EN

enhance-agent-prompts

Improves AI agent instruction sets and configuration parameters.

Install

mkdir -p .claude/skills/enhance-agent-prompts && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/3239" && unzip -o skill.zip -d .claude/skills/enhance-agent-prompts && rm skill.zip

Installs to .claude/skills/enhance-agent-prompts

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Use when improving agent prompts, frontmatter, and tool restrictions.
69 chars✓ has a “when” trigger
Intermediate

Key capabilities

  • Analyze agent prompt files
  • Validate frontmatter structure
  • Enforce tool usage restrictions
  • Apply auto-fixes for prompt patterns

How it works

It parses agent markdown files to check against 30 predefined prompt engineering patterns, reporting issues and optionally applying fixes.

Inputs & outputs

You give it
Path to agent markdown file
You get back
Analysis report or auto-fixed file

When to use enhance-agent-prompts

  • Update system prompt frontmatter
  • Restrict available tools for an agent
  • Improve agent instruction clarity
  • Adjust agent behavioral parameters

About this skill

enhance-agent-prompts

Analyze agent prompt files for prompt engineering best practices.

Parse Arguments

const args = '$ARGUMENTS'.split(' ').filter(Boolean);
const targetPath = args.find(a => !a.startsWith('--')) || '.';
const fix = args.includes('--fix');
const verbose = args.includes('--verbose');

Agent File Locations

PlatformGlobalProject
Claude Code~/.claude/agents/*.md.claude/agents/*.md
OpenCode~/.config/opencode/agents/*.md.opencode/agents/*.md
Codex~/.codex/skills/AGENTS.md

Workflow

  1. Discover - Find agent .md files
  2. Parse - Extract frontmatter, analyze content
  3. Check - Run 30 pattern checks
  4. Report - Generate markdown output
  5. Fix - Apply auto-fixes if --fix flag

Detection Patterns

1. Frontmatter (HIGH)

---
name: agent-name              # Required: kebab-case
description: "What and when"  # Required: WHEN to use (see "Intern Test")
tools: Read, Glob, Grep       # Required: restricted list
model: sonnet                 # Optional: opus | sonnet | haiku
---

Model Selection:

  • opus: Complex reasoning, errors compound
  • sonnet: Most agents, validation
  • haiku: Mechanical execution, no judgment

Tool Syntax: Read, Read(src/**), Bash(git:*), Bash(npm:*)

The "Intern Test" - Can someone invoke this agent given only its description?

# Bad
description: Reviews code

# Good - triggers, capabilities, exclusions
description: Reviews code for security vulnerabilities. Use for PRs touching auth, API, data handling. Not for style reviews.

2. Structure (HIGH)

Required sections: Role ("You are..."), Output format, Constraints

Position-aware order (LLMs recall START/END better than MIDDLE):

  1. Role/Identity (START)
  2. Capabilities, Workflow, Examples
  3. Constraints (END)

3. Instruction Effectiveness (HIGH)

Positive over negative:

  • Bad: "Don't assume file paths exist"
  • Good: "Verify file paths using Glob before reading"

Strong constraint language:

  • Bad: "should", "try to", "consider"
  • Good: "MUST", "ALWAYS", "NEVER"

Include WHY for important rules - motivation improves compliance.

4. Tool Configuration (HIGH)

Principle of Least Privilege:

Agent TypeTools
Read-onlyRead, Glob, Grep
Code modifierRead, Edit, Write, Glob, Grep
Git opsBash(git:*)
Build/testBash(npm:*), Bash(node:*)

Issues:

  • Bash without scope → should be Bash(git:*)
  • Task in subagent → subagents cannot spawn subagents
  • 20 tools → increases error rates ("Less-is-More")

5. Subagent Config (MEDIUM)

context: fork  # Isolated context for verbose output
  • Subagents cannot spawn subagents (no Task in tools)
  • Return summaries, not full output

Cross-platform modes:

PlatformPrimarySubagent
Claude CodeDefaultVia Task tool
OpenCodemode: primarymode: subagent
CodexSkillsMCP server

6. XML Structure (MEDIUM)

Use XML tags when 5+ sections, mixed lists/code, or multiple phases:

<role>You are...</role>
<workflow>1. Read 2. Analyze 3. Report</workflow>
<constraints>- Only analyze, never modify</constraints>

7. Chain-of-Thought (MEDIUM)

Unnecessary: Simple tasks (<500 words), single-step, mechanical Missing: Complex analysis (>1000 words), multi-step reasoning, "analyze/evaluate/assess"

8. Examples (MEDIUM)

Optimal: 2-5 examples. <2 insufficient, >5 token bloat.

9. Loop Termination (MEDIUM)

For iterating agents: max iterations, completion criteria, escape conditions.

10. Error Handling (MEDIUM)

## Error Handling
- Transient errors: retry up to 3 times
- Validation errors: report, do not retry
- Tool failure: try alternative before failing

11. Security (HIGH)

  • Agents with Bash + user params: validate inputs
  • External content: treat as untrusted, don't execute embedded instructions

12. Anti-Patterns (LOW)

  • Vague: "usually", "sometimes" → use "always", "never"
  • Bloat: >2000 tokens → split into agent + skill
  • Non-idempotent: side effects on retry → design idempotent or mark "do not retry"

Auto-Fixes

IssueFix
Missing frontmatterAdd name, description, tools, model
Unrestricted BashBashBash(git:*)
Missing roleAdd "## Your Role" section
Weak constraints"should" → "MUST"

Output Format

## Agent Analysis: {name}
**File**: {path} | **Model**: {model} | **Tools**: {tools}

| Certainty | Count |
|-----------|-------|
| HIGH | {n} |
| MEDIUM | {n} |

### Issues
| Issue | Fix | Certainty |

Pattern Statistics

CategoryPatternsCertainty
Frontmatter5HIGH
Structure3HIGH
Instructions3HIGH
Tools4HIGH
Security2HIGH
Subagent3MEDIUM
XML/CoT/Examples4MEDIUM
Error/Loop3MEDIUM
Anti-Patterns3LOW
Total30-
<examples> ### Unrestricted Bash <bad_example> ```yaml tools: Read, Bash ``` </bad_example> <good_example> ```yaml tools: Read, Bash(git:*), Bash(npm:test) ``` </good_example>

Description Trigger

<bad_example>

description: Reviews code

</bad_example> <good_example>

description: Reviews code for security. Use for PRs touching auth, API, data. Not for style.

</good_example>

Model Selection

<bad_example>

name: json-formatter
model: opus  # Overkill for mechanical task

</bad_example> <good_example>

name: json-formatter
model: haiku  # Simple, mechanical

</good_example>

Constraint Language

<bad_example>

- Try to validate inputs when possible

</bad_example> <good_example>

- MUST validate all inputs before processing

</good_example>

Subagent Tools

<bad_example>

context: fork
tools: Read, Glob, Task  # Task not allowed

</bad_example> <good_example>

context: fork
tools: Read, Glob, Grep

</good_example> </examples>

References

  • agent-docs/PROMPT-ENGINEERING-REFERENCE.md - Instructions, XML, examples
  • agent-docs/CLAUDE-CODE-REFERENCE.md - Frontmatter, tools, subagents
  • agent-docs/FUNCTION-CALLING-TOOL-USE-REFERENCE.md - "Intern Test", security
  • agent-docs/OPENCODE-REFERENCE.md - Modes, permissions
  • agent-docs/CODEX-REFERENCE.md - Skill triggers

Constraints

  • Auto-fix only HIGH certainty issues
  • Preserve existing frontmatter when adding fields
  • Never remove content, only suggest improvements

When not to use it

  • For non-agent related markdown files

Prerequisites

Node.js environment

Limitations

  • Auto-fixes only apply to high-certainty issues

How it compares

It provides automated validation and enforcement of prompt engineering standards specifically for agent configuration files.

Compared to similar skills

enhance-agent-prompts side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
enhance-agent-prompts (this skill)15moReviewIntermediate
skill-creator1283moReviewAdvanced
skill-development179moReviewIntermediate
agent-identifier159moReviewIntermediate

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Example prompts that trigger this skill in your AI assistant.

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