ai-output-verifier
FeaturedCheck AI output before you trust or use it — where it's likely wrong, what to verify, and how to catch confident-sounding errors. Use when asked can I trust this AI answer, how do I verify what AI told me, fact-check this AI output, or is this AI response reliable. Produces a risk read on the specific output (the claims most likely to be wrong or made up), the parts that need independent verification vs the parts that are low-risk, how to actually verify each, the tells of AI hallucination and overconfidence, and a habit for building verification into your AI use — because AI is confidently wrong often enough that unchecked trust is a real risk.
Install
Quality Score: 96/100
Skill Content
Details
- Author
- mohitagw15856
- Repository
- mohitagw15856/pm-claude-skills
- Created
- 8 months ago
- Last Updated
- today
- Language
- HTML
- License
- MIT
Integrates with
Bundled in these plugins
Similar Skills
Semantically similar based on skill content — not just same category
reality-check
Use whenever someone hands you an AI-generated technical plan, recommendation set, setup guide, or tool/config list and says "validate this", "fact-check this", "is this real", "is this accurate", "did it hallucinate", "sanity-check this", "pressure-test this", "is this overkill", or asks whether a plan is feasible and worth doing. Trigger hardest when the content reads as machine-written and is dense with checkable specifics that could be fabricated — repo URLs, CLI flags, file paths, versions, env vars, named "best-practice" patterns, time estimates. The job: pressure-test the thing for hallucinations, factual errors, and unnecessary complexity, then verify every surviving claim against live sources before the user acts on it. Do NOT trigger for a bare dependency question — whether a specific package is real, alive, and maintained is leftpad's registry rung, so "should we add this package" or "is this crate abandoned" goes there. This VERIFIES an existing plan's accuracy and practical value, not choosing be
ai-check
Use when someone asks "does this sound AI?", "check if this is AI-written", "what gives this away as AI", "run ai-check on this", or "score this text". Also use when reviewing a draft for AI tells before publishing, or when a piece of text reads as suspiciously polished, generic, or pattern-y and the user wants a forensic breakdown of why.
ai-code-reviewer
MUST USE when reviewing AI-generated code (Claude/ChatGPT/Copilot output), AI 写的代码/生成的代码能上线吗, or when a change was produced fast and unverified. Targets the characteristic failure modes of AI-generated code: plausible-but-wrong, hallucinated APIs, silent behavior drift, security theater, and over-engineering. Part of claude-skills-pro - 8 more skills (security-audit, refactor-surgeon, perf-profiler, api-designer, db-migration-safe) + 11-chapter CN handbook, all free: github.com/Hahaknight/claude-skills-pro