Verification

Agent Verifier

Purpose

Run comprehensive verification on AI agent code. This orchestrator invokes focused verification skills and consolidates results into a unified report. All analysis happens locally—code never leaves your machine.

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

| Command | Skill | What it checks | |---------|-------|----------------| | "verify agent" | This skill | Full suite (all below) | | "verify agent security" | verify-security | Secrets, dependencies, input validation | | "verify agent patterns" | verify-patterns | Loops, retries, tools, context size | | "verify agent quality" | verify-quality | Naming, organization, documentation | | "verify agent language" | verify-language | Type 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

1. 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

1. 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:

``bash mkdir -p reports/verification ``

1. 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

1. 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: All code analysis happens locally. Nothing is sent to external services.
• 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.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Aurite-ai
• Source: Aurite-ai/agent-verifier
• License: MIT
• Homepage: https://aurite.ai

Install and usage instructions live in the source repository linked above.