agentleFS
EveryIncEveryInc/every-marketplace/skills/ce-noslop/SKILL.md

ce-noslop

Skill26k starsChanged 3 months agoMITView on GitHub

Rewrite, check, or draft prose so it carries no AI writing tells, reads plainly on the first read, and keeps every source fact. Use when asked to make writing plainer or free of those tells, to check writing for them, or when drafting from supplied content. Use ce-promote for channel-specific marketing copy.

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Keep exact identifiers, paths, commands, and thresholds.

    line 45

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Write without slop

Prose that carries no AI tells and that a reader understands on the first read, with every fact the source stated still there. Both goals hold at once: text that is free of tells but still dense has failed, and text that is plain but changes how certain a claim is has failed.

Done: the mode's output is returned, every fact, number, name, quote, and citation in the input survives, and nothing was added that the source or the caller did not supply.

Boundaries: never touch code blocks, quoted text, frontmatter, link targets, identifiers, or a token the caller's own contract requires, unless the user names that content as the thing to fix. Never say whether text was written by a model. Write a named file in place only when the request asks for that; otherwise return the text.

Mode

Take a mode: token when one is given. Otherwise: no draft means author; an imperative on a draft means edit; a question about a draft means detect.

  • author. Hold the tests below while the caller writes; return nothing. When handed content and asked to write, draft it under the same tests.
  • edit. Rewrite only the sentences a test fails on, and return the text. A sentence that passes stays as written, so a second pass on the returned text changes nothing. Say what changed in one line only when the caller asks for it, and keep that line outside the rewritten text and out of any artifact.
  • detect. Name each pattern found, quote the line, give the fix in a few words. Do not rewrite.

For edit and detect, and for an author passage the tests alone do not settle, read references/patterns.md. On text that is not English, apply the tests only. Note that the pattern catalog did not apply inside detect findings or inside a change line the caller asked for, and nowhere else.

Register

Pick by who reads the result. The caller's own interaction contract wins over any line here.

  • Agent talking to the user. The reader is a teammate who knows the domain and did not watch the work. Write each sentence as you would say it to them.
  • Repo or team artifact. Neutral. Match the surrounding document's idiom. No first person, no opinion the artifact does not need. This is the default when no reader is named.
  • The user's own writing. Preserve voice; make the minimum effective edit. Understandability edits stop at sentence splits and actor restoration that keep the user's word choice.

The tests

Apply these to every sentence, in author mode as constraints and in edit or detect mode as checks.

  1. Mechanism. Does the sentence say what the thing does, or how it feels? Replace the feeling with the fact it displaced, or cut the sentence.
  2. Portability. Could the sentence move to another project unchanged? Then it carries no fact about this one.
  3. Actor. Who does the verb? Name them when the source says who. Keep the passive when the actor is unknown or naming it adds nothing.
  4. One idea. Would the reader have to reread to hold the sentence? Split it. A sentence the reader gets on the first pass stays, however long.
  5. Density. One device proves nothing. Three or more distinct patterns in a passage, or one repeated across passages, is a finding.
  6. Decision first. Does the first sentence carry the outcome the reader needs?
  7. Reader. Can someone without the document or the code open act on this? Gloss the identifier or name the consequence.

Keep exact identifiers, paths, commands, and thresholds. For wording choices, read references/terminology.md.

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Trending

Steady: 0 new projects took it in the last 4 weeks, none the 4 weeks before.thin data

Week of Aug 30: 0 new projectsWeek of Sep 6: 0 new projectsWeek of Sep 13: 0 new projectsWeek of Sep 20: 0 new projectsWeek of Sep 27: 0 new projectsWeek of Oct 4: 0 new projectsWeek of Oct 11: 0 new projectsWeek of Oct 18: 0 new projects
Aug 2026Sep 2026Oct 2026
New projects taking a version of this file each week, over the 8 weeks our latest run read: only 0 in all, so this is a hint, not a trend.

Who's talking about EveryInc/every-marketplace

The biggest 5 of 12 mentions linking to the repository that our crawl found. Each line is their own headline.

See all 12

Talked about on GitHub, YouTube and Hacker News (12 times).

On GitHub · 10

5 more on GitHub

On YouTube · 1

On Hacker News · 1

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

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What did you use it for? e.g. Reviewing pull requests in a Rails app

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.