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Aurite-aiAurite-ai/agent-verifier/skills/verification/SKILL.md

verification

Skill45 starsChanged 32 days agoMITView on GitHub

Full agent verification suite. Runs security, patterns, quality, and language-specific checks. Use when asked to "verify agent", "verify my agent", "audit agent", or "full verification".

47 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use evidence-driven-writing, experiment-results-planning and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • Norman-burySkill

    evidence-driven-writing

    Use when writing or revising Introduction, Related Work, background, literature synthesis, or any section where references must drive claims

    Also in 3 projects that use this

  • Norman-burySkill

    experiment-results-planning

    Use when designing experiments, result tables, mock planning data, evaluation protocols, or results sections before real data are final

    Also in 3 projects that use this

  • +10 more from Norman-bury

The file

We split this skill into the rules it gives an agent

9 rules. 0 are common, 4 are distinctive, and 5 are very specific to this project.

  • 0

    Common

    Most of the 39 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 5

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Run comprehensive verification on AI agent code.

    line 11
  2. Very specific:

    Check for pyproject.toml, package.json, go.mod

    line 40
  3. Very specific:

    Look at file extensions in src/ or project root

    line 41
  4. Very specific:

    Check if .kahuna/ directory exists

    line 51
  5. Very specific:

    If yes, read .kahuna/context-guide.md for organizational rules

    line 52
  6. Distinctive:

    After presenting the report, ask the user:

    line 228
  7. Distinctive:

    Create the reports directory if it doesn't exist:

    line 234
  8. Distinctive:

    IMPORTANT: Use the real current time, not zeros or placeholders.

    line 245
  9. Very specific:

    Example: If the current time is March 17, 2026 at 1:05:30 AM PST, the filename should be: reports/verification/2026-03-17_01-05-30.md

    line 247

“Common” is measured: kept by at least 6 in 10 of the 39 edited versions of this file we could read. “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

Agent Verifier

Purpose

Run comprehensive verification on AI agent code. This orchestrator invokes focused verification skills and consolidates results into a unified report. No telemetry or network calls of its own; the code is processed by the host coding agent and its model provider.

When to Use

Trigger this skill when the user asks to:

  • "verify agent" (primary invocation)
  • "verify my agent"
  • "audit agent"
  • "full verification"
  • "verify my code" (when agent patterns are detected)
  • "check compliance"

Available Verification Modes

CommandSkillWhat it checks
"verify agent"This skillFull suite (all below)
"verify agent security"verify-securitySecrets, dependencies, input validation
"verify agent patterns"verify-patternsLoops, retries, tools, context size
"verify agent quality"verify-qualityNaming, organization, documentation
"verify agent language"verify-languageType hints, idioms, language best practices

Process

Step 1: Context Discovery

Scan the project to identify:

  1. Primary language:
    • Check for pyproject.toml, package.json, go.mod
    • Look at file extensions in src/ or project root
  2. Agent framework (if any):
    • langgraph in imports → LangGraph
    • crewai in imports → CrewAI
    • autogen in imports → AutoGen
    • langchain in imports → LangChain
    • Direct SDK usage → Custom agent
  3. Kahuna integration:
    • Check if .kahuna/ directory exists
    • If yes, read .kahuna/context-guide.md for organizational rules

Record the detected context for reporting.

Step 2: Run Security Checks

Load the verify-security skill and execute its process.

This checks for:

  • Hardcoded secrets and API keys
  • Dependency version pinning
  • Input validation patterns
  • Error message exposure
  • Secure defaults

Record all findings.

Step 3: Run Pattern Checks

Load the verify-patterns skill and execute its process.

This checks for:

  • Loop safety (termination conditions)
  • Retry limit enforcement
  • Tool registry consistency
  • Context size awareness
  • LangGraph cycle analysis (if applicable)

Record all findings.

Step 4: Run Quality Checks

Load the verify-quality skill and execute its process.

This checks for:

  • Naming conventions
  • Code organization
  • Magic numbers/strings
  • Documentation
  • Error handling patterns

Record all findings.

Step 5: Run Language-Specific Checks

Based on detected language, load the verify-language skill and execute its process.

Python checks:

  • Type hints on public functions
  • Docstrings
  • Requirements pinning
  • Python idioms

TypeScript/JavaScript checks:

  • Strict mode enabled
  • No any types
  • Async/await error handling
  • Promise handling

Go checks:

  • No ignored errors
  • Context propagation
  • Package structure
  • Go idioms

Record all findings.

Step 6: Consolidate Report

Combine all findings from Steps 2-5 into a unified verification report.

Report Format

# Agent Verification Report

**Project:** [project name or path]
**Date:** [current date]
**Mode:** [Kahuna-enhanced | Standalone]
**Language:** [Python | TypeScript | JavaScript | Go]
**Agent framework:** [LangGraph | CrewAI | AutoGen | LangChain | Custom | None]
**Files analyzed:** [count]

## Summary

✅ X checks passed | ⚠️ Y warnings | ❌ Z issues

### By Category
| Category | Pass | Warn | Issue |
|----------|------|------|-------|
| Security | X | X | X |
| Patterns | X | X | X |
| Quality | X | X | X |
| Language | X | X | X |

## Security

*(Summary from verify-security)*

- [x] No hardcoded secrets
- [x] Dependencies pinned
- [ ] ⚠️ [finding]
- [ ] ❌ [finding]

## Agent Patterns

*(Summary from verify-patterns — include only if agent detected)*

### Loop Safety
- [x] All loops have termination conditions
- [ ] ⚠️ Potential unbounded loop at `[file:line]`

### Retry Limits
- [x] All retry mechanisms have explicit limits
- [ ] ❌ Missing retry limit at `[file:line]`

### Tool Consistency
- [x] Tool registry found: X tools defined
- [ ] ❌ Hallucinated tool reference at `[file:line]`
- [ ] ⚠️ Undocumented tool: `[name]`

### Context Size
- [x] System prompt within limits (~X tokens)
- [ ] ⚠️ System prompt exceeds recommended size

## Quality

*(Summary from verify-quality)*

- [x] Naming conventions consistent
- [x] Code well-organized
- [ ] ⚠️ [finding]

## Language ([Python/TypeScript/Go])

*(Summary from verify-language)*

- [x] Type safety enforced
- [ ] ⚠️ [finding]
- [ ] ❌ [finding]

## Detailed Findings

> `[P]` = pattern-matched (structurally reliable) · `[H]` = heuristic (best-effort judgment)

### ✅ Passing
- `[P]` No hardcoded secrets or API keys
- `[P]` All retry decorators have stop conditions
- `[H]` Code organization follows best practices

### ⚠️ Warnings
- `[P|H]` [Check name]: [Description]
  - **Location:** [file:line]
  - **Category:** [Security | Patterns | Quality | Language]
  - **Suggestion:** [How to address]

### ❌ Issues
- `[P|H]` [Check name]: [Description]
  - **Location:** [file:line]
  - **Category:** [Security | Patterns | Quality | Language]
  - **Rule:** [Which rule this violates]
  - **Fix:** [Specific remediation steps]

## Recommendations

1. **[Highest priority]** - [Specific action]
2. **[Second priority]** - [Specific action]
3. [Additional improvements]

---

*Report generated by Agent Verifier v1.0.0*

Step 7: Export Report (Optional)

After presenting the report, ask the user:

Would you like to save this verification report to a file?

If confirmed:

  1. Create the reports directory if it doesn't exist:
    mkdir -p reports/verification
  2. Generate filename using the current date and time (NOT placeholders):

    • Get the actual current timestamp from your environment context
    • Format: reports/verification/{date}_{time}.md
    • Date format: YYYY-MM-DD (e.g., 2026-03-17)
    • Time format: HH-MM-SS (e.g., 08-15-42 for 8:15:42 AM)

    IMPORTANT: Use the real current time, not zeros or placeholders. Check your system context for "Current Time" information.

    Example: If the current time is March 17, 2026 at 1:05:30 AM PST, the filename should be: reports/verification/2026-03-17_01-05-30.md

  3. Save the complete report to that file.

Check Tier Discipline

Throughout all verification steps, maintain tier discipline:

  • [PATTERN] checks — Apply exactly as written. A rule says "flag X" → flag X. No judgment.
  • [HEURISTIC] checks — Apply with judgment. Mark findings clearly with [H].

Tag every finding in the report with [P] or [H] so readers understand confidence level.

Notes

  • Privacy first: This skill adds no telemetry and makes no network calls of its own. Do not tell users their code stays on their machine: it is processed by the host coding agent and its model provider.
  • Kahuna enhances, not requires: The skill works standalone with built-in rules. Kahuna adds organization-specific knowledge.
  • Be specific: Include file names and line numbers when reporting issues.
  • Explain the "why": Help developers understand why each rule matters.
  • Honor existing configs: Respect project's existing lint rules, .editorconfig, etc.

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