agentleFS
fapariciorfaparicior/sdlc-skills/skills/auditing/agents-maintainer/SKILL.md

agents-maintainer

Skill2 starsChanged 7 days agoMITView on GitHub

Maintain and optimize AGENTS.md files for AI coding agents. LOAD THIS SKILL when user mentions: agents.md, agent guidelines, agent best practices, karpathy principles, think before coding, agent optimization, agent instructions, coding standards for agents, audit agents.md, update agent guidelines, or validate agent rules. Executes audit, update, validate, generate, and compare modes.

The file

We split this skill into the rules it gives an agent

10 rules. About 0 are common, 10 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈10

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Before major project changes

    line 53
  2. Distinctive:

    When agent performance issues arise

    line 54
  3. Distinctive:

    Update specific sections of AGENTS.md.

    line 62
  4. Distinctive:

    Check if AGENTS.md meets quality standards.

    line 76
  5. Distinctive:

    Create new sections or files based on needs.

    line 90
  6. Distinctive:

    Problem: No explanation why rules exist

    line 168
  7. Distinctive:

    Fix: Add rationale: "DDD abstraction reduces migration cost by 85%"

    line 169
  8. Distinctive:

    Fix: Run audit, update or remove outdated sections

    line 173
  9. Distinctive:

    Use tables for quick scanning

    line 178
  10. Distinctive:

    Before ending your turn, verify every item below with concrete evidence (not just a checkmark).

    line 228

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

PROTOCOL: AGENTS-MAINTAINER (EXECUTION LEVEL 3)

<state_machine> CURRENT_STEP -> REQUIRED_TOOL -> REQUIRED_OUTPUT -> MANDATORY_HALT Step 1: Read Target -> read_file(AGENTS.md, templates/agents-sections.md) -> Current structure vs required 10 sections -> Continue to Step 2 Step 2: Execute Mode -> read_file(templates/validation-checklist.md) -> Audit / Update / Validate / Generate / Compare output -> 🛑 HALT TURN (Present result) </state_machine>

<execution_invariants>

  1. WORKFLOW IMMUTABILITY: You may reason freely INSIDE each step to analyze repository conventions and agent failure modes, but you are strictly forbidden from skipping steps (workflow structure = immutable | step reasoning = flexible).
  2. TEMPLATE LOCK: Before auditing, validating, or generating AGENTS.md sections, you MUST call read_file on templates/agents-sections.md and templates/validation-checklist.md (and references/best-practices.md when benchmarking).
  3. SPECIFICITY RULE: Every rule written to AGENTS.md must be concrete, verifiable, and grounded in this repo's real commands and architecture.
  4. ESCAPE HATCH: If the repository's structure does not fit the contract, do not silently improvise and do not force-fit: declare the deviation in one line and ask. </execution_invariants>

<output_contract>

  • TARGET_FILE: AGENTS.md (when in Update or Generate mode) or structured Audit/Validation report
  • SOURCE_TEMPLATES: templates/agents-sections.md and templates/validation-checklist.md (MUST call read_file before producing output)
  • SCHEMA_INVARIANCE: Preserve all 10 required AGENTS.md sections (Commands, Boundaries, Project Structure, Code Style, Testing Guidelines, Definition of Done, Documentation, Architecture Principles, Karpathy Principles, Git Workflow).
  • ESCAPE_HATCH: Never silently omit or invent required sections. If a section genuinely does not apply to the repository, preserve the heading and write "N/A — [1-line rationale]", or halt and ask the user before deviating. </output_contract>

A specialized skill for maintaining, updating, and optimizing the AGENTS.md file to ensure it stays aligned with industry best practices and project needs.

🎯 Purpose

This skill helps you:

  • Review current AGENTS.md against best practices
  • Update sections with new guidelines or changes
  • Validate that rules are clear and actionable
  • Optimize for agent performance and understanding
  • Generate new sections based on project evolution

📋 Skill Capabilities

Audit Capability

Review the current AGENTS.md and identify gaps or improvements.

When to use:

  • Periodic review of agent guidelines
  • Before major project changes
  • When agent performance issues arise

Expected output:

  • Gap analysis against best practices
  • Priority recommendations
  • Specific improvement suggestions

Update Capability

Update specific sections of AGENTS.md.

When to use:

  • New project requirements emerge
  • Industry best practices evolve
  • Lessons learned from agent mistakes
  • Team feedback indicates improvements needed

Expected output:

  • Updated AGENTS.md with changes
  • Summary of what changed
  • Change justification

Validate Capability

Check if AGENTS.md meets quality standards.

When to use:

  • After making changes
  • Before committing changes
  • During code review

Expected output:

  • Compliance score (0-100%)
  • Missing required sections
  • Formatting issues
  • Clarity assessment

Generate Capability

Create new sections or files based on needs.

When to use:

  • Setting up new project
  • Adding new agent instruction files
  • Creating coding standards documentation

Expected output:

  • New content sections
  • Agent-specific instruction files (CLAUDE.md, GEMINI.md, etc.)
  • Integration suggestions

Compare Capability

Compare current AGENTS.md with best practices benchmarks.

When to use:

  • Evaluating current state
  • Planning improvements
  • Benchmarking against industry standards

Expected output:

  • Side-by-side comparison
  • Missing practices
  • Adoption recommendations

📊 Required Sections

A complete AGENTS.md should include:

SectionRequiredPurpose
Commands✅Available scripts and tools
Boundaries✅Always/Ask/Never guidelines
Project Structure✅Directory organization
Code Style✅Language-specific conventions
Testing Guidelines✅Test organization and requirements
Definition of Done✅Completion criteria
Documentation✅Reference locations
Architecture Principles✅Core architectural decisions
Karpathy Principles✅AI agent behavioral guidelines
Git Workflow✅Branching and commit standards

🔧 Best Practices Checklist

Content Quality

  • Rules are specific and actionable
  • Examples provided for complex concepts
  • No contradictory statements
  • Language is clear and unambiguous
  • Covers common edge cases

Structure

  • Logical organization with clear headings
  • Uses tables for quick scanning
  • Includes code examples
  • Proper markdown formatting
  • Cross-references to other docs

Agent Optimization

  • Karpathy principles included
  • Think-before-coding workflow defined
  • Search-first requirement explicit
  • File size limits specified
  • Domain knowledge embedded

Maintenance

  • Last updated date present
  • Version tracking if applicable
  • Change log maintained
  • Regular review schedule

🔍 Common Issues & Fixes

Issue: Vague Rules

Problem: "Write good code" Fix: "Follow TypeScript strict mode, no any types without justification"

Issue: Missing Context

Problem: No explanation why rules exist Fix: Add rationale: "DDD abstraction reduces migration cost by 85%"

Issue: Outdated Information

Problem: References to removed features Fix: Run audit, update or remove outdated sections

Issue: Too Long

Problem: Agents don't read entire file Fix:

  • Use tables for quick scanning
  • Add summary sections
  • Keep examples concise

Issue: Contradictions

Problem: Conflicting rules in different sections Fix:

  • Detect contradictions
  • Consolidate overlapping rules
  • Add cross-references

📈 Metrics to Track

MetricTargetHow to Measure
Agent Error Rate< 10%Track agent mistakes per task
Rework Rate< 15%Count of changes after initial delivery
Clarification Questions< 5 per taskTrack questions asked by agent
Task Completion TimeBaselineMeasure time to complete tasks
Code Quality Score> 90%Linting, type checking, tests

🔄 Integration with Other Skills

SkillIntegration Point
adr-create / adr-amend / adr-validateReference ADRs in architecture sections
testing-workflowAlign testing guidelines
security-reviewIncorporate security constraints
code-qualityEnforce coding standards

📚 Related Resources

📝 Version History

VersionDateChanges
1.0.02026-06-25Initial skill creation

Skill Owner: Technical Team
Last Updated: 2026-06-25


<self_validation_gate> Before ending your turn, verify every item below with concrete evidence (not just a checkmark). If any item cannot be cited with real evidence from this turn, DO NOT produce your final response — fix the violation first:

  • Template Read Evidence: Exact paths passed to read_file (templates/agents-sections.md, templates/validation-checklist.md): <paths>
  • Specificity Evidence: Concrete repo files (package.json, Makefile, ARCHITECTURE.md) read to ground commands and boundaries: <paths>
  • Required Sections Evidence: Confirm all 10 required AGENTS.md sections are present (or list any "N/A — [rationale]" section): <10/10 status> </self_validation_gate>

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Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.