AI Writing Audit

Workflow

Open patterns.md, then review prose quality before citation mechanics unless the user specifically asks for citation verification:

1. Audience-model failures: prose that ignores what the reader knows, needs, doubts, or will do next; generic empathy; no real prioritization.
2. Fluff and LLM tells: inflated significance, vague stakes, template transitions, rhetorical balance, generic intros/outros, abstract filler, repeated cadence.
3. Claim quality: vague attribution, unsupported superlatives, stale timing, softened quantifiers, causal overreach.
4. Mechanical residue: leaked tool tokens, placeholders, broken markup, invalid references, wrong target-format syntax.
5. Citation support when relevant: real source, correct metadata, quote/page/number/date/name support, source-chaining mistakes.
6. Rewrite plan: smallest concrete fix, reader-specific framing, concrete verbs/nouns, target-format markup, and any verification still needed.

Output

Lead with findings. For each finding, include:

• Issue
• Evidence (exact snippet or line location)
• Class (P0, P1, P2)
• Why it matters
• Possible non-AI explanation
• Smallest fix
• Confidence (High, Medium, Low, or Needs source access)
• File/line when available

Use classes this way:

• P0: fabricated or wrong source, materially unsupported claim, quote/number/name error, broken markup that changes meaning or publication viability.
• P1: recurring audience-model failure, generic claim scaffold, citation metadata drift, vague attribution, unsupported quantitative/date/causal claim.
• P2: isolated fluff, local style cleanup, minor formatting polish.

Return the top 5-8 findings. Merge repeated symptoms under one root cause. If the user asks for a rewrite, provide a compact replacement after the findings; otherwise give patch-ready guidance, not a full rewrite.

Guardrails

• Do not infer AI authorship from detector scores, a single style cue, perfect grammar, formal tone, multilingual English, or translation artifacts.
• Treat suspicious markers as text-quality defects first. Name provenance risk only when objective residue or source failures justify it.
• Verify citation existence before judging claim support. If sources are unavailable, label the check as unverified and recommend the narrowest follow-up.
• Treat "lack of theory of mind" as an editorial diagnosis: the writing fails to model the reader, situation, objections, or next action. Do not use it as a claim about the writer.
• Do not moralize, shame the writer, or perform detector-score theater.
• Only patch files when the user asks for edits.

Resource

• patterns.md: compact artifact taxonomy, verification checks, and rewrite guidance.