ai-writing-detector

AI Writing Detector

Run a detect-only review using the original Avoid AI Writing rules. Never rewrite unless the user changes the request.

Authority

The canonical rulebook is ../avoid-ai-writing/SKILL.md. Its cautions about false positives, context, protected material, and authorship claims apply here.

For cross-Skill work, follow ../avoid-ai-writing-router/references/handoff-contract.md and the typed edges in ../avoid-ai-writing-router/references/skill-graph.json.

Connection contract

Incoming

Accept detector work from:

• avoid-ai-writing-router via ROUTE for detect-only requests, the audit stage of a multi-stage request, or fresh signal collection after another terminal stage returns control to the router.
• preservation-verifier via bounded RECHECK only when convergence or residual auditing was part of the request.

Do not accept a direct handoff from false-positive-reviewer. That Skill is terminal in the graph and must return control to avoid-ai-writing-router when fresh signal collection is needed. This prevents a reviewer-detector cycle.

Carry forward the canonical context_profile separately from the detector's context_mode, along with protected constraints, pass state, and risk flags. Do not collapse or reset them.

Produce

Update the handoff envelope with:

• execution_evidence.detector: executed only if the bundled detector actually ran, otherwise model_only.
• detector_summary.score and label only when produced by executed detector code.
• detector_summary.issue_types from actual findings.
• any consequential_authorship_claim risk flag observed in the user's request.

Outgoing

• FEED findings to voice-preserving-rewriter only when the user also requested returned-text rewriting.
• FEED findings to file-edit-in-place only when the user explicitly requested mutation of a named file.
• ESCALATE to false-positive-reviewer when the user asks what the findings can establish about authorship or another consequential conclusion.
• Otherwise stop after the detect-only result.

Deterministic hits are candidate matches. Keep the engine's public issue types and scores intact, then apply the canonical context exceptions and pass conditions when deciding which hits are justified editorial findings. Neither kind of result is a mandatory edit instruction or authorizes a mutation.

AI-engineering evidence lens