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
- neuraforge-cl-es/adaptive-engineeringtheir own version, first seen Nov 8, 2026
- facebook/docusaurustheir own version, first seen Nov 8, 2026
- maideps/ai-harness-frameworktheir own version, first seen Nov 8, 2026
- Lanqiao-Luca/ai-java-workflowtheir own version, first seen Nov 8, 2026
- Beskars-Code/Skillstheir own version, first seen Nov 6, 2026
- Gabriel-Lafrance/Skillstheir own version, first seen Nov 6, 2026
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-burySkillevidence-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-burySkillexperiment-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
Other versions47 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 47
- facebook/docusaurus★ 67ksame name
- open-metadata/OpenMetadata★ 16ksame name
- openai/plugins★ 7.8ksame name
- hi-godot/godot-ai★ 3.4ksame name
- Norman-bury/research-writing-skill★ 3.4ksame name
- Norman-bury/articlewriting-skill★ 3.4ksame name
- forcedotcom/salesforcedx-vscode★ 1ksame name
- vercel/vercel-plugin★ 328same name
- s3s-project/s3s★ 315same name
- project-numina/numina-lean-agent★ 279same name
37 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository4 other files it gives its agents.
- verify-languageSkill
- verify-patternsSkill
- verify-qualitySkill
- verify-securitySkill
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
- Distinctive: line 11
Run comprehensive verification on AI agent code.
- Very specific: line 40
Check for pyproject.toml, package.json, go.mod
- Very specific: line 41
Look at file extensions in src/ or project root
- Very specific: line 51
Check if .kahuna/ directory exists
- Very specific: line 52
If yes, read .kahuna/context-guide.md for organizational rules
- Distinctive: line 228
After presenting the report, ask the user:
- Distinctive: line 234
Create the reports directory if it doesn't exist:
- Distinctive: line 245
IMPORTANT: Use the real current time, not zeros or placeholders.
- Very specific: line 247
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
“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.
Files
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
| 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:
- Primary language:
- Check for
pyproject.toml,package.json,go.mod - Look at file extensions in
src/or project root
- Check for
- Agent framework (if any):
langgraphin imports → LangGraphcrewaiin imports → CrewAIautogenin imports → AutoGenlangchainin imports → LangChain- Direct SDK usage → Custom agent
- Kahuna integration:
- Check if
.kahuna/directory exists - If yes, read
.kahuna/context-guide.mdfor organizational rules
- Check if
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
anytypes - 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:
- Create the reports directory if it doesn't exist:
mkdir -p reports/verification 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.,08-15-42for 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- 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.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
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