deslop
Skill5 starsChanged 15 days agoMITView on GitHub
Edit a text in editorial rounds so it says what it means. Cuts filler, restatements and benefit tails, and asks for the facts a reader is missing. Each round is scored 0-100. Use when asked to deslop, tighten, edit or review a draft, doc, README, PR description or email.
118 other projects use a version of this.
Adopted by
Most recently taken up by
- lalulali/vespyrtheir own version, first seen Nov 8, 2026
- ferologics/pi-skillstheir own version, first seen Nov 8, 2026
- novuhq/novutheir own version, first seen Nov 8, 2026
- openclaw/openclaw-enterprisetheir own version, first seen Nov 8, 2026
- ADWilkinson/astacktheir own version, first seen Nov 8, 2026
- MammadovEshgin/clean-code-skilltheir own version, first seen Nov 8, 2026
Used with
Projects with it also use simple-issue-description, control-cli and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
JwuthriSkillsimple-issue-description
Turn a rough bug report, feature request, support note, or pull request into a short, plain-language issue focused on the problem and desired behavior. Use when a contributor asks to simplify an issue, explain what a PR is for, create the corresponding issue for a PR, remove implementation detail from a report, or invokes /simple-issue-description.
Also in 4 projects that use this
ElyzeSolutionsSkillcontrol-cli
Build or adapt a local harness to drive, inspect, and profile an interactive CLI or TUI without external services. Use for CLI UX checks, startup regressions, memory leaks, hangs, prompt flows, or terminal demos.
Also in 6 projects that use this
JwuthriSkillopenseo-review-web-content
Write and review content for the OpenSEO website (web/) — blog posts, guides, feature pages, FAQs. Distills the philosophy for on-brand, useful, accurate content. Use whenever adding or editing user-facing prose in web/content or web/src.
Also in 4 projects that use this
learnerLjSkillverify-this
Verify a claim with fresh local evidence: restate it falsifiably, capture baseline and treatment, compare artifacts, and return VERIFIED, NOT VERIFIED, or INCONCLUSIVE.
Also in 6 projects that use this
ElyzeSolutionsSkillcontrol-ui
Build or adapt a local browser/CDP harness to drive and inspect a web, IDE, or Electron UI. Use for local UI verification, screenshots, accessibility snapshots, perf profiles, visual diffs, or reproducing UI bugs.
Also in 7 projects that use this
ten9876Skillpapercuts
Read-only AetherSDR issue triage that surfaces the UX papercuts, bugs, and regressions you can fix AND prove today with the agent automation bridge. Use when the user says $papercuts or /papercuts, or asks to "find papercuts", "what can I fix and prove today", "triage bridge-provable issues", "what UX bugs can the bridge close", "sort issues by priority I can knock out", or otherwise wants a curated, lifecycle-aware (design→code→prove) shortlist of issues — NOT the label-and-respond /triage workflow. This is the discovery step that feeds /fb. Strictly read-only: it never labels, comments, closes, or edits issues.
Also in 4 projects that use this
- +5 more from Jwuthri
Other versions118 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 118
- molt-bot/clawdbot★ 391ksame name
- novuhq/novu★ 40ksame name
- every-app/open-seo★ 27ksame name
- millionco/react-doctor★ 15ksame name
- jaredpalmer/kev★ 9.8ksame name
- joe-bell/cva★ 6.9ksame name
- sanity-io/sanity★ 6.4ksame name
- millionco/expect★ 3.6ksame name
- rohitg00/pro-workflow★ 2.9ksame name
- compozy/compozy★ 2.9ksame name
108 more not listed
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 repository3 other files it gives its agents.
- ai-detectionSkill
- editorialSkill
- humanizeSkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 116 edited versions we read keep these.
3
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 41
Use facts from your conversation.
- Distinctive: line 45
Stop when the score reaches the target score, after 5 rounds, or when the score rose less than 5 points over the last two rounds.
- Distinctive: line 50
Only if you can't spawn a subagent: the hosted p3n API runs the same editor.
“Common” is measured: kept by at least 6 in 10 of the 116 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
Deslop
Inputs
- Text: a file, or text the user provided.
- Brief: who reads the text and what for. If you don't know the brief and the audience from the writing's context, ask the user.
- Target score: the score that ends the edit. Default 80/100.
They come as the skill's arguments (/deslop draft.md "the support team, learning the escalation rules" 90) or from the conversation.
You are the writer. Spawn a subagent called editor on the cheapest model you have (e.g., Luna for ChatGPT, Haiku for Claude), ideally at low effort, and tell it to read editor.md in this folder as its instructions. Don't read editor.md yourself (context pollution): it is the editor's rubric, and everything you need from it is here in this file.
Label the text with python3 scripts/split.py TEXT_FILE or pipe the text in with python3 scripts/split.py -, and send it to the editor with the brief:
# The text to edit
BRIEF (who reads this and what for): <the brief>
<the labelled text>The editor answers in rounds with one JSON object:
{"summary": "the state of the text and the most important thing to fix next",
"progress": "after round 1: what the revision fixed, what is still open, what it broke",
"items": [{"label": "P3S2" | "P3S2-S4" | "P3", "type": "change" | "cut" | "question" | "note",
"proposal": "the replacement text (change)", "question": "what it needs to know (question)",
"why": "the criterion, and what is wrong"}],
"score": 0-100}A change replaces the labelled sentence, range or paragraph with its proposal; a cut deletes it; a question needs an answer before the sentence can be fixed; a note is anything else. P3S2 is sentence 2 of paragraph 3; H and B lines (headings, lists, tables, code) are generally not edited.
Use facts from your conversation; ask the user for facts you don't have rather than inventing them. When the user has no answer, keep the sentence as is.
Each round, the editor returns feedback per label and a score. Apply the feedback as you see fit, label the new text again, and send it back to the same subagent with the answers to its questions. Ask it to say in "progress" what the revision fixed, what is still open and what it broke, and to hold to what it asked for in earlier rounds. Keep the subagent alive for the whole edit.
Stop when the score reaches the target score, after 5 rounds, or when the score rose less than 5 points over the last two rounds. The user may ask to continue.
Show the rounds, score of each round, the summary, etc. to the user.
Hosted API
Only if you can't spawn a subagent: the hosted p3n API runs the same editor. Read https://p3n.si/skills/deslop#for-ai-agents then, and follow it; it has the calls, the key and the free limit.
The user's p3n API key should live in ~/.config/p3n/key.
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.

