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Agent Doc Discipline

CommunityPopular
Yeachan-Heo
agent-doc-discipline

Writing-time discipline for documents agents consume (the five surfaces, specs, tickets, .omc/skills/) — every rule checkable and carrying a why, steps before reference, one meaning in one home, no restating what the environment already says. Mandatory at drydock seed generation and the launch C5 sediment pass; opt-in for any other agent-facing doc edit. The companion of minimal-code-discipline: that one disciplines code, this one disciplines papers.

Overview

PublisherYeachan-Heo
Repositoryoh-my-claudecode
Skill nameagent-doc-discipline
Stars
39.8K
Forks
3.6K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Yeachan-Heo on GitHub. Read the source before you install it.

Installation

Install the Agent Doc Discipline AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Yeachan-Heo/oh-my-claudecode/tree/main/skills/agent-doc-discipline
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Yeachan-Heo/oh-my-claudecode.git /tmp/oh-my-claudecode
mkdir -p .claude/skills
cp -r /tmp/oh-my-claudecode/skills/agent-doc-discipline .claude/skills/agent-doc-discipline
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Doc Discipline in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agent Doc Discipline on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agent Doc Discipline is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Agent Doc Discipline

Use this skill to apply a writing-time discipline while creating or editing any document an agent consumes to act: the five surfaces (CLAUDE.md, GLOSSARY.md, docs/standards/, design-system/, .omc/skills/), specs, tickets, and skill files. The test a document must pass: a fresh agent session can act on it by reading alone.

Mandatory when: drydock generates surface seeds, the launch C5 sediment pass writes a lesson into a slot. Opt-in for every other edit — but any edit to an agent-facing document should survive these rules.

When Not to Use

Documents written for humans only: docs/business/ narrative, ADR decision stories, READMEs for human onboarding. They may still follow the rules where it costs nothing, but they are not held to this discipline.

The Discipline

Write for a reader with no chat history. The document is self-describing: nothing leans on "as discussed", a prior session, or knowledge that lives in someone's head. Test: a brand-new agent session can act on the document by reading alone.

Every rule checkable and carrying a why. No "keep it clean" — write the observable condition and the reason. Test: an agent can decide pass/fail from the text alone, and the why is stated next to the rule.

One meaning, one home. Each rule or definition has a single authoritative place; duplication is drift waiting to happen. Test: changing a behavior is a one-place edit.

Never restate what the environment confesses. Package scripts, directory layouts, --help output are lookups, not documents — a copied lookup goes stale. Document only what cannot be found by looking: the unwritten convention, the reason behind a choice, the gotcha. Test: every line survives "can this be looked up elsewhere?".

Steps first, reference behind, rare material behind a pointer. What to do, in order, at the top; consult-on-demand rules below; low-frequency material pushed behind a pointer whose wording names the branches that should trigger reaching it. Test: the next action is findable within the first screen.

Every step ends on a completion criterion. Done must be tellable from not-done — a vague bound invites premature completion. Test: for each step, "how do I know this is finished?" has an answer in the text.

A procedure longer than two steps is numbered. The numbers are stable references: a reader can name step 3, follow the order, and jump without re-reading. An unnumbered procedure of many steps makes the reader hold the order in their head. Test: every procedure of three or more steps carries its numbers.

A list is capped at what a reader holds in one glance. A list that outgrows the reader's grasp loses its point — nothing in it is findable. A longer enumeration becomes structure (a table, subsections) or splits. This governs the writing of documents; it never touches the machinery of a gate or a batched decision, which lives in the methodology, not the prose. Test: every list in the document fits in one glance, and any longer enumeration has become structure.

Deferred and scheduled work states when. A document that defers work to a later step, session, or release states that timing next to the work it defers — "when" is a fact the reader needs to act, and an unstated deferral reads as an unstarted one. The timing is stated in the prose only; it never rebinds a checkpoint the methodology pushes right deliberately. Test: every deferral in the document carries its when.

Close on a next action a reader can start now. A report, ticket, or session-close pointer ends not with a summary but with the one next step a reader can begin in under two minutes — the destination, the pointer, or the command. A close that only summarizes makes the reader re-derive what to do first. Test: the last line answers "what do I do next?" without scrolling up.

Re-state the position each time the reader rejoins. A document a returning reader touches mid-flight (a long spec, a run report, a map Notes section) opens the new material with where things stand — step, phase, or decision count — before adding anything new. Test: a reader arriving cold can locate the current state in the first two lines of the newest section.

Prompt the positive. State the target behavior; a prohibition is reserved for hard guardrails and is always paired with the positive target. Test: every prohibition in the document names the thing to do instead.

Scrape barnacles on write. When the document contains stale or redundant material, remove it in the same edit; when it does not, add only the required material and do not invent deletions. A sentence the model already obeys by default pays load for nothing — delete the whole sentence. Test: every line re-read earns its place against "does this change behavior versus the default?", and any stale or redundant material found during the edit is gone.

Verification

Before reporting a document change done, confirm:

  • a fresh session could act on it without asking a human anything
  • every rule is checkable and states its why; no rule restates a lookup
  • meanings live in one place; pointers name their trigger branches
  • stale or redundant material found during the edit was removed, while valid unrelated content was preserved
  • closes end on a next action the reader can start now; rejoining readers find the current state stated before new material
  • procedures of three or more steps are numbered; lists fit in one glance; every deferral states its when

Frequently asked questions

What does the Agent Doc Discipline AI skill do?

Writing-time discipline for documents agents consume (the five surfaces, specs, tickets, .omc/skills/) — every rule checkable and carrying a why, steps before reference, one meaning in one home, no restating what the environment already says. Mandatory at drydock seed generation and the launch C5 sediment pass; opt-in for any other agent-facing doc edit. The companion of minimal-code-discipline: that one disciplines code, this one disciplines papers.

Why use Agent Doc Discipline on TypingMind?

Because you install it once and use it with any model. Agent Doc Discipline is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agent Doc Discipline in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Yeachan-Heo/oh-my-claudecode/tree/main/skills/agent-doc-discipline. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Agent Doc Discipline?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agent Doc Discipline?

As many as you like. As long as a model supports skills, you can use Agent Doc Discipline with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agent Doc Discipline AI skill free?

Yes. It is published on GitHub by Yeachan-Heo under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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