eko24ive/pi-ask/ask-user

Claude Code and agent skill by eko24ive/pi-ask

Trust tier 3
  • community
Source check pending

Checking that the SKILL.md file is still in the repository.

Use ask_user as a decision, research, and requirements gate before ambiguous or high-stakes choices.

Install

npx vskill@latest install eko24ive/pi-ask/ask-user

SKILL.md

Ask User decision/research gate

Use this skill to force explicit user alignment before consequential decisions, preference-sensitive planning, research scoping, or requirements gathering.

This skill is for decision control, research scoping, requirements gathering, and preference-sensitive planning, not general chat.

Trigger

Classify the next step as one of:

  • high_stakes
  • ambiguous
  • both
  • clear

Use ask_user when the next step is ambiguous, preference-sensitive, or high-stakes and the user has not already made the decision explicitly.

Use ask_user for any domain where user input changes the plan, recommendation, research direction, output format, criteria, constraints, or next action.

Also use ask_user when the user asks to gather requirements, interview them, ask questions, scope research, plan work, compare options, or answer a set of open product/design/architecture/research questions. Do not respond with a plain-text questionnaire unless the user explicitly asks for a checklist or written questionnaire.

Treat as high_stakes when the next step changes:
  • architecture, schema, API contract, deployment, or security posture
  • production-facing behavior in a costly-to-undo way
  • large refactors, migrations, or destructive edits
  • legal, financial, medical, career, hiring, vendor, purchasing, travel, or other costly-to-reverse decisions
  • public-facing claims, sensitive communications, or consequential recommendations
Treat as ambiguous when:
  • requirements, goals, constraints, evaluation criteria, or success criteria are missing/conflicting
  • multiple valid options exist and the trade-off is preference-sensitive
  • research scope, audience, budget, timeline, risk tolerance, or output format is unclear
  • you would otherwise make a material assumption

Handshake (required)

  1. Gather evidence first from code/docs/tools.
  2. Summarize neutral context (current state, constraints, trade-offs, recommendation).
  3. Ask one focused ask_user decision question, or bundle 2-5 closely related questions when the user is explicitly in requirement-gathering/interview mode.
  4. Restate the user decision and proceed explicitly with it.
  5. Re-open only for materially new ambiguity.

Question spew prevention

Before sending any assistant response that contains 2+ substantive questions for the user, stop and decide whether those questions should be interactive.

Use ask_user instead of prose when:

  • the questions are meant to collect requirements, goals, constraints, preferences, scope, priorities, criteria, or missing context
  • answers will materially change the next artifact, recommendation, research direction, plan, implementation, architecture, schema, UX, stack choice, or decision criteria
  • the user previously corrected you with phrases like "ask those questions", "ask interactively", or "use ask_user"

Plain-text questions are acceptable only when:

  • the user asked for a written checklist/list of open questions
  • the questions are rhetorical or purely explanatory
  • there is exactly one small factual clarification and an interactive flow would be heavier than needed

If there are too many questions, group them into the smallest coherent ask_user batches and ask the highest-impact batch first.

Question budget and escalation

  • Max 1 ask_user call per decision boundary in normal cases.
  • Max 2 calls for the same boundary if first answer is unclear/cancelled.
  • Never re-ask the same trade-off without new evidence.

Attempt 2 (only if needed) must be narrower and include:

  • Proceed with recommended option
  • Choose another option
  • Stop for now

After attempt 2:

  • for high_stakes or both: stop as blocked until explicit decision
  • for ambiguous only: if user delegates ("your call"), proceed with the most reversible default and state assumptions

ask_user payload quality

  • Ask one concrete decision at a time.
  • Provide clear, distinct options. Do not add filler options.
  • Choose question type from semantics: single means one answer is expected, multi means multiple answers could reasonably be selected, and preview means options need preview-pane detail with non-empty preview text.
  • Avoid defaulting mechanically; infer from whether options are mutually exclusive, can coexist, or need preview-pane detail.
  • Keep option labels short and outcome-oriented.
  • Include trade-off descriptions when non-obvious.
  • For research/planning, ask about goals, constraints, evaluation criteria, audience, budget, timeline, risk tolerance, and desired output only when they materially affect the result.
  • Prefer non-preview questions when a free-form answer may be useful, since those include an internal Type your own option.

Guardrails

  • Do not ask before reading available context.
  • Do not use for trivial formatting/style micro-decisions.
  • Do not continue implementation after unclear high-stakes answers.

Conflict rule

If this skill conflicts with implementation behavior or tests, the project contract wins:

  1. docs/contract.md
  2. tests/*.test.ts
  3. this skill

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
52
Repository forks
22
7-day trend score
20

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

  • Claude Code
  • Cursor
  • GitHub Copilot
  • Windsurf
  • Codex
  • Gemini CLI
  • Cline
  • Amp
  • Roo Code
  • Goose
  • Continue
  • Kilo Code
  • Junie
  • Trae
  • OpenHands
  • Qwen Code
  • AI Agent
  • Tabnine Chat
  • Sourcegraph Cody
  • Amazon Q
  • Firebase Genkit
  • Sweep
  • Devin
  • Phind
  • Mentat
  • Claude Desktop
  • Aider
  • GPT Pilot
  • Plandex
  • bolt.new
  • v0
  • Replit Agent
  • Anse
  • TypingMind
  • BetterChatGPT
  • LibreChat
  • Warp AI
  • Pieces
  • Fig AI
Embed badge
vskill VERIFIED badge
[![vskill VERIFIED](https://verified-skill.com/api/v1/skills/eko24ive/pi-ask/ask-user/badge)](https://verified-skill.com/skills/eko24ive/pi-ask/ask-user)

Something wrong with this skill or its page? Tell us.