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veeramanikandanr48

Agent Development

by Veera · GitHub ↗ · v0.1.0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install agent-development
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.
README (SKILL.md)

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 \x3C\x3C '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-01HTML-05HTML-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
Usage Guidance
This skill is coherent with its stated purpose (agent design) but it encourages persistent, broad permission changes that increase security risk. Before following its recommendations: (1) Do not blindly apply the .claude/settings.json allowlist—narrow allowed WebFetch domains and Bash patterns to the minimum required. Avoid WebFetch(domain:*) wildcard if you care about data exfiltration. (2) Prefer per-agent tool lists rather than 'give all tools to all agents'; grant Bash/Write only to agents that truly need them. (3) Back up ~/.bashrc before changing NODE_OPTIONS and prefer setting NODE_OPTIONS per-session or per-service rather than globally if possible. (4) Review any allowlist commands to ensure they don't permit destructive shell operations or access to sensitive paths (e.g., ~/.ssh, /etc). (5) Test changes in a sandboxed environment or non-production account first. (6) If you intend to follow the skill's guidance in a team or production environment, get an explicit security review and restrict agent permissions with least privilege. The lack of code files means no immediate code-execution risk from the skill itself, but the operational recommendations materially expand agent privileges—treat those changes with caution.
Capability Analysis
Type: OpenClaw Skill Name: agent-development Version: 0.1.0 This skill bundle is designed to teach users how to build powerful OpenClaw agents. It is classified as suspicious due to its explicit recommendations for granting broad permissions to agents. Specifically, it advises configuring `.claude/settings.json` with `WebFetch(domain:*)` and an extensive allowlist of `Bash` commands (e.g., `cd`, `cp`, `ls`, `cat`, `find`, `echo`, `grep`, `mv`, `for`, `cut`), as detailed in `SKILL.md` and `rules/custom-agent-instructions.md`. While the stated intent is to enable agents to operate autonomously without constant human approval, these broad permissions for network access and system command execution introduce significant risk, as they could be leveraged for data exfiltration or unauthorized system manipulation if an agent were compromised or given a malicious prompt, even though the skill bundle itself does not contain instructions for such malicious actions.
Capability Assessment
Purpose & Capability
The skill is about designing Claude Code agents and the provided instructions and rules directly address that topic. Recommending agent description patterns, prompt structure, and delegation is coherent. However, several recommended operational changes (giving all agents Read/Write/Edit/Bash, wildcard WebFetch, and editing global .claude/settings.json) are broader than strictly necessary for 'design guidance' and shift from guidance into privileged configuration changes.
Instruction Scope
SKILL.md instructs the user to (a) give broad tool access to agents (Read, Write, Edit, Glob, Grep, Bash), (b) allowlist many Bash patterns and WebFetch(domain:*), and (c) change ~/.bashrc for NODE_OPTIONS. These instructions are not limited to documentation—they direct persistent configuration changes and global permission expansion that let agents read/write files, run shell commands, and fetch from any domain, increasing the attack surface and enabling inadvertent data access or exfiltration.
Install Mechanism
This is an instruction-only skill with no install spec and no code to execute. That minimizes code-delivery risk because nothing is downloaded or executed by the skill itself.
Credentials
The skill requests no environment variables, but explicitly tells users to edit persistent environment (NODE_OPTIONS in ~/.bashrc) and system config (.claude/settings.json) to grant broad permissions (especially WebFetch(domain:*), Bash allowlists). Those persistent changes are disproportionate for mere guidance and could grant agents access to data and networks unrelated to the specific agent tasks.
Persistence & Privilege
Although the skill is not 'always:true' and doesn't autonomously install, it instructs making persistent, global configuration changes (.claude/settings.json and shell rc). Those changes affect the platform's privilege model across agents (global allowlists and broader tool grants), increasing long-term risk beyond a single agent.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install agent-development
  3. After installation, invoke the skill by name or use /agent-development
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
agent-development 0.1.0 — Initial Release - Provides guidelines for designing and building custom Claude Code agents. - Documents strong agent description patterns for effective auto-delegation. - Explains tool access principles and safe command allowlisting. - Details best practices for model selection, memory limits, and sub-agent usage. - Offers declarative prompt design templates and self-documentation recommendations. - Includes workflow tips for agent pipelines and effective prompt structuring.
Metadata
Slug agent-development
Version 0.1.0
License
All-time Installs 25
Active Installs 24
Total Versions 1
Frequently Asked Questions

What is 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. It is an AI Agent Skill for Claude Code / OpenClaw, with 3119 downloads so far.

How do I install Agent Development?

Run "/install agent-development" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Agent Development free?

Yes, Agent Development is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Agent Development support?

Agent Development is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Agent Development?

It is built and maintained by Veera (@veeramanikandanr48); the current version is v0.1.0.

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