writing-review
Skill0 starsChanged 27 days agoMITView on GitHub
Review a draft and report findings without rewriting it. Use when Shane says: "review this", "critique this draft", "what's wrong with this piece", "give me feedback on this", "is this any good", "review my post", "poke holes in this", "/writing-review". Distinct from humanize (which edits the prose) and ms-style-pass (which applies house style) — this one diagnoses, ranks the findings, and stops. Does not write to or modify any file.
5 other projects use a version of this.
Adopted by
Most recently taken up by
- gwpicard/ai-loop-kittheir own version, first seen Nov 1, 2026
- michaelwjohnson/claude-skillstheir own version, first seen Nov 1, 2026
- ragnos-labs/skill-indextheir own version, first seen Aug 23, 2026
- markrstevenson/skillstheir own version, first seen Aug 10, 2026
- darrenCWJ/agent-skills-scaffoldtheir own version, first seen Aug 9, 2026
Other versions5 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 5
- gwpicard/ai-loop-kit★ 1same name
- darrenCWJ/agent-skills-scaffold★ 0same name
- markrstevenson/skills★ 0same name
- michaelwjohnson/claude-skills★ 0same name
- ragnos-labs/skill-index★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository5 other files it gives its agents.
- humanizeSkill
- ms-style-passSkill
- plain-languageSkill
- ste100Skill
- writing-interviewSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 4 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 5 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 19
Use exactly these four, and no others:
- Distinctive: line 67
Before proposing any replacement, check it for the same formula, inflated claim, or invented detail you just flagged.
- Distinctive: line 77
Specificity test: Remove the specific. Does the argument weaken?
- Distinctive: line 109
If the prose already performs its job, say so plainly and stop.
“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Writing Review
One job: tell Shane what is wrong with a piece, biggest problem first, without changing a word of it.
The rule that makes this skill work
Never produce a replacement draft. The moment you write a competing version, the review stops being a diagnosis and becomes a negotiation about your prose. Shane invokes this when he wants to decide, not to be handed a rewrite. If he wants the edit, he will run humanize.
Also: never edit the file, never save a new file, never stage anything. The review is reported in chat and nowhere else.
The verdict vocabulary
Use exactly these four, and no others:
| Verdict | Meaning |
keep | A pattern is present but earned, or the medium requires it. State what earns it. |
revise | The draft already contains enough material for an honest improvement. |
ask-author | The fix needs a fact, mechanism, example, or experience only Shane has. Ask for exactly that. |
cut | The passage only repeats, performs, or reaches for a close. |
ask-author is what earns this skill its keep. It is the alternative to inventing the missing detail, which is the single easiest way to damage a draft while believing you improved it. A review with four ask-author findings is worth more than one with four clever rewrites.
Order of work
Diagnose in this order. Do not jump to sentences before the earlier layers are settled: a sentence-level finding on a piece with a substance problem is noise.
- Truth and scope — claims, numbers, attribution, uncertainty, conditions, links.
- Substance — the actual point, and the material only Shane could supply.
- Development — does each paragraph depend on the one before it?
- Sentences — surface patterning.
- Craft — did the piece lose warmth, stance, or a landing?
Piece-level diagnosis
Open with this. Use the fields that carry information and omit the rest.
Job: what kind of piece this is, who it's for, what should change for them
Substance: what it specifically contributes, or what's missing
Trust: factual support, attribution, uncertainty, and any preservation risk
Development: how it moves, and where it stalls, repeats, or turns into a list
Voice: what reads as Shane's, and where generic register takes over
Ending: whether it stops on the last useful thought or reaches for a close
Top fixes: the two or three changes with the largest expected gain, rankedPassage-level findings
One block per material finding, ordered by Top fixes rather than by position in the draft.
Passage: the shortest quote that locates the issue
Verdict: keep / revise / ask-author / cut
Pattern: a short name
Why: what the passage does instead of its job
Suggestion: a supported replacement, a precise question for Shane, or the reason to cut
Safety check: does the suggestion preserve facts, attribution, scope, and voice?Before proposing any replacement, check it for the same formula, inflated claim, or invented detail you just flagged.
Tests to run before naming a finding
Substance test. Could this paragraph appear nearly word for word in someone else's article on the same subject? If yes, it is filler even if it is well made.
Flatten test. State the claim without the cadence. If nothing specific remains, the formula was carrying reasoning that was never done.
Relation test. Restate the implied connection using because, although, once, if, so, or which. If doing so requires inventing a relation, only rhythm was there.
Specificity test. Remove the specific. Does the argument weaken? If not, it was a flex, not evidence.
Triad test. Does each of the three items carry distinct weight? A parallel-grammatical three with identical structure is filler dressed as rhythm.
Do not report these as defects
Profiles/voice.md is authoritative for voice. These are deliberate choices, and a review that flags them is wrong:
- A fragment sequence that lands a build-up (
Three emails sent. One reply. Zero closes.). - The closing punch that restates the thesis in compressed form.
- The confessional or first-person opener.
- Hedges doing honest work, and the absence of a hedge where the claim is settled.
- Functional specificity: proper nouns, versions, file paths, gateway names doing real work.
- Headers carrying the argument, so a header-only read still surfaces the spine.
- One grounded colloquial aside, or none at all.
- A deliberately short sentence landing after a long build.
The governing calibration: change repeated use or unsupported performance, not the device itself.
Hard refusals bind the review
Profiles/voice.md's <hard_refusals> are absolute, so a violation is a finding no matter how well it reads:
- em-dashes anywhere, in any form
- "simply", "just", "obviously", "actually"
- em-dash lists, single-noun colon-reveals, semicolons between independent clauses
- highlight-reel structure, emoji-prefixed bullet headers
- top-ten lists, meme formats, regurgitated AI-session pastes
- invented specifics, war stories, or receipts
Reporting a clean piece
If the prose already performs its job, say so plainly and stop. Do not manufacture findings to look useful. "This is ready" is a valid review outcome and often the correct one.
Handoff
Close by collecting every open ask-author item into one list of questions. That list is the input to the next pass — without it, humanize has nothing to work with but the prose itself.
This skill is the agent-side input to Gate 4 (copy: true, in-voice, nothing fabricated). It produces the findings; the human makes the call.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

