writing-skills

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SUMMARY

Claude Code skills for rewriting AI-drafted prose to pass AI detectors: a measured three-step pipeline (structural rewrite, tell removal, cross-model diction) scored against Pangram, plus reference management and citation auditing.

README.md

writing-skills

Claude Code skills that rewrite AI-drafted prose until it reads as human, measured against the Pangram detector, with reference management and citation auditing alongside.

An AI-generated draft reveals itself in three ways — rhetorical scaffolding, semantic tells, and the drafting model's lexical fingerprint — and fixing one leaves the other two untouched. The pipeline attacks all three in sequence — a structural pass reshapes the prose away from its source, a semantic pass erases the tells, and a cross-model diction pass strips the model's imprint — with a detector score recorded before and after each step. Verified on a published article: 100% AI to mixed, mean window score 0.993 to 0.576.

flowchart LR
    S[structure: match-outline, caller-run] --> A[humanize chain]
    subgraph A[humanize chain]
        C[filter-tells] --> D[seeded match-voice]
        D --> T[tighten-style]
        T --> X[accent-dial, optional]
        X --> V[inject-vernacular, terminal]
    end
    A --> R[review: reverse-outline, critic-panel, voice-critic]
    R -->|author picks; cycle decision| S

Scope and Status

The repository hosts 19 skills and 3 commands, canonical under .claude/. They fall into four categories (GH-208).

The humanize chain — humanize orchestrates one generative pass: filter-tells (semantic cleanup), match-voice (seeded cross-model diction rewrite, plus the optional burstiness pass), tighten-style (word recovery toward the author's density floor), accent-dial (optional L2-accent stage), and inject-vernacular (the deterministic terminal stage). match-structure is the shared library underneath — metrics, anchor retrieval, venue profiles.

Structure, caller-run — match-outline rewrites a whole document against a blueprint. It is invoked by a workflow before the chain, never by the chain: humanize's input contract assumes its work is done.

Review instruments, caller-run — after the chain's terminal stage: reverse-outline labels the argument as RST markers and ranks every paragraph by what deletion costs, critic-panel reads a finished draft through named persona critics in parallel and merges them into one convergence-first sheet, critic-apply applies that sheet by rule through the rewrite transport, cold-review runs the fresh-context entailment check whose only repairs are verbatim reverts, and voice-critic gatekeeps against the author's voice constitution. Applied picks re-enter the chain as a new cycle.

Data and corpus tools — update-references and audit-references keep a CSL-YAML bibliography current and checked against retrieved sources; tune-anchors sweeps anchor queries; bake-off compares models over multiple payloads so the chain's defaults can be pinned; patent-disclosure populates an eleven-section invention-disclosure template; pattern-language extracts Alexandrian pattern languages from repositories. These maintain data, not prose — a different kind from the chain's stages.

The commands — brainstorm-article, write-article, seo-pass — drive an end-to-end article pipeline. History traces back to coding-skills, where these skills lived through August 2026; the coding commands remain there.

Documentation

The pipeline is described in How to Build a Writing Pipeline — the three passes, why fixing one tell class leaves the others, and the detector scores before and after each step.

Two books draft their chapters through it: agentic-coding-book and agentic-applications-book. Chapters run as articles first, so the skills here are what shapes them.

Methodology

The target voice sits in a writing-voice/ directory of exemplar prose — the contract is in .claude/rules/writing-voice.md. Skills gauge a draft's distance from that corpus, pull anchors from it, and gate every rewrite: a candidate must keep citations, numbers, and meaning, or the original remains. The external Pangram check is consent-gated per document; everything else runs locally against an Ollama endpoint.

Repository Structure

.claude/skills/      the 12 skills, one directory each
.claude/commands/    brainstorm-article, write-article, seo-pass
.claude/rules/       writing-voice contract, technical document types
.claude/scripts/     shared plumbing: credentials, Pangram client, prose parsing
scripts/             mirror sync

Environment

Run the test suite with scripts/run-tests.sh (or mage test); mage tag runs the same gate from a clean main and creates the next v0.YYYYMMDD.N release tag, counting revisions over local and remote tags.

pixi manages Python dependencies. pixi.toml and pixi.lock ship in .claude/, and .claude/scripts/ensure-env.sh provisions the locked environment. Credentials (pangram, serpapi, semantic_scholar) resolve through a gitignored .secrets/ directory per the contract in the skills' documentation; no credential is ever committed or printed.

License

MIT. See LICENSE.

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