:
1. Read [source file]
2. Verify with [external check - npm view, API call, etc.]
3. Check [authoritative source]
4. Score/evaluate
5. FIX issues found ← Critical instruction

Key elements:

  • "FIX issues found" - Without this, agents only report. With it, they take action.
  • Exact file paths - Prevents ambiguity
  • Output format template - Ensures consistent, parseable reports
  • Batch size ~5 items - Enough work to be efficient, not so much that failures cascade

Workflow Pattern

1. ME: Launch 2-3 parallel agents with identical prompt, different item lists
2. AGENTS: Work in parallel (read → verify → check → edit → report)
3. AGENTS: Return structured reports (score, status, fixes applied, files modified)
4. ME: Review changes (git status, spot-check diffs)
5. ME: Commit in batches with meaningful changelog
6. ME: Push and update progress tracking

Why agents don't commit: Allows human review, batching, and clean commit history.

Signs a Task Fits This Pattern

Good fit:

  • Same steps repeated for many items
  • Each item requires judgment (not just transformation)
  • Items are independent (no cross-item dependencies)
  • Clear success criteria (score, pass/fail, etc.)
  • Authoritative source exists to verify against

Bad fit:

  • Items depend on each other's results
  • Requires creative/subjective decisions
  • Single complex task (use regular agent instead)
  • Needs human input mid-process

Quick Reference

Agent Frontmatter Template

---
name: my-agent
description: |
  [Role] specialist. MUST BE USED when [triggers].
  Use PROACTIVELY for [task category].
  Keywords: [trigger words]
tools: Read, Write, Edit, Glob, Grep, Bash
model: sonnet
---

Fix Bash Approval Spam

  1. Remove Bash from tools if not needed
  2. Put critical instructions FIRST (right after frontmatter)
  3. Use allowlists in .claude/settings.json

Memory Crash Recovery

export NODE_OPTIONS="--max-old-space-size=16384"
source ~/.bashrc && claude

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