Agent skill

Doc Generator

by athola in athola/claude-night-market

Generates or remediates documentation with human-quality writing.

MITAuto-check passedDevelopment

Install Doc Generator

skills CLI
$ npx skills add athola/claude-night-market --skill doc-generator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install athola/claude-night-market doc-generator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/athola/claude-night-market.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/scribe/skills/doc-generator .claude/skills/doc-generator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
doc-generator
GitHub stars
342
Token cost
~2.3k tokens
SKILL.md length
1,025 words
Files
4
Skills in repo
159
Repo updated
First seen
Licence
MIT

At a glance

Generates or remediates documentation with human-quality writing.

  • Works in 11 steps: Limit Humanizing Constructs → Imperative Mood for Docstrings → Define Scope → …
  • Creating new docs
  • SKILL.md covers When NOT To Use, Core Writing Principles, Required TodoWrite Items and Mode: Generation, plus 5 more sections
  • Calls uv

What it does

Doc Generator is an agent skill from athola/claude-night-market. Generates or remediates documentation with human-quality writing. Use when creating new docs, rewriting AI-generated content, or applying style profiles.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files (for example `modules/generation-guidelines.md`, `modules/quality-gates.md` and `modules/remediation-workflow.md`).

It sits in Development, covering Technical documentation. The repository describes itself as: 23 Claude Code plugins: TDD enforcement hooks, git/PR workflows, spec-driven development, code review, project lifecycle, fix-from-error, maintenance automation, context… The licence is MIT.

When your agent uses it

  • Creating new docs
  • Rewriting AI-generated content
  • Applying style profiles

Example prompts

  • “Use the doc-generator skill to generate or remediates documentation with human-quality writing”
  • “/doc-generator”

Requirements

  • Python 3

Workflow steps

11 steps, taken from the step headings in SKILL.md.

  1. Limit Humanizing Constructs
  2. Imperative Mood for Docstrings
  3. Define Scope
  4. Load Style (if available)
  5. Draft Content
  6. Run Slop Detector
  7. Quality Gate
  8. Analyze Current State
  9. Section-by-Section Approach
  10. Preserve Intent
  11. Re-verify

What it can do on your machine

Read from SKILL.md and the folder at commit 9f3eb00. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Doc Generator loads about 2.3k tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 1,025 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~42
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from athola/claude-night-market at commit 9f3eb00, republished under its MIT licence (© athola). 1,025 words, ~2,265 tokens.

Download SKILL.mdSave it as .claude/skills/doc-generator/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
doc-generator
description
Generates or remediates documentation with human-quality writing. Use when creating new docs, rewriting AI-generated content, or applying style profiles.
globs
**/*.md
alwaysApply
false
category
artifact-generation
tags
documentation, writing, generation, remediation, polish
complexity
medium
model_hint
standard
estimated_tokens
1600
progressive_loading
true
modules
modules/generation-guidelines.md, modules/remediation-workflow.md, modules/quality-gates.md
dependencies
scribe:slop-detector

Documentation Generator

A document costs the sum of its readers' time. Earn that cost or cut.

Generate documents that are grounded in specific claims, lead with their thesis, and earn every sentence. Filler phrases like "In today's fast-paced world" and vague descriptors like "thorough" or "complete" without evidence are bloat. So is any sentence that does not carry, instance, bound, or repeat the document's one takeaway.

This skill enforces both sentence-level cleanliness (no slop vocabulary, em dash overuse, or sycophantic openers) and document-level economy (thesis-first, every sentence earns weight, repetition reserved for the thesis). See Skill(scribe:slop-detector) module document-economy.md for the full rubric.

When NOT To Use

  • Converting an external file into markdown (use leyline:document-conversion and its project-import module)
  • Scanning existing prose for AI patterns (use scribe:slop-detector)

Core Writing Principles

Use active voice and an authorial perspective. Explain the reasoning behind technical choices (why this database, not that one) rather than presenting neutral boilerplate. Use bullets sparingly for short, parallel summaries. Convert multi-line bullet waterfalls into prose so the reasoning survives.

Vocabulary and Style

Avoid business jargon and linguistic tics like mirrored sentence structures or em dash overuse. Use the imperative mood for docstrings ("Validate input", not "Validates"). Do not humanize non-living constructs ("the code wants", "the function speaks to").

Instead ofUse
fallbackdefault, secondary
leverageuse
utilizeuse
facilitatehelp, enable
comprehensivethorough, complete
9. Limit Humanizing Constructs

"Lives under," "speaks to," and similar phrases only make sense for living things.

10. Imperative Mood for Docstrings

"Validate" not "Validates" (per PEP 257, pydocstyle, ruff).

Required TodoWrite Items

  1. doc-generator:scope-defined - Target files and type identified
  2. doc-generator:style-loaded - Style profile applied (if available)
  3. doc-generator:content-drafted - Initial content created
  4. doc-generator:slop-scanned - AI markers checked
  5. doc-generator:quality-verified - Principles checklist passed
  6. doc-generator:user-approved - Final approval received

Mode: Generation

For new documentation:

Step 1: Define Scope
markdown
## Generation Request

**Type**: [README/Guide/API docs/Tutorial]
**Audience tier**: [newcomer | practitioner | expert | persona: <one line>]
**Audience**: [developers/users/admins]
**Audience size**: [1 / small team / org / public]
**Read frequency**: [once / weekly / per-invocation]
**Thesis**: [one sentence the reader must walk away with]
**Length target**: [~X words or sections]
**Style profile**: [profile name or "default"]

The Thesis field is required. If you cannot state the takeaway in one sentence, the scope is not ready. Audience size and read frequency feed the reader-time budget (see scribe:slop-detector module document-economy.md): a skill loaded daily by 50 users has a wildly different budget than a 1:1 design note.

Audience tier is required too, and when the request omits it, ask, do not guess. A guessed reader produces a document that reads as competent and serves nobody. The tier table, the Socratic set for eliciting one, and the creative-writing carve-out are in scribe:slop-detector module audience-targeting.md.

The tier decides what survives the draft:

TierKeepMove to a deep dive
newcomerThe one path that works, end to endInternals, history, alternatives considered
practitionerRepo-specific facts they cannot deriveGeneral-domain teaching
expertThe novel claim and its numbersNothing. Deep dives land here
Step 2: Load Style (if available)

If a style profile exists:

bash
cat .scribe/style-profile.yaml

Apply voice, vocabulary, and structural guidelines.

Step 3: Draft Content

Lead with the thesis. The first paragraph must state the single takeaway. If a reader stops after the lead, they should still leave with the message. Echo the thesis once in the body and once at the close. Cut every other repetition.

Follow the 10 core principles above. For each section:

  1. Start with the essential information (state the thesis or a clear instance of it)
  2. Add context only if it adds value (does it carry, instance, or bound the thesis?)
  3. Use specific examples (one is proof; two is emphasis; three is filler)
  4. Prefer prose over bullets
  5. End when information is complete (no summary padding, no "in conclusion" restatements)

Run the cut test on every section against the declared tier: keep what the reader needs before they can act, link what they need later, extract what only a higher tier wants, delete what no tier wants. Extraction is the verdict that gets skipped. Content a newcomer cannot use is usually not weak, it is answering a question they have not asked yet. Move it to modules/<topic>.md for a skill or docs/deep-dive/<topic>.md for a repo doc, and link it from the parent's lead. Never delete to hit a tier.

Show full SKILL.md (359 more words)Show less
Step 4: Run Slop Detector
bash
uv run --with pyyaml python scripts/slop_score.py --audit <files>
Skill(scribe:slop-detector)

The script locates every finding with a file and a line, including the low-confidence and opt-in categories the merge gate does not score. The skill says how to rewrite each one. Fix the findings before proceeding, and leave (low) and (medium) hits for a person to judge.

Step 5: Quality Gate

Verify against checklist:

Sentence-level:

  • No tier-1 slop words
  • Em dash count < 3 per 1000 words
  • Bullet ratio < 40%
  • All claims grounded with specifics
  • No formulaic openers or closers
  • Authorial perspective present
  • No emojis (unless explicitly requested)

Document-level (document-economy module):

  • Thesis stated in the lead, single and clear (2/2)
  • >80% of sentences carry, instance, bound, or repeat the thesis (2/2)
  • Thesis echoed at least 3 times; non-thesis repetition cut (2/2)
  • Writing time roughly proportional to (audience size × read frequency × per-read time)

Audience (audience-targeting module):

  • A tier is declared, and was asked for rather than guessed when the request omitted it (2/2)
  • Every section serves the declared tier
  • Off-tier content was extracted and linked, not deleted
  • Each new deep dive declares its own tier

Mode: Remediation

For cleaning up existing content:

Load: @modules/remediation-workflow.md

Step 1: Analyze Current State
bash
# Get slop score
Skill(scribe:slop-detector) --target file.md
Step 2: Section-by-Section Approach

For large files (>200 lines), edit incrementally:

markdown
## Section: [Name] (Lines X-Y)

**Current slop score**: X.X
**Issues found**: [list]

**Proposed changes**:
1. [Change 1]
2. [Change 2]

**Before**:
> [current text]

**After**:
> [proposed text]

Proceed? [Y/n/edit]
Step 3: Preserve Intent

Never change WHAT is said, only HOW. If meaning is unclear, ask.

Step 4: Re-verify

After edits, re-run slop-detector to confirm improvement.

Docstring-Specific Rules

When editing code comments:

  1. ONLY modify docstring/comment text
  2. Never change surrounding code
  3. Use imperative mood ("Validate input" not "Validates input")
  4. Brief is better - remove filler
  5. Keep Args/Returns structure if present

Module Reference

  • See modules/generation-guidelines.md for content creation patterns
  • See modules/quality-gates.md for validation criteria

Integration with Other Skills

SkillWhen to Use
slop-detectorAfter drafting, before approval
style-learnerBefore generation to load profile
sanctum:doc-updatesFor broader doc maintenance

Exit Criteria

  • Content created or remediated
  • Slop score < 1.5 (clean rating)
  • Audience tier declared in the request and honored in the draft
  • Document economy score >= 7/8, audience fit scoring 2/2
  • Every extraction landed in modules/ or docs/deep-dive/ and is linked from the parent's lead
  • Quality gate checklist passed
  • User approval received
  • No emojis present (unless specified)

© athola, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files in plugins/scribe/skills/doc-generator of athola/claude-night-market.

  • SKILL.md
  • modules/generation-guidelines.md
  • modules/quality-gates.md
  • modules/remediation-workflow.md

Open the folder on GitHubat commit 9f3eb00

Compare with similar skills

Doc Generator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Doc Generator compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Doc Generator this skillathola/claude-night-market342—~2.3kAutomated safety check: PassMIT
Diagram Designcathrynlavery/diagram-design45k1 repos~7.5kAutomated safety check: PassMIT
Simple Englishmoeru-ai/airi50k2 repos~4.6kAutomated safety check: PassMIT
Get API Docs with chubandrewyng/context-hub14k2 repos~775Automated safety check: PassMIT
Doc SyncJetBrains/ideavim10k2 repos~2.6kAutomated safety check: PassMIT
Mailspring App ScreenshotsFoundry376/Mailspring18k—~1.5kAutomated safety check: PassGPL-3.0

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Categories

Questions about Doc Generator

What does Doc Generator do?

Generates or remediates documentation with human-quality writing. Doc Generator is an agent skill from athola/claude-night-market. Generates or remediates documentation with human-quality writing.

When should I use Doc Generator?

Doc Generator fits situations like: creating new docs; rewriting AI-generated content; applying style profiles.

How do I install Doc Generator in Claude Code?

Run `npx skills add athola/claude-night-market --skill doc-generator -a claude-code`. Or copy the skill folder (plugins/scribe/skills/doc-generator in athola/claude-night-market) into .claude/skills/doc-generator in your project. Claude Code loads it when a task matches its description.

How do I install Doc Generator in Codex?

Run `npx skills add athola/claude-night-market --skill doc-generator -a codex`. Or copy the skill folder (plugins/scribe/skills/doc-generator in athola/claude-night-market) into .agents/skills/doc-generator in your project. Codex loads it when a task matches its description.

Can I use Doc Generator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add athola/claude-night-market --skill doc-generator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/doc-generator, .gemini/skills/doc-generator, .github/skills/doc-generator and .opencode/skills/doc-generator in your project.

What does Doc Generator need to run?

Going by SKILL.md and its folder, Doc Generator needs the command-line tools its instructions call (uv). Our summary lists: Python 3.

Does Doc Generator access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Doc Generator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Doc Generator use?

Doc Generator is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Doc Generator use?

About 2.3k tokens (SKILL.md is roughly 9.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Doc Generator?

Skills that share tags, products or a category with Doc Generator: Diagram Design (cathrynlavery/diagram-design, 45k stars), Simple English (moeru-ai/airi, 50k stars), Get API Docs with chub (andrewyng/context-hub, 14k stars) and Doc Sync (JetBrains/ideavim, 10k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Doc Generator?

athola (a GitHub user) maintains it in athola/claude-night-market, which has 342 GitHub stars. The repository holds 159 skills in this directory. The repository was last updated on October 6, 2026.

Source: athola/claude-night-market on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.