Agent skill

Clarification

by tmdgusya in tmdgusya/engineering-discipline

A skill your agent uses when a user's request is vague, ambiguous, or underspecified.

No licenceAuto-check passed

Install Clarification

skills CLI
$ npx skills add tmdgusya/engineering-discipline --skill clarification -a claude-code

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

GitHub CLI
$ gh skill install tmdgusya/engineering-discipline clarification --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/tmdgusya/engineering-discipline.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/clarification .claude/skills/clarification && 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
clarification
GitHub stars
125
Token cost
~3.4k tokens
SKILL.md length
1,402 words
Files
1
Skills in repo
11
Repo updated
First seen
Licence
None found

At a glance

A skill your agent uses when a user's request is vague, ambiguous, or underspecified.

  • Works in 5 steps: Explore before you ask. Dispatch recon… → Always use subagents. Dispatch subagents… → Do not start implementation until you… → …
  • A users request is vague
  • SKILL.md covers Core Principle, Hard Gates, When To Use and When NOT To Use, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Clarification is an agent skill from tmdgusya/engineering-discipline. Use when a user's request is vague, ambiguous, or underspecified. Explores the codebase first, then runs an iterative Q&A loop grounded in the findings until ambiguity is gone. Outputs a clear, well-scoped context brief so the user can plan sharply. Triggers on "I want to...", "I need...", "let's build...", "can you help me...", "we should...", or any request where the full scope isn't immediately clear.

Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: SKILL for engineering-discipline.

When your agent uses it

  • A users request is vague
  • Can you help me...
  • Any request where the full scope isnt immediately clear

Example prompts

  • “I want to...”
  • “I need...”
  • “s build...”
  • “/clarification”

Workflow steps

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

  1. Explore before you ask. Dispatch recon subagents BEFORE the first question. Every question must be grounded in exploration findings…
  2. Always use subagents. Dispatch subagents before the first question, and again in response to the user's answers.
  3. Do not start implementation until you can say "this is clear enough." Understanding must be complete at the codebase level.
  4. Every question must narrow scope. Do not repeat questions at the same level of ambiguity. Independent questions may be bundled into one…
  5. Never dump raw code exploration results on the user. Summarize findings in the context of the user's question.

What it can do on your machine

Read from SKILL.md and the folder at commit 137dead. 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 dot and 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

Clarification loads about 3.4k tokens when it runs. Until then it costs about 105 tokens; SKILL.md has 1,402 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~105
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k

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

Without a licence we can't republish the file, so here is its outline and opening line. It has 1,402 words (~3,424 tokens).

“Narrows vague user requests into well-defined work scopes. Explores the codebase first, then asks questions grounded in what exploration found, iterating until ambiguity is gone.”

— opening of SKILL.md by tmdgusya
name
clarification

Read the full SKILL.md on GitHub

Files

Just SKILL.md in skills/clarification of tmdgusya/engineering-discipline.

Open the folder on GitHubat commit 137dead

Compare with similar skills

Clarification 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.

Clarification compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Clarification this skilltmdgusya/engineering-discipline125—~3.4kAutomated safety check: PassNone
Requirements Clarificationasgeirtj/system_prompts_leaks69k—~687Automated safety check: PassCC0-1.0
Vagueteam-attention/plugins-for-claude-natives827—~1kAutomated safety check: PassMIT
Clarification BrokerSeemSeam/claude_codex_bridge3.6k—~193Automated safety check: PassCustom licence
Clarify Ambiguous Requestsaiming-lab/MetaClaw3.5k—~216Automated safety check: PassMIT
Ambiguity Reportlawve-ai/awesome-legal-skills836—~4.6kAutomated safety check: PassApache-2.0

Similar skills

  • Requirements Clarification

    asgeirtj/system_prompts_leaks

    Clarify a material user-owned product decision before substantive implementation commitments.

    69k GitHub stars~687 tokensUpdated today
    Backend & APIsAuto-check passed
  • Vague

    team-attention/plugins-for-claude-natives

    This skill should be used when the user's request or requirement is ambiguous and needs iterative questioning to become actionable.

    827 GitHub stars~1k tokensUpdated 5 mo ago
    Agent WorkflowsAuto-check passed
  • Clarification Broker

    SeemSeam/claude_codex_bridge

    Compress planner candidate questions into a compact frontdesk-facing clarification batch and normalize answers back to planner.

    3.6k GitHub stars~193 tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Clarify Ambiguous Requests

    aiming-lab/MetaClaw

    A skill your agent uses when the user's request is ambiguous, under-specified, or could be interpreted in multiple ways.

    3.5k GitHub stars~216 tokensUpdated 4 mo ago
    AI & LLM EngineeringAuto-check passed
  • Ambiguity Report

    lawve-ai/awesome-legal-skills

    Turn an interpretive-ambiguity audit of a legal text — contract, statute, regulation, or judicial opinion — into a polished deliverable.

    836 GitHub stars~4.6k tokensUpdated 6 days ago
    Documents & OfficeAuto-check passed
  • Ambiguity Detector

    majiayu000/claude-skill-registry

    Detects and analyzes ambiguous language in software requirements and user stories.

    666 GitHub starsUsed in 1 repo~2.5k tokens
    Product & Project ManagementAuto-check passed

More from tmdgusya/engineering-discipline

All 11 skills in this repo
  • Clean AI Slop

    tmdgusya/engineering-discipline

    Corrective cleanup of AI-generated code — removes LLM-specific patterns while preserving behavior.

    125 GitHub stars~1.9k tokensUpdated 3 mo ago
    Auto-check passed
  • Karpathy

    tmdgusya/engineering-discipline

    Behavioral guardrails to prevent common LLM coding mistakes — enforces surgical changes, assumption verification, and scope discipline before and during implementation.

    125 GitHub stars~2k tokensUpdated 3 mo ago
    Auto-check passed
  • Plan Crafting

    tmdgusya/engineering-discipline

    A skill your agent uses when a task's scope is clear and multi-step implementation is needed, before touching code.

    125 GitHub stars~4k tokensUpdated 3 mo ago
    Auto-check passed
  • Review Work

    tmdgusya/engineering-discipline

    Use after run-plan completes to independently verify the implementation.

    125 GitHub stars~2.5k tokensUpdated 3 mo ago
    Auto-check passed
  • Run Plan

    tmdgusya/engineering-discipline

    A skill your agent uses when you have a written implementation plan to execute.

    125 GitHub stars~4.6k tokensUpdated 3 mo ago
    Auto-check passed
  • Systematic Debugging

    tmdgusya/engineering-discipline

    A skill your agent uses when encountering any bug, test failure, or unexpected behavior.

    125 GitHub stars~2k tokensUpdated 3 mo ago
    Auto-check passed

Questions about Clarification

What does Clarification do?

A skill your agent uses when a user's request is vague, ambiguous, or underspecified. Clarification is an agent skill from tmdgusya/engineering-discipline. Use when a user's request is vague, ambiguous, or underspecified.

When should I use Clarification?

Clarification fits situations like: A users request is vague; can you help me..; any request where the full scope isnt immediately clear.

How do I install Clarification in Claude Code?

Run `npx skills add tmdgusya/engineering-discipline --skill clarification -a claude-code`. Or copy the skill folder (skills/clarification in tmdgusya/engineering-discipline) into .claude/skills/clarification in your project. Claude Code loads it when a task matches its description.

How do I install Clarification in Codex?

Run `npx skills add tmdgusya/engineering-discipline --skill clarification -a codex`. Or copy the skill folder (skills/clarification in tmdgusya/engineering-discipline) into .agents/skills/clarification in your project. Codex loads it when a task matches its description.

Can I use Clarification 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 tmdgusya/engineering-discipline --skill clarification -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/clarification, .gemini/skills/clarification, .github/skills/clarification and .opencode/skills/clarification in your project.

What does Clarification need to run?

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

Does Clarification 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 Clarification 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 Clarification use?

No licence was found for Clarification or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Clarification use?

About 3.4k tokens (SKILL.md is roughly 14k 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 Clarification?

Skills that share tags, products or a category with Clarification: Requirements Clarification (asgeirtj/system_prompts_leaks, 69k stars), Vague (team-attention/plugins-for-claude-natives, 827 stars), Clarification Broker (SeemSeam/claude_codex_bridge, 3.6k stars) and Clarify Ambiguous Requests (aiming-lab/MetaClaw, 3.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Clarification?

tmdgusya (a GitHub user) maintains it in tmdgusya/engineering-discipline, which has 125 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on July 3, 2026.

Source: tmdgusya/engineering-discipline on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.