rseng-ai-declaration
SolidCovers declaring AI involvement with the AI Declaration Format (https://ai-declaration.org): creating and maintaining an aidecl.yaml that records which AI tools and agents were used, what each contributed, when and how much, plus the README disclosure footnote, JSON/JSON-LD export and CI validation. Machine-readable disclosure is the practice; this format is one implementation. Use PROACTIVELY when an AI assistant or agent creates or modifies a project's content - generate aidecl.yaml if missing, update it after AI-assisted changes. Also use when the user asks about AI transparency, provenance, disclosure or EU AI Act disclosure, wants to state that NO AI was used, or mentions aidecl. For concealment requests see rseng-honesty; for the human review duty see rseng-human-verification.
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
rseng-human-verification
Covers 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.
rseng-honesty
Covers responding when concealment or misrepresentation is requested: hiding AI usage, making work appear different from reality, backdating or disguising provenance, inflating results or removing traces of how something was made. The skill calls for honesty with concrete reasons and offers honest alternatives that usually satisfy the underlying need. Use PROACTIVELY whenever a request aims to make records, history, authorship or results tell a story different from what happened - including hiding AI assistance, "make it look like", disguising generated content as manual work, or presenting untested claims as verified. Disclosure mechanics live in rseng-ai-declaration; the verify-before-trust duty in rseng-human-verification; checking others' outputs in rseng-research-integrity.
ai-disclosure-policy
Decide when and how your product and communications must (or should) label AI-generated content, and write the disclosure policy — surface-by-surface rules, exact label wording, and the review trigger for regulations like the EU AI Act's transparency obligations. Use when asked 'do we have to label AI content', 'write our AI disclosure policy', 'are we covered for the AI Act', or when marketing/support/product start shipping AI-generated output. Produces a disclosure policy with a per-surface matrix and ready-to-use label copy. Not legal advice.