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Agent skill

Intent Requirements Intake

by Yeachan-Heo in Yeachan-Heo/oh-my-claudecode

Turns a pasted chat log or spoken problem report from support or ops staff into a reviewed five-section intent.md through numbered batches of questions.

MITAuto-check passedProduct & Project Management

Install Intent Requirements Intake

skills CLI
$ npx skills add Yeachan-Heo/oh-my-claudecode --skill intent -a claude-code

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

GitHub CLI
$ gh skill install Yeachan-Heo/oh-my-claudecode intent --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/Yeachan-Heo/oh-my-claudecode.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/intent .claude/skills/intent && 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
intent
GitHub stars
40k
Token cost
~1.5k tokens
SKILL.md length
720 words
Files
1
Skills in repo
47
Repo updated
First seen
Licence
MIT

At a glance

Turns a pasted chat log or spoken problem report from support or ops staff into a reviewed five-section intent.md through numbered batches of questions.

  • Works in 6 steps: Opening inventory: restate the problem… → Numbered batch questioning: list every… → Re-inventory: apply the answers; if gaps… → …
  • A support or ops person has a pasted chat log describing a product problem
  • SKILL.md covers Role contract, The conversation (numbered…, The intent.md template and Grading open questions, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Intent is a requirements intake for people who see product problems first but cannot write engineering specs. The agent restates the problem in one sentence, shows what is known and missing across five sections, and lists every gap as numbered questions in a single batch. The contributor answers by number, and anything unknown is recorded as an item to confirm instead of being pressed until someone guesses.

The five sections are problem, goal, users and systems, constraints and open questions. A draft is only produced when each passes its bar: observable phenomena with no solution inside, a one-sentence goal naming entities and relations, real names for users and systems, explicit boundaries and non-goals, and an open-question list that is non-empty or explicitly empty. A soft prompt to draft appears at round 6 and a hard cap at round 12, and an early exit is never blocked.

The agent drafts the file under docs/intents at draft status and the contributor confirms the wording. Humans keep every decision: the supervisor submits, the product owner verifies facts and signs accept or reject, and the agent never signs or rejects for anyone. After tracker review, the accepted intent is handed to the /launch step as its mission brief. The output is decisions, not code.

When your agent uses it

  • A support or ops person has a pasted chat log describing a product problem
  • Turning a verbal problem report into a goal-level requirements file engineers can act on
  • Preparing a reviewed mission brief before launching engineering work

Example prompts

  • “Here is the customer chat about failed invoice exports. Turn it into an intent file.”
  • “Ask me the open questions about the checkout timeout complaint so we can draft the intent.”
  • “Hand the accepted intent for the refund delay issue over to launch as the mission brief.”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Opening inventory: restate the problem in one sentence, then show the five-section inventory (known / missing per section).
  2. Numbered batch questioning: list every gap as numbered questions in one batch. The contributor answers by number (1 是; 2 不确定). Unknown…
  3. Re-inventory: apply the answers; if gaps remain, emit the next numbered batch. One round = one batch.
  4. Stop gate (all five sections must pass)
  5. Soft limits: soft prompt at round 6 ("draft with current clarity?"), hard cap at round 12. An early exit is never blocked — thin sections…
  6. Draft: the agent drafts docs/intents//intent.md (template below) at status: draft; the contributor confirms wording before any submission.

What it can do on your machine

Read from SKILL.md and the folder at commit 454bae0. 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 (its code samples are markdown).

    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

Intent Requirements Intake loads about 1.5k tokens when it runs. Until then it costs about 95 tokens; SKILL.md has 720 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~95
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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 Yeachan-Heo/oh-my-claudecode at commit 454bae0, republished under its MIT licence (© Yeachan-Heo). 720 words, ~1,545 tokens.

Download SKILL.mdSave it as .claude/skills/intent/SKILL.md (or your agent's skills folder).
name
intent
description
Shipyard's internal requirements intake for non-engineer contributors (support/ops) — turn a pasted chat log or verbal problem report into a five-section intent.md through numbered batch questioning with a completion gate, walk it through tracker review with harbor's four records, and hand the accepted intent to /launch as its mission brief. Produces decisions, not code.
argument-hint
<pasted feedback / chat log | path to existing intent.md | nothing to continue open review>
level
3
disable-model-invocation
true

Intent

Intent is the shipyard's internal intake: support/ops staff see product problems first but cannot write engineering specs. The intent skill converts their conversation into a goal-level YAML+markdown artifact that an owner reviews and signs, so engineering receives a fog-free mission. It stands on the verifiability boundary — the agent asks, records, and drafts; humans submit, verify, and sign.

Design provenance: every decision here was pinned by a wayfinder map (7 tickets) and walked end-to-end in a demo repository before implementation.

Role contract

  • The contributor (e.g. support staff) pastes raw feedback or a chat log. The agent never invents facts; unknowns become explicit 待确认 items.
  • Decisions are the humans': the contributor confirms wording, the supervisor submits, the product owner verifies facts and signs accept/reject. The agent never signs, never rejects on anyone's behalf, and never stands in for a reviewer.
  • The stop gate is a completion gate, not an ambiguity score — no math is borrowed from deep-interview; only its Goal and Constraint clarity judgments are reused as quality bars.

The conversation (numbered batch questioning)

  1. Opening inventory: restate the problem in one sentence, then show the five-section inventory (known / missing per section).
  2. Numbered batch questioning: list every gap as numbered questions in one batch. The contributor answers by number (1 是; 2 不确定). Unknown answers are recorded as 待确认 and pushed into open questions — never pressed until guessed.
  3. Re-inventory: apply the answers; if gaps remain, emit the next numbered batch. One round = one batch.
  4. Stop gate (all five sections must pass):
    • 问题: observable phenomena, no solution embedded
    • 目标: one sentence, no qualifiers, names entities and relations (deep-interview Goal Clarity bar)
    • 用户和系统: real names for users and systems; unknowns written as 待确认 and counted as open questions
    • 约束: boundaries, limits, and non-goals explicit (deep-interview Constraint Clarity bar)
    • 未决问题: list non-empty, or an explicit 无
  5. Soft limits: soft prompt at round 6 ("draft with current clarity?"), hard cap at round 12. An early exit is never blocked — thin sections surface as longer open questions, and review is the gate that rejects them.
  6. Draft: the agent drafts docs/intents/<slug>/intent.md (template below) at status: draft; the contributor confirms wording before any submission.

The intent.md template

markdown
---
intent: <slug>
title: <one-line title>
author: <name (role)>
date: <YYYY-MM-DD>
status: draft | in-review | accepted | rejected
round: <tracker review round>
---

## 问题
<observable phenomena, no solution>

## 目标
one sentence, no qualifiers

## 用户和系统
<who the users are, which systems, real names; unknowns as 待确认>

## 约束
<boundaries, non-goals; cite Rules pillar files when a constraint comes from them>

## 未决问题
- [阻塞|非阻塞] <question>   ← agent suggests, product owner finalizes

Grading open questions

The test for 阻塞: "can the spec still be approved without answering it?" No → blocking; yes → non-blocking (tracked, may ride into development). The drafting agent suggests grades; the product owner finalizes at spec approval.

Show full SKILL.md (319 more words)Show less

Review handoff (harbor four records)

Review runs on the repo's tracker — the tracker is the only record source; intent.md frontmatter mirrors status only. One record file per Intent, rounds accumulate inside it. Required fields per record: signer, date, verdict, link to intent.md, round, rejection reason (mandatory on reject).

  • proposal = supervisor submits the Intent (intent.md → status: in-review)
  • verification = product owner checks facts against repo evidence before deciding; the agent may draft the fact-check table, but the signature belongs to the reviewer — no repo evidence to check? Then verification records why none was needed
  • decision = accept or reject; reject requires a reason, which is the key input to resubmission
  • execution result = spec generation completed for this Intent

Rejected → revise → resubmit in the same file under the next round number. History stays traceable.

Handoff to launch

An accepted intent (status: accepted) is a valid mission brief. Launch's spec synthesis then follows the four-step contract:

  1. read docs/intents/<slug>/intent.md (must be accepted, latest round)
  2. combine with the existing codebase
  3. follow the Rules pillar (CLAUDE.md + docs/standards/ + docs/business/)
  4. list every doubt and rule conflict — graded into the spec's pending-confirmation section

Intent open questions carry into the spec verbatim, keeping their pending status.

Amendment

New information after acceptance (typically surfaced by the first spec) is an amendment: anyone may initiate, the submitter signs, and it always re-enters full review as a new round — no minor-change exemption. An intent change marks the generated spec stale; the spec is regenerated from the new intent and re-approved. No separate amendment record type: rounds carry it.

Conflict sedimentation

Conflict conclusions in the spec's pending section follow precedent-based routing: case-local answers stay in the spec; conclusions that will bind later Intents sediment into the Rules pillar (docs/business/ for business rules, docs/standards/ for behavior rules); hard-to-reverse technical tradeoffs become ADRs. Never double-write; never defer archiving. The product owner decides whether a conclusion is precedent-setting; the tech lead advises the destination.

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

Files

Just SKILL.md in skills/intent of Yeachan-Heo/oh-my-claudecode.

Open the folder on GitHubat commit 454bae0

Compare with similar skills

Intent Requirements Intake 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.

Intent Requirements Intake compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Intent Requirements Intake this skillYeachan-Heo/oh-my-claudecode40k—~1.5kAutomated safety check: PassMIT
Ouroboros PM InterviewQ00/ouroboros6.2k—~5.7kAutomated safety check: PassMIT
User Alignment and Agent-Ready PRDstryproduck/produck-skills510—~5.3kAutomated safety check: PassApache-2.0
Creating Issuesopsmill/infrahub533—~1.2kAutomated safety check: PassApache-2.0
Grilling Ideasopsmill/infrahub533—~3.8kAutomated safety check: PassApache-2.0
Feature ForgeJeffallan/claude-skills12k—~1.1kAutomated safety check: PassMIT

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Categories

Questions about Intent Requirements Intake

What does Intent Requirements Intake do?

Turns a pasted chat log or spoken problem report from support or ops staff into a reviewed five-section intent.md through numbered batches of questions. Intent is a requirements intake for people who see product problems first but cannot write engineering specs. The agent restates the problem in one sentence, shows what is known and missing across five sections, and lists every gap as numbered questions in a single batch.

When should I use Intent Requirements Intake?

Intent Requirements Intake fits situations like: A support or ops person has a pasted chat log describing a product problem; turning a verbal problem report into a goal-level requirements file engineers can act on; preparing a reviewed mission brief before launching engineering work.

How do I install Intent Requirements Intake in Claude Code?

Run `npx skills add Yeachan-Heo/oh-my-claudecode --skill intent -a claude-code`. Or copy the skill folder (skills/intent in Yeachan-Heo/oh-my-claudecode) into .claude/skills/intent in your project. Claude Code loads it when a task matches its description.

How do I install Intent Requirements Intake in Codex?

Run `npx skills add Yeachan-Heo/oh-my-claudecode --skill intent -a codex`. Or copy the skill folder (skills/intent in Yeachan-Heo/oh-my-claudecode) into .agents/skills/intent in your project. Codex loads it when a task matches its description.

Can I use Intent Requirements Intake 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 Yeachan-Heo/oh-my-claudecode --skill intent -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/intent, .gemini/skills/intent, .github/skills/intent and .opencode/skills/intent in your project.

What does Intent Requirements Intake need to run?

SKILL.md names no scripts, command-line tools or credentials: Intent Requirements Intake is instructions for the agent only.

Does Intent Requirements Intake 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 Intent Requirements Intake 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 Intent Requirements Intake use?

Intent Requirements Intake 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 Intent Requirements Intake use?

About 1.5k tokens (SKILL.md is roughly 6.2k 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 Intent Requirements Intake?

Skills that share tags, products or a category with Intent Requirements Intake: Ouroboros PM Interview (Q00/ouroboros, 6.2k stars), User Alignment and Agent-Ready PRDs (tryproduck/produck-skills, 510 stars), Creating Issues (opsmill/infrahub, 533 stars) and Grilling Ideas (opsmill/infrahub, 533 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Intent Requirements Intake?

Yeachan-Heo (a GitHub user) maintains it in Yeachan-Heo/oh-my-claudecode, which has 39,720 GitHub stars. The repository holds 47 skills in this directory. The repository was last updated on October 8, 2026.

Source: Yeachan-Heo/oh-my-claudecode on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.