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Agent skill

Rich Elicitation

by sickn33 in sickn33/agentic-awesome-skills

Asks clarifying questions in multiple rounds before starting ambiguous tasks.

MITAuto-check passedAgent Workflows

Install Rich Elicitation

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill rich-elicitation -a claude-code

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

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills rich-elicitation --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/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/rich-elicitation .claude/skills/rich-elicitation && 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
rich-elicitation
GitHub stars
47k
Used in
1 other repo
Token cost
~1.9k tokens
SKILL.md length
856 words
Files
1
Skills in repo
1,497
Repo updated
First seen
Licence
MIT

At a glance

Asks clarifying questions in multiple rounds before starting ambiguous tasks.

  • Works in 5 steps: Run the Trigger Checklist → Ask Round 1 Questions → Re-run the Checklist → …
  • Tasks that involve Requirements gathering
  • SKILL.md covers Overview, When to Use This Skill, How It Works and Examples, plus 5 more sections
  • Calls npm

What it does

Rich Elicitation is an agent skill from sickn33/agentic-awesome-skills. Asks clarifying questions in multiple rounds before starting ambiguous tasks. Fires when 2+ task dimensions each have 3+ viable answers.

Its SKILL.md is about 1.9k 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 Agent Workflows, covering Requirements gathering. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

  • Tasks that involve Requirements gathering

Example prompts

  • “/rich-elicitation”

Workflow steps

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

  1. Run the Trigger Checklist
  2. Ask Round 1 Questions
  3. Re-run the Checklist
  4. Run Follow-up Rounds (if needed)
  5. Proceed

What it can do on your machine

Read from SKILL.md and the folder at commit b84d35a. 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

    Shell commands in SKILL.md call:

    • npm

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

  • Network

    No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.

    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

Rich Elicitation loads about 1.9k tokens when it runs. Until then it costs about 38 tokens; SKILL.md has 856 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~38
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

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 sickn33/agentic-awesome-skills at commit b84d35a, republished under its MIT licence (© sickn33). 856 words, ~1,925 tokens.

Download SKILL.mdSave it as .claude/skills/rich-elicitation/SKILL.md (or your agent's skills folder).
name
rich-elicitation
description
Asks clarifying questions in multiple rounds before starting ambiguous tasks. Fires when 2+ task dimensions each have 3+ viable answers.
category
productivity
risk
none
source
self
source_type
self
date_added
2026-05-07
author
abubakar
tags
elicitation, clarifying-questions, ambiguity, multi-round, prompt-engineering
tools
antigravity

Rich Elicitation Skill

Overview

This skill governs how Antigravity resolves task ambiguity before starting work. When a user's request has too many unanswered dimensions — each with several reasonable answers — Antigravity asks targeted clarifying questions across multiple rounds rather than silently picking defaults.

The goal is a correct first draft, not a generic answer that requires three revision cycles. Rounds are capped at three; anything still unclear after Round 3 gets a stated assumption and Antigravity proceeds.

When to Use This Skill

  • Use when a request has 2 or more dimensions that are ambiguous and each has 3+ viable options
  • Use when the user's likely intent is unclear across scope, audience, tone, format, or strategy
  • Use when an early answer would meaningfully change the structure or direction of the output
  • Use when working on writing, planning, design, recommendations, or creative tasks with open-ended scope
  • Use when a Round 1 answer unlocks a new set of meaningful choices that need resolving before proceeding

Do not trigger for:

  • Simple factual lookups or math
  • Clearly scoped requests with a single obvious interpretation
  • Minor unknowns where a safe default exists

How It Works

Step 1: Run the Trigger Checklist

Before starting any task, mentally check how many of these apply:

SignalAction
Multiple valid output formatsAsk about format
Audience is unknownAsk about audience
Tone is ambiguousAsk about tone
Scope could be narrow or broadAsk about depth/length
Technical vs. simple treatment unclearAsk about technical level
Multiple strategic directions existAsk which direction
User's constraints are unknownAsk about constraints

If 2+ rows apply → trigger this skill.

Step 2: Ask Round 1 Questions

Ask up to 3 questions using ask_user_input_v0. Group related questions in a single call. Lead with 1–2 sentences explaining why you're asking. Mark one option per question as (Recommended).

Step 3: Re-run the Checklist

After Round 1 answers, re-run the checklist on what's still unresolved. If 2+ rows still apply, run Round 2. Otherwise, proceed.

Step 4: Run Follow-up Rounds (if needed)
RoundPurposeMax questions
Round 1Blocking questions — shape the entire output3
Round 2Follow-ups unlocked by Round 1 answers3
Round 3Final details — use sparingly2

Transition between rounds naturally. Don't announce "Round 2" mechanically. Use phrasing like:

"Got it — that helps a lot. One more thing before I start:"

Step 5: Proceed

After Round 3 (or earlier, if enough context exists), state any remaining assumptions briefly and begin the task.

Examples

Example 1: Multi-Round — Investor Pitch Deck

User: "Help me create a presentation for my project."

Round 1 — Three blocking questions:

Framing: "This could go a lot of different ways. Quick questions before I start:"

Q1: Who is the audience?
  - Internal team / colleagues
  - External clients or partners
  - Investors or stakeholders (Recommended)
  - General / public audience

Q2: What's the primary goal?
  - Inform and update
  - Persuade and drive a decision (Recommended)
  - Teach or explain a concept
  - Pitch and raise funding

Q3: How much content do you already have?
  - Starting from scratch
  - Rough notes or an outline (Recommended)
  - Full draft — just needs polish
  - Previous version to update

User answers: Investors | Pitch | Rough notes → Round 2 is warranted.

Round 2 — Unlocked by Round 1:

Framing: "Perfect — investor pitch it is. A couple more things:"

Q1: What stage is this raise?
  - Pre-seed / idea stage
  - Seed round (Recommended)
  - Series A or later
  - Strategic partnership / grant

Q2: How long should the deck be?
  - Short and punchy, 8–10 slides (Recommended)
  - Standard, 12–15 slides
  - Comprehensive, 20+ slides

No Round 3 needed — proceed.

Example 2: Single-Round — Business Email

User: "Write a business email to follow up on a proposal."

Round 1 only:

Framing: "Two quick questions to nail the tone:"

Q1: What tone should this email strike?
  - Formal and professional (Recommended)
  - Friendly but direct
  - Urgent and firm
  - Warm and relationship-focused

Q2: What's the primary goal?
  - Request action / get a response (Recommended)
  - Share information only
  - Repair or maintain the relationship
  - Negotiate or push back

Enough context. No Round 2 needed.

Show full SKILL.md (382 more words)Show less

Best Practices

  • ✅ Always mark one option per question as (Recommended)
  • ✅ Lead with a 1–2 sentence framing before the question widget
  • ✅ Group up to 3 related questions in a single ask_user_input_v0 call
  • ✅ Re-evaluate after each round — stop as soon as you have enough context
  • ✅ Use single_select for mutually exclusive choices, multi_select when combinations are valid
  • ✅ State remaining assumptions explicitly before proceeding after Round 3
  • ❌ Don't ask 6 separate question calls when 2 grouped calls would do
  • ❌ Don't mark two options as Recommended in the same question
  • ❌ Don't use vague option labels like "Other" or "It depends" without elaborating
  • ❌ Don't mechanically label rounds in the UI ("Round 1:", "Round 2:")
  • ❌ Don't run a follow-up round for minor details that have safe defaults

Limitations

  • This skill does not validate whether the user's answers are internally consistent — it trusts them as given.
  • Round structure is a guideline, not a rigid contract; judgment is required on when to stop.
  • Works best with ask_user_input_v0 — in environments without that tool, question quality may degrade.
  • Does not handle tasks where ambiguity can only be resolved by fetching external information (e.g., reading a file the user hasn't uploaded).
  • Not designed for real-time or high-latency-sensitive workflows where any question overhead is unacceptable.

Security & Safety Notes

This skill is pure reasoning — it issues no shell commands, reads no files, makes no network requests, and mutates no state. Risk level is none.

No npm run security:docs review is required for this skill.

Common Pitfalls

  • Problem: Antigravity asks one good question, gets an answer, then proceeds without checking if new unknowns emerged. Solution: Always re-run the trigger checklist mentally after each round before deciding to proceed.

  • Problem: All options in a question look equally valid so Antigravity marks none as Recommended. Solution: Pick the option that works for most users or is lowest-risk and mark it. "No preference" is rarely true.

  • Problem: Antigravity runs 4+ rounds trying to eliminate every unknown. Solution: Hard cap at 3 rounds. After Round 3, state assumptions and proceed.

  • Problem: Round 2 questions cover the same category as Round 1 (e.g., tone again). Solution: Each round should unlock new dimensions, not re-ask resolved ones.

  • @ask-user-questions — Single-round elicitation with recommended options. Use that skill for simpler tasks; use rich-elicitation when answers to early questions open up new meaningful choices.

© sickn33, 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/rich-elicitation of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit b84d35a

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 9, 2026.

Compare with similar skills

Rich Elicitation 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.

Rich Elicitation compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Rich Elicitation this skillsickn33/agentic-awesome-skills47k1 repos~1.9kAutomated safety check: PassMIT
Using Superpowersfarm-fe/farm5.6k36 repos~1.4kAutomated safety check: PassMIT
Interview Meaddyosmani/agent-skills105k6 repos~3.8kAutomated safety check: PassMIT
Brainstormingobra/superpowers297k1 repos~2.5kAutomated safety check: PassMIT
Grillingpietheinstrengholt/rssmonster56431 repos~510Automated safety check: PassMIT
Agentic Workflow Designerdotnet/Open-XML-SDK4.6k2 repos~3.5kAutomated safety check: PassMIT

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Categories

Questions about Rich Elicitation

What does Rich Elicitation do?

Asks clarifying questions in multiple rounds before starting ambiguous tasks. Rich Elicitation is an agent skill from sickn33/agentic-awesome-skills. Asks clarifying questions in multiple rounds before starting ambiguous tasks.

When should I use Rich Elicitation?

Rich Elicitation fits situations like: tasks that involve Requirements gathering.

How do I install Rich Elicitation in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill rich-elicitation -a claude-code`. Or copy the skill folder (skills/rich-elicitation in sickn33/agentic-awesome-skills) into .claude/skills/rich-elicitation in your project. Claude Code loads it when a task matches its description.

How do I install Rich Elicitation in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill rich-elicitation -a codex`. Or copy the skill folder (skills/rich-elicitation in sickn33/agentic-awesome-skills) into .agents/skills/rich-elicitation in your project. Codex loads it when a task matches its description.

Can I use Rich Elicitation 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 sickn33/agentic-awesome-skills --skill rich-elicitation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/rich-elicitation, .gemini/skills/rich-elicitation, .github/skills/rich-elicitation and .opencode/skills/rich-elicitation in your project.

What does Rich Elicitation need to run?

Going by SKILL.md and its folder, Rich Elicitation needs the command-line tools its instructions call (npm).

Does Rich Elicitation access the network?

SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Rich Elicitation 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 Rich Elicitation use?

Rich Elicitation 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 Rich Elicitation use?

About 1.9k tokens (SKILL.md is roughly 7.7k 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 Rich Elicitation?

Skills that share tags, products or a category with Rich Elicitation: Using Superpowers (farm-fe/farm, 5.6k stars), Interview Me (addyosmani/agent-skills, 105k stars), Brainstorming (obra/superpowers, 297k stars) and Grilling (pietheinstrengholt/rssmonster, 564 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Rich Elicitation?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,405 GitHub stars. The repository holds 1,497 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.