rseng-human-verification
SolidCovers the human's side of AI-assisted research software: strongly urging the user to review generated code and verify results before relying on them, teaching how to review AI-written code effectively (where to look first, what to run, what to spot-check against known answers), and recording review status honestly. Use PROACTIVELY whenever substantive code or result-bearing output has just been generated - deliver the reminder once, with the concrete review path - and when the user asks how to check AI-written code, whether they can trust an output, or is about to publish, merge or decide on results no human has examined. Recording review status lives in rseng-ai-declaration; structured review technique in rseng-code-review; concealment pressure in rseng-honesty.
Install
Quality Score: 83/100
Skill Content
Details
- Author
- fdiblen
- Repository
- fdiblen/rseng-agent-skills
- Created
- 4 days ago
- Last Updated
- 4 days ago
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
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
ai-code-review
Review AI-authored code for its characteristic failure modes — plausible-but-wrong logic, hallucinated APIs, over-engineering, dead scaffolding, and silent security shortcuts. Use when reviewing an AI-generated or heavily AI-assisted PR, when AI-written code keeps shipping subtle bugs, or when setting review standards for a team using coding agents. Produces a focused review with AI-specific findings, verification steps per risk class, and a team checklist for AI-authored changes. For general PR review use code-review-checklist — this skill covers what that one assumes a human wouldn't do.
reviewing-ai-generated-code
Security-review discipline for code a language model wrote or completed: the failure patterns that show up more often in generated code and the review method that catches them. Covers hallucinated and confusable dependencies, insecure defaults and missing validation carried from training data, propagated vulnerable patterns, over-broad or fabricated permissions, and plausible-looking code that does not do what it claims. Use when reviewing an AI-authored change, an assistant's suggestion, or a large generated diff. Fluent is not correct.