xmutfyh/dsh-plugin-writing-guard

Less AI. More Evidence. Better Journal Fit.

Writing Guard is a research-paper writing guard for DeepSeek Harness: it reduces mechanical, templated and defensive AI writing, protects research facts and scientific commitments during AI-assisted revision, and calibrates a manuscript's writing distributions against representative target-journal papers.

Language can change. Evidence cannot.

Local · Deterministic · Zero Network · Zero LLM

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Three pillars: STYLE / EVIDENCE / JOURNAL

1. Less AI / STYLE Detect and reduce mechanical, templated, over-defensive AI writing — revision residue, defensive writing, hollow buzzwords and structural tells. We do not hide AI use; we remove bad AI writing.

   Stronger AI models increasingly write “correct but unnecessary” sentences.

2. More Evidence / EVIDENCE Numbers, p-values, citations and DOIs must not silently drift during polishing; null findings must not disappear; correlation must not become causation; scope and evidence status must not be silently changed. Language can change. Evidence cannot.

3. Better Journal Fit / JOURNAL Distill section-level writing distributions, scientific claim patterns and rhetorical moves from representative target-journal papers. It is not only about wording — it compares what each section typically says and in what order.

Quick Start

dsh plugin --profile web add dsh-plugin-writing-guard
dsh web

Published on npm. GitHub / local source installs are also supported — see full install instructions.

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How it works

writing rules → Agent revision → automatic guard → targeted revision

Writing Guard is not a one-shot humanizer. It works continuously inside the DSH paper workflow:

• Load writing_rules before writing
• Check while writing / editing with writing_audit
• Compare before/after revisions to protect Scholarship / Epistemic invariants

STYLE — removing AI flavor

Detects:

• Revision residue: revised, as requested, 本轮, 审稿人要求
• Defensive writing: concession stacking, limitation pre-emption, generic value claim, unnecessary epistemic retreat
• Mechanical rhetoric: not X but Y, rather than overuse, rule of three, em-dash / colon abuse
• LLM-associated words: delve / tapestry / testament / leverage (density-based, a single use is fine)
• Chinese filler chains, average sentence-length anomalies, etc.

Density thresholds are language-aware: English by word count, Chinese by CJK character count, with a double gate to avoid false positives on domain terms.

EVIDENCE — Scholarship + Epistemic Lock

Writing Guard compares before/after AI revision and protects:

• Numbers, percentages, p-values, confidence intervals, units
• \cite / \ref, Figure/Table numbers, DOIs
• Causal and evidential force: associated with must not silently become caused
• Negation / null findings: no significant difference must not disappear or flip
• Scope boundaries and evidence status: “observed / reported” must not become direct claims

Each finding is tagged INVARIANT / VIOLATION / CANDIDATE / ADVISORY and an integrity regression report is produced.

JOURNAL — target-journal calibration

Writing Guard builds a corpus-aware Journal Profile from multiple representative target-journal papers, each parsed independently.

It currently compares five signal groups:

• Structure: sentence length, paragraph length
• Voice: passive voice, first-person usage
• Citations: bibliographic citations, figure/table references
• Scientific claims: claim density, causal/evidential strength, hedging, scope, null findings
• Rhetoric: rhetorical move coverage, canonical order, section-bound transition fit

Journal Fit is reported per section, together with corpus size and confidence.

Scientific Integrity > Journal Fit

Journal Fit uses grouped weights: Structure 20% / Voice 10% / Citations 15% / Epistemics 35% / Rhetoric 20%.

Four DSH Tools

Tool	Purpose
writing_rules	Returns the writing-discipline cheat sheet before writing
writing_audit	Main audit entry: checks STYLE issues, compares Scholarship / Epistemic invariants, and can load Style Profile / Journal Profile
writing_style_profile	Learns an author's style from previous papers and returns JSON for audit
writing_journal_profile	Distills a Journal Profile from target-journal papers and returns JSON for audit

Document-aware auditing

The same sentence can mean different things in different document types:

profile	meaning	e.g. as requested by the reviewer
manuscript	paper body	🔴 revision residue, flagged
rebuttal	point-by-point response	✅ normal, not flagged
cover_letter	submission letter	🔴 residue, flagged
review / notes / unknown	other	conservative handling

writing_audit accepts a profile argument, or auto-detects it from the file path.

Automatic / incremental audit

The plugin listens to tools/post-execute: when the agent writes/edits paper files (.md / .tex / .txt), it automatically audits and injects results into the next model request.

• Audit state is persisted per file; only incremental changes are injected (new / resolved / still present)
• No repeated injection when nothing changed
• Before/after text is captured automatically, so Scholarship Lock + Epistemic Lock run without manually passing original

Full install

# From npm (published — recommended)
dsh plugin --profile web add dsh-plugin-writing-guard

# From GitHub (lib/ is committed — no build needed)
dsh plugin --profile web add github:xmutfyh/dsh-plugin-writing-guard

# Or from the GitHub tarball
dsh plugin --profile web add https://github.com/xmutfyh/dsh-plugin-writing-guard/archive/refs/heads/master.tar.gz

# Or from a local source directory
dsh plugin --profile web add ./path/to/dsh-plugin-writing-guard

# Restart to apply
dsh web

Repository: https://github.com/xmutfyh/dsh-plugin-writing-guard

Why not Humanizer / AI Detector?

	Writing Guard	Humanizer	AI Detector
Rules before writing	✅	❌	❌
Checks while writing	✅	usually ❌	❌
Auto-audits paper edits	✅	❌	❌
Full-text rewrite	❌	✅	❌
Explainable issue location	✅	partial	partial
Local rules (zero network / zero LLM)	✅	usually needs LLM	varies

A humanizer fixes the text after it is written; Writing Guard guards it as you write.

Security & Privacy

• All rules run locally: zero network, zero LLM, zero subprocesses
• The plugin only reads the paper files the agent is currently writing/editing and writes its incremental state under ~/.dsh/plugins/dsh-plugin-writing-guard/
• It does not collect or upload paper content
• See SECURITY.md

Tests

npm test

300+ deterministic TP / TN / boundary / regression tests covering:

• STYLE, Scholarship Lock, Epistemic Lock
• Claim alignment, local citation integrity
• Journal Profile, Journal Fit
• Rhetorical semantics (Chinese / medoid / transition)

CI runs build + tests on every push / PR.

FAQ

Is this a DSH “remove AI flavor” plugin?

You can think of it that way, but Writing Guard is not a traditional humanizer. It detects common AI writing patterns during paper writing and revision instead of rewriting the whole text with another model.

Does it support Chinese papers?

Yes. Rules cover both Chinese and English academic writing patterns, with language-aware density thresholds (CJK characters vs. English words).

Does it support SCI / English academic writing?

Yes. writing_audit checks English manuscripts for revision residue, defensive writing, LLM-overused expressions, and common AI-style sentence patterns.

What is the difference from academic-humanizer?

academic-humanizer focuses on rewriting existing text into a more natural style; Writing Guard focuses on continuous checking and prevention inside the DSH paper workflow. They can be used together.

CHANGELOG

Full changelog and implementation details are in CHANGELOG.md.

License

MIT