Writing for Humans
SkillDocs & knowledgeWrite copy a human reads: a landing page, a README's front half, a launch post, a profile page. Use when drafting or revising public-facing prose, when a page reads like agent documentation, or when a finished draft needs its last-mile scrub for AI tells.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Writing for Humans skill
What this skill tells your AI
The instructions your AI receives, as published by timharris707/skills in skills/author/writing-for-humans/SKILL.md and read by ahel’s review.
The sibling skill writing-for-agents makes documents predictable enough that an agent runs the same process every time. This skill makes pages worth a stranger's next minute: the reader is free to leave at any sentence, and the page earns each one. The compression that serves an agent reads cold to a human; when the document is a SKILL.md, an AGENTS.md, or a reference an agent consumes, use the sibling instead.
Work the sections in order for a full draft. Jump straight to the scrub when the content already stands and only the tells remain.
Guide structure over catalog structure
A catalog lists what exists. A guide walks the reader somewhere. Human-facing pages take the guide shape, in this order:
- Identity and hook first. One or two sentences before any list: what this is, for whom, and the opinion that animates it.
- The quickest possible start. The smallest real action the reader can take right now, finishable in minutes.
- Problems framed from the reader's seat. Each runs problem → fix → link: the pain as the reader feels it, then the fix, then where to go.
- Explicit ordering. "Start here. Do this first." The reader never infers the sequence.
- Full reference last. The complete listing sits at the bottom, where the convinced reader looks it up, not at the top where it greets the undecided one.
The test at every scroll depth: can the reader say what to do next? A section that leaves them informed but directionless goes lower or gets a pointer forward.
Warmth moves
Warmth is specific moves, each observable in the text:
- First person with real opinions. "I built this because X annoyed me" over "This tool addresses X." An opinion is a claim the writer could lose an argument about.
- Admit limits plainly. "It won't untangle the mud for you" builds more trust than any capability claim. Every piece carries at least one honest limit.
- Permission-giving imperatives. "Hack around with them. Make them your own." The reader is invited to act, not licensed to observe.
- Empathy before feature talk. Open from the reader's chair, then introduce what you built. A feature named before its pain is a spec line, not a sentence.
Failure modes
Check a draft against each by name:
- Agent-register bleed. Human copy in the compressed declarative style of agent docs. The tell is a term of art standing where a reader's word should be; translate it or teach it in the sentence where it first appears.
- Process bleed. The piece narrates the hidden work behind it: chat history shipping as copy. Write from the facts, ordered by the reader's questions, never by the build timeline.
- Clean nothing. Tidy, de-AI'd, and empty. A scrub is not a voice. The test: does the piece contain an opinion, an admitted limit, or a choice a competitor's page wouldn't make?
Standing voice rules
Warmth never buys these back:
- Checkable claims only. Every claim hands the reader a way to verify it: a link, a sourced number, or a behavior they can try. A claim that offers none is absent.
- No stale numbers. A count or date that will rot either lives where the release process updates it, or is written so it cannot rot ("the catalog table below is the current list").
- Facts sacred. Never invent a user, an anecdote, or a metric to sound human. Where a fact is missing, leave a visible placeholder and go get the fact.
- Names only in praise. A person or company is named in your copy only when the mention flatters them.
- Dashes on a budget. The em dash is one of the most recognized AI tells, and the clause-spliced rhythm it builds is the reason. A handful per page at most, each an earned interruption. Fix an overage by restructuring: split the sentence, subordinate with a comma, or cut the aside. Never swap a dash for another mark in place; the swap keeps the AI rhythm and only changes its costume.
- Positioning is canon, read before writing. Read the project's recorded positioning before using any autobiographical claim or number, and reuse its copy of record rather than paraphrasing it. For this catalog that record is decision 0005: the headline "Skills For Real Non-Engineers", the lead-developer framing, and a short list of retired lines that never come back (
scripts/check_positioning.pyfails the build if one does). When this skill and that record disagree, the record wins.
Last-mile scrub
After structure and voice are settled (never before, or you produce clean nothing), run references/last-mile-scrub.md. Start with the guardrails: hunt clusters rather than isolated tells, and let a voice sample outrank any conflicting tell rule (the standing voice rules above are never outranked). Rewrite whole sentences rather than swapping words.
It's working if
Qualities of the finished page, judged by reading it cold:
- A reader who has never seen the project can say what to install (or read, or click) first and what their first session looks like.
- The piece carries at least one first-person opinion and one plainly admitted limit: something a competitor's page would not say.
- The page is scrubbed but not silenced: free of AI tells and still audibly voiced. A page that is only cleaner is clean nothing; put voice back before shipping.
- What the reader gets and does next fills the page; how it got made appears nowhere.
Done when (checkable: verify each line before reporting complete)
- Hook first, quickest start second, reference last; every section leaves a visible next action.
- No insider term appears before the sentence that teaches it: the page teaches its vocabulary or drops it.
- Every claim is checkable or absent, every number has a live source or cannot rot, and nothing was invented to sound human.
- The dash budget was spent deliberately, and no over-budget dash was fixed by an in-place swap.
- The scrub ran last, whole clusters were rewritten, and the voice sample (when one exists) won every conflict with the tell rules.
- Every line of "It's working if" was checked against the final text, not assumed.
Attribution
The guide structure is modeled on the README of Matt Pocock's skills (MIT): hook, thirty-second start, problem → fix framing, and reference last are the shape his README demonstrates; the quoted phrases in Warmth moves ("it won't untangle the mud for you", "Hack around with them. Make them your own.") are his, and the It's working if section follows the outcome-test shape of his skill docs pages. Process bleed is forint573/human-copywrite's term (Apache-2.0). The scrub's guardrails (clusters over isolated tells, voice sample outranks the tell rules, no fabrication) follow blader/humanizer (MIT), whose 33-pattern catalog builds on Wikipedia's "Signs of AI writing"; the dash budget is a softer cousin of that skill's outright em-and-en-dash ban. What this catalog adds: the register split against its sibling writing-for-agents, the agent-register bleed and clean nothing failure modes, the standing voice rules, and the two checkable exit sections.
Signals
- GitHub stars
- 21
- Forks
- 4
- Last commit
- Sep 2026
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writing-for-humans- Source
- github.com/timharris707/skills