ahtishamshahzad/agent_dev_flow/ai-output-review
- community
Checking that the SKILL.md file is still in the repository.
Use to critically review AI-generated output (plans, code, docs, decisions) for the failure modes AI agents are prone to — unsupported assumptions, invented facts, conflicting architecture, unnecessary dependencies, security risks, missing tests, over-engineering, scope expansion, outdated patterns, incomplete validation, and false claims of completion.
Install
npx vskill@latest install ahtishamshahzad/agent_dev_flow/ai-output-reviewSKILL.md
AI Output Review
Purpose
Act as a skeptical reviewer of AI-generated output before it is trusted or shipped. Catch the specific failure modes AI agents produce, and separate what is verified from what is asserted. Complements code-review, security-review, and final-quality-audit.
When to Use
- After any AI agent produces a plan, code change, document, or decision.
- Before acting on AI output that affects architecture, security, or scope.
- As an independent-review step in multi-agent runs (
../../system/MULTI_AGENT_RULES.md).
Inputs
- The AI-generated output under review.
- The original request, requirements, and approved plan/architecture.
Discovery Questions
- What was actually requested vs what the output delivered?
- Which claims are backed by evidence vs asserted?
- Does the output contradict the approved architecture or prior decisions?
Responsibilities
Evaluate the output for each failure mode:
- Unsupported assumptions — claims presented as fact without basis.
- Invented facts — fabricated APIs, files, paths, results, or citations.
- Conflicting architecture — contradicts the approved design or itself.
- Unnecessary dependencies — libraries added without a justified need.
- Security risks — introduced or ignored (hand depth to
security-review). - Missing tests — changes without corresponding verification.
- Over-engineering — complexity beyond the requirement.
- Scope expansion — work beyond what was approved.
- Outdated patterns — deprecated/legacy approaches where current ones exist.
- Incomplete validation — checks claimed but not actually run.
- False claims of completion — "done"/"working" without evidence.
Report each hit with location, why it's a problem, and the correction.
Required Workflow
- Read the request/plan and the AI output side by side.
- Walk the 11 failure modes.
- For each finding: cite location, classify the failure mode, state the fix.
- Separate verified from asserted claims.
- Issue a verdict: accept / revise / reject, with blockers.
Decision Rules
- Treat any "done/working/verified" without evidence as a false-completion finding until proven.
- Fabricated file/API/result → reject that portion outright.
- Architecture conflict or scope expansion → block until reconciled with the approved plan.
- Route deep security/perf concerns to
security-review/performance-review.
Rules
- Be skeptical by default; assertion is not evidence.
- Cite specifics; no vague "looks off."
- Don't approve output you can't verify — mark it "unverified."
Anti-Patterns
- Trusting confident phrasing as correctness.
- Passing output with fabricated facts or unrun "validation."
- Missing silent scope expansion because the result "looks good."
- Reviewing only style while ignoring invented facts.
Validation Checklist
- [ ] All 11 failure modes evaluated.
- [ ] Findings cite location + failure mode + fix.
- [ ] Verified vs asserted separated.
- [ ] Dependency additions justified or flagged.
- [ ] Completion claims backed by evidence or flagged false.
- [ ] Verdict (accept/revise/reject) with blockers.
Definition of Done
A review report covering all 11 failure modes with located findings and fixes, a clean separation of verified vs asserted, and an accept/revise/reject verdict — no fabricated or unvalidated output passed as done.
Related Skills
code-review, security-review, performance-review, final-quality-audit, project-orchestrator, documentation.
Related Knowledge
../../projects/current/ (approved plan/architecture to check against).
Related References
../../checklists/ (review checklists).
Context Loading Guidance
- Requires: the AI output, the original request, and the approved plan/architecture.
- Does not require: the whole repo (unless verifying a specific claim), unrelated references.
- May load:
security-review/performance-reviewfor deep concerns; the specific file to verify an invented-fact claim. - Stop when: the verdict and findings are delivered.
Token Efficiency Guidance
Compare output against the recorded plan, not the entire history. Verify suspicious claims by checking the specific file/command rather than reloading everything.
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryChecking.ai/skills/ai-output-review/SKILL.md
Popularity
- 7-day trend score
- 0
Not refreshed yet.
Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
- Claude Code
- Cursor
- GitHub Copilot
- Windsurf
- Codex
- Gemini CLI
- Cline
- Amp
- Roo Code
- Goose
- Continue
- Kilo Code
- Junie
- Trae
- OpenHands
- Qwen Code
- AI Agent
- Tabnine Chat
- Sourcegraph Cody
- Amazon Q
- Firebase Genkit
- Sweep
- Devin
- Phind
- Mentat
- Claude Desktop
- Aider
- GPT Pilot
- Plandex
- bolt.new
- v0
- Replit Agent
- Anse
- TypingMind
- BetterChatGPT
- LibreChat
- Warp AI
- Pieces
- Fig AI
Embed badge
[](https://verified-skill.com/skills/ahtishamshahzad/agent_dev_flow/ai-output-review)