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Agent skill

Clarify Ambiguous Requests

by aiming-lab in aiming-lab/MetaClaw

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

MITAuto-check passedAI & LLM Engineering

Install Clarify Ambiguous Requests

skills CLI
$ npx skills add aiming-lab/MetaClaw --skill clarify-ambiguous-requests -a claude-code

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

GitHub CLI
$ gh skill install aiming-lab/MetaClaw clarify-ambiguous-requests --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/aiming-lab/MetaClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/memory_data/skills/clarify-ambiguous-requests .claude/skills/clarify-ambiguous-requests && 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
clarify-ambiguous-requests
GitHub stars
3.5k
Token cost
~216 tokens
SKILL.md length
76 words
Files
1
Skills in repo
36
Repo updated
First seen
Licence
MIT

At a glance

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

  • Works in 3 steps: Identify the single most important… → Ask exactly one targeted question. Do… → Wait for the user's answer before…
  • The users request is ambiguous
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Under-specified

What it does

Clarify Ambiguous Requests is an agent skill from aiming-lab/MetaClaw. Use this skill when the user's request is ambiguous, under-specified, or could be interpreted in multiple ways. If proceeding with a wrong assumption would waste significant work, always ask exactly one focused clarifying question before doing anything.

Its SKILL.md is about 220 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Requirements gathering. The repository describes itself as: 🦞 Just talk to your agent — it learns and EVOLVES 🧬. The licence is MIT.

When your agent uses it

  • The users request is ambiguous
  • Under-specified
  • Could be interpreted in multiple ways

Example prompts

  • “/clarify-ambiguous-requests”

Workflow steps

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

  1. Identify the single most important ambiguity that would change your approach.
  2. Ask exactly one targeted question. Do not ask several at once.
  3. Wait for the user's answer before proceeding.

What it can do on your machine

Read from SKILL.md and the folder at commit 922caf3. 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

Clarify Ambiguous Requests loads about 216 tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 76 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~70
When it runs · the whole SKILL.md, loaded when a task matches
~216

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 aiming-lab/MetaClaw at commit 922caf3, republished under its MIT licence (© aiming-lab). 76 words, ~216 tokens.

Download SKILL.mdSave it as .claude/skills/clarify-ambiguous-requests/SKILL.md (or your agent's skills folder).
name
clarify-ambiguous-requests
description
Use this skill when the user's request is ambiguous, under-specified, or could be interpreted in multiple ways. If proceeding with a wrong assumption would waste significant work, always ask exactly one focused clarifying question before doing anything.
category
general

Clarify Ambiguous Requests

When the task or constraint is unclear, do not guess — ask.

Process:

  1. Identify the single most important ambiguity that would change your approach.
  2. Ask exactly one targeted question. Do not ask several at once.
  3. Wait for the user's answer before proceeding.

Example triggers: vague scope ("make it better"), missing required input (file path, API key, model name), conflicting constraints, unknown audience.

Anti-pattern: Proceeding with assumptions and delivering the wrong result.

© aiming-lab, 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 memory_data/skills/clarify-ambiguous-requests of aiming-lab/MetaClaw.

Open the folder on GitHubat commit 922caf3

Compare with similar skills

Clarify Ambiguous Requests 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.

Clarify Ambiguous Requests compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Clarify Ambiguous Requests this skillaiming-lab/MetaClaw3.5k—~216Automated safety check: PassMIT
SageMaker Deployment Plannerhuggingface/skills11k1 repos~2.1kAutomated safety check: PassApache-2.0
Agent BuildershareAI-lab/learn-claude-code78k6 repos~1.2kAutomated safety check: PassMIT
Using Superpowersfarm-fe/farm5.6k35 repos~1.4kAutomated safety check: PassMIT
Interview Meaddyosmani/agent-skills103k6 repos~3.8kAutomated safety check: PassMIT
Grillingpietheinstrengholt/rssmonster56432 repos~510Automated safety check: PassMIT

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Categories

Questions about Clarify Ambiguous Requests

What does Clarify Ambiguous Requests do?

A skill your agent uses when the user's request is ambiguous, under-specified, or could be interpreted in multiple ways. Clarify Ambiguous Requests is an agent skill from aiming-lab/MetaClaw. Use this skill when the user's request is ambiguous, under-specified, or could be interpreted in multiple ways.

When should I use Clarify Ambiguous Requests?

Clarify Ambiguous Requests fits situations like: the users request is ambiguous; under-specified; could be interpreted in multiple ways.

How do I install Clarify Ambiguous Requests in Claude Code?

Run `npx skills add aiming-lab/MetaClaw --skill clarify-ambiguous-requests -a claude-code`. Or copy the skill folder (memory_data/skills/clarify-ambiguous-requests in aiming-lab/MetaClaw) into .claude/skills/clarify-ambiguous-requests in your project. Claude Code loads it when a task matches its description.

How do I install Clarify Ambiguous Requests in Codex?

Run `npx skills add aiming-lab/MetaClaw --skill clarify-ambiguous-requests -a codex`. Or copy the skill folder (memory_data/skills/clarify-ambiguous-requests in aiming-lab/MetaClaw) into .agents/skills/clarify-ambiguous-requests in your project. Codex loads it when a task matches its description.

Can I use Clarify Ambiguous Requests 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 aiming-lab/MetaClaw --skill clarify-ambiguous-requests -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/clarify-ambiguous-requests, .gemini/skills/clarify-ambiguous-requests, .github/skills/clarify-ambiguous-requests and .opencode/skills/clarify-ambiguous-requests in your project.

What does Clarify Ambiguous Requests need to run?

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

Does Clarify Ambiguous Requests 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 Clarify Ambiguous Requests 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 Clarify Ambiguous Requests use?

Clarify Ambiguous Requests 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 Clarify Ambiguous Requests use?

About 216 tokens (SKILL.md is roughly 864 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 Clarify Ambiguous Requests?

Skills that share tags, products or a category with Clarify Ambiguous Requests: SageMaker Deployment Planner (huggingface/skills, 11k stars), Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Interview Me (addyosmani/agent-skills, 103k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Clarify Ambiguous Requests?

aiming-lab (a GitHub organization) maintains it in aiming-lab/MetaClaw, which has 3,458 GitHub stars. The repository holds 36 skills in this directory. The repository was last updated on June 7, 2026.

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