/clarify — Ambiguity Resolution Interview

SkillMedia

Turn fuzzy requirements, strategy questions, and half-formed ideas into clear output. Clarify is a pack that gives your AI three lenses for clarity: one turns vague requirements into concrete specs, one lays out strategy blind spots in a four-quadrant playbook, and one shifts between content and form to find leverage.

Use /clarify — Ambiguity Resolution Interview in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add /clarify — Ambiguity Resolution Interview and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use the /clarify skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

After adding Clarify, bring your AI something fuzzy, like a rough requirement or a strategy question, and ask it to apply the matching lens.

/clarify — Ambiguity Resolution InterviewStart free

What your AI can do with it

  • Turn vague requirements into concrete specs
  • Surface strategy blind spots in a four-quadrant playbook
  • Shift between content and form to find leverage
  • Apply the vague, unknown, and metamedium lenses when asked

What this skill tells your AI

The instructions your AI receives, as published by team-attention/hoyeon in skills/clarify/SKILL.md and read by Ahel’s review.

clarify is a pre-spec interview loop. It is closer to grill-me than specify: ask one precise question at a time, recommend an answer, record the answer, and keep going until material ambiguity is gone.

Do not implement, plan execution, or generate final requirements. The output is traceable context for the next workflow.

Runtime Surface

Claude Code

  • Use AskUserQuestion for mode selection and branching decisions.
  • Use Task(subagent_type="clarity-auditor") at audit boundaries.
  • Use Task(subagent_type="code-explorer") when a question can be answered from the codebase instead of asking the user.

Codex

  • Use Codex-native structured input when available; otherwise ask one concise plain-text question at a time.
  • Use hoyeon-clarity-auditor when native adapters are loaded.
  • Use hoyeon-code-explorer when codebase exploration can answer the question.
  • If native adapters are unavailable, perform the smallest direct read-only pass and record that fallback in qa-log.md.

Artifacts

Create a topic directory:

.hoyeon/clarify/<topic-slug>/
├── qa-log.md
└── clarity-summary.md

Read templates when writing artifacts:

  • templates/qa-log.md
  • templates/clarity-summary.md

Use a short kebab-case topic slug. If the current repo already has a Hoyeon spec directory for the same work, mention it in frontmatter as related_spec.

Modes

Infer the mode from the user's request. If uncertain, ask first.

ModeUse ForMain Question LensClear Enough When
requirementsProduct/feature intent before /specifyusers, goal, non-goals, success, scope, flows, edge cases, constraints$hoyeon-specify --context clarity-summary.md can start without guessing
designArchitecture or implementation direction before planningalternatives, boundaries, interfaces, data flow, trade-offs, risks, reversibility, verificationchosen direction, rejected alternatives, risks, and validation are explicit
domainTerms, concepts, and domain modelcanonical terms, definitions, relationships, edge cases, conflicts with docs/codekey terms have stable definitions and unresolved terms are listed
planWork sequencing before blueprint/executiondependencies, acceptance criteria, blocking decisions, validation, rollback, ownershipno blocking execution decision remains

Frontmatter fields:

mode: requirements | design | domain | plan
status: active | complete | paused
target_handoff: hoyeon-specify | hoyeon-blueprint | docs | none

Default mode is requirements.

Core Loop

  1. Mirror — State the current understanding in 2-4 bullets.
  2. Map ambiguity branches — List the active ambiguity branches in memory: vague terms, hidden assumptions, unresolved forks, missing criteria, external facts/code facts to verify.
  3. Ask one question — Ask exactly one question. Include:
    • why this question matters
    • your recommended answer
    • the trade-off behind the recommendation
  4. Explore instead of asking — If the answer is discoverable from the codebase or existing docs, explore first and ask only if evidence conflicts.
  5. Record immediately — Append to qa-log.md after every exchange.
  6. Classify — Mark the branch as resolved, ambiguous, assumption, or deferred.
  7. Audit — After 3-5 Q&A turns, after each major branch, and before summary, call the clarity auditor with the full qa-log.md.
  8. Continue or summarize — If auditor returns CONTINUE, ask the next suggested question. If SUFFICIENT, write clarity-summary.md.

Question Rules

  • Ask one question at a time.
  • Always provide a recommended answer unless the question is purely factual and must be discovered.
  • Prefer concrete options over open-ended prompts, but allow "Other".
  • Do not ask the user for facts that code/docs can answer.
  • Do not repeat a question. If the user does not know, choose a tentative default, mark it assumption or deferred, and move on.
  • Keep pressure on vague words: "fast", "simple", "good", "production-ready", "secure", "later", "nice UX", "admin", "sync", "done".

Mode-Specific Checks

requirements

Required branches:

  • primary user or actor
  • problem and desired outcome
  • explicit non-goals
  • success criteria
  • core happy path
  • important edge/failure states
  • constraints and risk modifiers

design

Required branches:

  • candidate approaches
  • chosen direction and why
  • rejected alternatives and why
  • boundaries and interfaces
  • state/data flow
  • failure modes
  • reversibility and migration
  • verification strategy

domain

Required branches:

  • canonical terms
  • term definitions
  • relationships between terms
  • overloaded or conflicting terms
  • boundary scenarios
  • code/doc contradictions, if a repo exists
  • doc target: CONTEXT.md, ADR, glossary, or no docs

Do not update CONTEXT.md or ADRs unless the user explicitly asks for docs-mode updates. By default, write candidates into clarity-summary.md.

plan

Required branches:

  • acceptance criteria
  • task dependencies
  • blocking decisions
  • validation evidence
  • rollback/recovery
  • ownership or handoff
  • out-of-scope work

Q&A Log Format

Append entries under ## Q&A:

### Q<N>: <short branch title>
- mode: <mode>
- branch: <branch id or name>
- status: resolved | ambiguous | assumption | deferred
- asked: <question>
- recommended: <recommended answer>
- answer: <user answer or discovered evidence>
- rationale: <why this resolves or does not resolve ambiguity>

Maintain ## Open Ambiguities as the current queue. Remove resolved items.

Auditor Contract

Send the auditor:

  • full qa-log.md
  • mode
  • current branch, if any
  • question count since last audit

Auditor returns:

  • CONTINUE with material ambiguities and suggested next question, or
  • SUFFICIENT with remaining non-blocking assumptions.

Only stop as complete when the auditor says SUFFICIENT or the user explicitly stops. If the user stops early, set status to paused.

Handoff

After SUFFICIENT, write clarity-summary.md and present one next action:

ModeDefault Handoff
requirements$hoyeon-specify --context .hoyeon/clarify/<topic>/clarity-summary.md "<topic>"
design$hoyeon-blueprint --context .hoyeon/clarify/<topic>/clarity-summary.md or ADR candidate
domaindocs/glossary update, if requested
plan$hoyeon-blueprint or direct execution planning

Do not run the handoff workflow unless the user asks.

Hard Rules

  1. No implementation.
  2. No final requirements.md, plan.json, or ADR unless explicitly requested.
  3. One question at a time.
  4. Recommended answer required for each user-facing question.
  5. Record each exchange before asking the next question.
  6. Continue until SUFFICIENT, paused, or explicit user stop.

Signals

GitHub stars
174
Forks
24
Last commit
May 2026
Hacker News mentions
5
Advanced
Item type
skill
Key
clarify-team-attention
Source
github.com/team-attention/hoyeon