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Agent skill

Doc Co-Authoring Workflow

by shareAI-lab in shareAI-lab/Kode-CLI

Guides a three-stage workflow for turning partial context into a clear PRD, RFC or design doc: capture context, draft section by section, then test with a fresh reader.

Apache-2.0Auto-check passedWriting & Content

Install Doc Co-Authoring Workflow

skills CLI
$ npx skills add shareAI-lab/Kode-CLI --skill doc-coauthoring -a claude-code

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

GitHub CLI
$ gh skill install shareAI-lab/Kode-CLI doc-coauthoring --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/shareAI-lab/Kode-CLI.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/builtin-skills/skills/doc-coauthoring .claude/skills/doc-coauthoring && 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-coauthoring
GitHub stars
5.2k
Token cost
~977 tokens
SKILL.md length
517 words
Files
3 (incl. references)
Skills in repo
8
Repo updated
First seen
Licence
Apache-2.0

At a glance

Guides a three-stage workflow for turning partial context into a clear PRD, RFC or design doc: capture context, draft section by section, then test with a fresh reader.

  • Works in 3 steps: Context Capture (close the gap) → Outline-First Drafting (iterate by… → Reader Testing (catch blind spots)
  • Writing a PRD, RFC, design doc or proposal from scattered notes
  • SKILL.md covers Triggers, The Workflow (3 stages), Default Section Templates and Quality Bar (what to optimize…
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

The skill keeps you in charge of decisions while the agent builds a document that works for readers who lack the author's context. Stage one collects the minimum context: doc type and goal, audience, constraints, current state, options considered, success criteria and open questions. It yields a short context snapshot, ranked open questions and a one-screen outline.

Stage two drafts outline-first, one section at a time, with a section intent, a short draft, a quick review by you and a running decision log, while unresolved items stay visible in an Open Questions and Risks section. Stage three tests the draft for readability and completeness from the point of view of a reader without context. If you prefer freeform writing, the workflow is kept light, and references/templates.md holds document templates.

When your agent uses it

  • Writing a PRD, RFC, design doc or proposal from scattered notes
  • Turning a team discussion into a document others can read
  • Setting up a template or standard for recurring documents
  • Checking a draft for blind spots with a fresh-reader review

Example prompts

  • “Help me write an RFC for moving our job queue to a new broker, starting from my rough notes.”
  • “Summarize our discussion into a decision doc the whole team can read.”
  • “Create a standard template for our weekly incident write-ups.”

Workflow steps

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

  1. Context Capture (close the gap)
  2. Outline-First Drafting (iterate by section)
  3. Reader Testing (catch blind spots)

What it can do on your machine

Read from SKILL.md and the folder at commit c7f6fcc. 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

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    No URLs in SKILL.md.

    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 Co-Authoring Workflow loads about 977 tokens when it runs, and up to ~1.2k if it reads all its reference files. Until then it costs about 87 tokens; SKILL.md has 517 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~87
When it runs · the whole SKILL.md, loaded when a task matches
~977
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.2k

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 shareAI-lab/Kode-CLI at commit c7f6fcc, republished under its Apache-2.0 licence (© shareAI-lab). 517 words, ~977 tokens.

Download SKILL.mdSave it as .claude/skills/doc-coauthoring/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
doc-coauthoring
description
A structured workflow for co-authoring high-signal docs (PRD, RFC, design docs, proposals, decision records). Use when the user needs to turn messy context into a readable artifact with clear goals, tradeoffs, and next steps. Emphasizes context capture, outline-first drafting, and context-free reader testing to catch blind spots.
license
Complete terms in LICENSE.txt

Doc Co-Authoring

Turn partial context into a clear document by following a staged workflow. Keep the user in control of decisions, and optimize for a doc that works for readers who do not share the author’s context.

Triggers

Use this workflow when the user asks to:

  • write or refine documentation, proposals, RFCs, PRDs, decision docs, specs
  • “summarize our discussion into a doc”
  • “make this readable for others” / “share with the team”
  • create a template or standard for recurring documents

If the user explicitly wants freeform writing, keep the workflow lightweight (ask fewer questions; draft faster).

The Workflow (3 stages)

Stage 1 — Context Capture (close the gap)

Goal: collect the minimum context required to write a doc that is correct, scoped, and actionable.

Ask for:

  1. Doc type + goal: what is this document for, and what decision/action should it unlock?
  2. Audience: who will read it, and what do they already know?
  3. Constraints: deadlines, non-goals, dependencies, security/compliance, platform limits.
  4. Current state: what exists today? what’s broken? what’s missing?
  5. Options considered: at least 1–2 alternatives and why they may/ may not work.
  6. Success criteria: how we know it worked (metrics, user outcomes, acceptance tests).
  7. Open questions: unknowns that block writing certain sections.

Output of Stage 1:

  • a short “context snapshot”
  • a list of open questions (ranked by importance)
  • a proposed doc outline (1 screen)
Stage 2 — Outline-First Drafting (iterate by section)

Goal: draft a document in layers without losing coherence.

Rules:

  • Outline before prose. Do not write full paragraphs until the outline is agreed.
  • One section at a time. Draft → review → revise, then move on.
  • Maintain a decision log (small bullet list) so changes are explicit.
  • Keep unknowns visible: unresolved items stay in an “Open Questions / Risks” section, not hidden.

Recommended iteration loop per section:

  1. Write a 3–7 bullet “section intent” (what this section must answer).
  2. Draft the section (short, concrete).
  3. Ask the user for a quick pass: “What’s wrong / missing / too detailed?”
  4. Revise and update the decision log.
Show full SKILL.md (181 more words)Show less
Stage 3 — Reader Testing (catch blind spots)

Goal: validate readability and completeness for a reader without the author’s context.

Method:

  • Prepare a clean-context review prompt: “You are a reviewer with no prior context. Read this doc and identify: missing context, unclear terms, ambiguous decisions, hidden assumptions, and where you’d ask questions.”
  • If sub-agents are available, run the review in a fresh agent session. Otherwise, run the review yourself by explicitly pretending you have no access to prior conversation.

Output of Stage 3:

  • a short list of fixes (highest leverage first)
  • revised doc with clarified assumptions, terms, and decisions

Default Section Templates

Load references/templates.md and pick the closest template:

  • Decision record (ADR-lite)
  • Product requirements (PRD-lite)
  • Technical design / RFC
  • Proposal / pitch

Quality Bar (what to optimize for)

The doc should make it easy for a reader to answer:

  • What problem are we solving, for whom, and why now?
  • What are we proposing, and what are we not doing?
  • What options did we consider, and what tradeoffs drive the choice?
  • What are the risks, unknowns, and mitigations?
  • What are the next steps and owners?

© shareAI-lab, Apache-2.0. 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 2 other files (references) in packages/builtin-skills/skills/doc-coauthoring of shareAI-lab/Kode-CLI.

  • SKILL.md
  • LICENSE.txt
  • references/templates.md

Open the folder on GitHubat commit c7f6fcc

Compare with similar skills

Doc Co-Authoring Workflow 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 Co-Authoring Workflow compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Doc Co-Authoring Workflow this skillshareAI-lab/Kode-CLI5.2k—~977Automated safety check: PassApache-2.0
Technical Writingluoling8192/technical-writing217—~2.2kAutomated safety check: PassMIT
Technical WriterRightNow-AI/openfang18k—~891Automated safety check: PassApache-2.0
Run Assert Evalresponsibleai/ASSERT330—~11kAutomated safety check: NotesMIT
Schematicblader/schematic240—~2.2kAutomated safety check: PassMIT
Shep Workstreamsshep-ai/shep264—~2.5kAutomated safety check: PassMIT

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Categories

Questions about Doc Co-Authoring Workflow

What does Doc Co-Authoring Workflow do?

Guides a three-stage workflow for turning partial context into a clear PRD, RFC or design doc: capture context, draft section by section, then test with a fresh reader. The skill keeps you in charge of decisions while the agent builds a document that works for readers who lack the author's context. Stage one collects the minimum context: doc type and goal, audience, constraints, current state, options considered, success criteria and open questions.

When should I use Doc Co-Authoring Workflow?

Doc Co-Authoring Workflow fits situations like: writing a PRD, RFC, design doc or proposal from scattered notes; turning a team discussion into a document others can read; setting up a template or standard for recurring documents; checking a draft for blind spots with a fresh-reader review.

How do I install Doc Co-Authoring Workflow in Claude Code?

Run `npx skills add shareAI-lab/Kode-CLI --skill doc-coauthoring -a claude-code`. Or copy the skill folder (packages/builtin-skills/skills/doc-coauthoring in shareAI-lab/Kode-CLI) into .claude/skills/doc-coauthoring in your project. Claude Code loads it when a task matches its description.

How do I install Doc Co-Authoring Workflow in Codex?

Run `npx skills add shareAI-lab/Kode-CLI --skill doc-coauthoring -a codex`. Or copy the skill folder (packages/builtin-skills/skills/doc-coauthoring in shareAI-lab/Kode-CLI) into .agents/skills/doc-coauthoring in your project. Codex loads it when a task matches its description.

Can I use Doc Co-Authoring Workflow 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 shareAI-lab/Kode-CLI --skill doc-coauthoring -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-coauthoring, .gemini/skills/doc-coauthoring, .github/skills/doc-coauthoring and .opencode/skills/doc-coauthoring in your project.

What does Doc Co-Authoring Workflow need to run?

SKILL.md names no scripts, command-line tools or credentials: Doc Co-Authoring Workflow is instructions for the agent only.

Does Doc Co-Authoring Workflow access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Doc Co-Authoring Workflow 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 Co-Authoring Workflow use?

Doc Co-Authoring Workflow is published under the Apache-2.0 licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Doc Co-Authoring Workflow use?

About 977 tokens (SKILL.md is roughly 3.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 267 tokens, read only when the agent opens those files.

What are the alternatives to Doc Co-Authoring Workflow?

Skills that share tags, products or a category with Doc Co-Authoring Workflow: Technical Writing (luoling8192/technical-writing, 217 stars), Technical Writer (RightNow-AI/openfang, 18k stars), Run Assert Eval (responsibleai/ASSERT, 330 stars) and Schematic (blader/schematic, 240 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Doc Co-Authoring Workflow?

shareAI-lab (a GitHub organization) maintains it in shareAI-lab/Kode-CLI, which has 5,234 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on October 9, 2026.

Source: shareAI-lab/Kode-CLI on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.