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MithunWijayasiriMithunWijayasiri/dotclaude/skills/ask-first/SKILL.md

ask-first

Skill4 starsChanged 17 days agoMITView on GitHub

Ask the user clarifying questions before acting, instead of filling gaps with guesses. Use when starting to implement a feature, fix a bug, write or change tests, refactor, or plan any change where intent, scope, expected behavior, values, or done-criteria aren't fully stated. Also use mid-task when a new unknown surfaces. Skip for fully-specified asks, pure questions, and read-only lookups.

6 other projects use a version of this.

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The file

We split this skill into the rules it gives an agent

4 rules. 0 are common, 4 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 3 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    No type → infer from wording + code.

    line 15
  2. Distinctive:

    Ask one at a time: Wait for the answer before the next.

    line 22
  3. Distinctive:

    Check on top of the generic gaps.

    line 35
  4. Distinctive:

    Before editing, restate in a few lines: goal, scope in/out, approach, done-criteria.

    line 46

“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Ask First

Goal: shared understanding before code. User knows what I'll build; I know what they want. Guessed gap → wrong work baked in, costs a rework cycle.

Input

  • Shape: <type> - <what needs doing>, e.g. bug - after I turn off save history, I cannot turn it on. Often short or lazy — expected. Fill gaps by reading code, then asking.
  • Types: bug, feature, improvement, refactor, test, docs. Type picks the gap checklist below.
  • No type → infer from wording + code. Question needed → state inferred type in the first one so user confirms or corrects. Fully specified → proceed, no type confirmation.
  • Runs inside the target repo → ground every question in real files, names, current behavior.

Loop

  1. Read first. Explore relevant code, config, tickets, logs. Answerable from the code → read, don't ask. Verify claims against code; contradiction → surface it as a question.
  2. Find gaps. What's still unknown or ambiguous: goal, scope (in/out), expected behavior, exact values/labels/text, edge cases, done-criteria, constraints.
  3. Ask one at a time. Wait for the answer before the next. Order by dependency — answers that change later questions go first.
  4. Always recommend. Each question carries my proposed answer + why, so user confirms or corrects instead of composing from scratch. Never a blank question.
  5. Repeat until no gap would change what I build.

Question shape

  • Discrete choices → AskUserQuestion, recommended option first, labelled (Recommended).
  • Open-ended (a value, a label, what's on screen) → plain text question.
  • User can observe what I can't (live UI, env, runtime output) → ask what they see rather than trial-and-error runs.
  • Targeted and concrete: real paths, names, values. Not "any other requirements?".

Gaps by type

Check on top of the generic gaps. Ask only what code/logs don't answer.

  • Bug — expected vs actual, repro steps, env, when it started, what changed. Don't propose a root cause as fact — ask to confirm.
  • Feature — who uses it and when, entry point (UI, CLI, config), behavior incl. error/edge cases, scope out, existing pattern to follow, done-criteria.
  • Improvement — current behavior (from code) vs desired, what's wrong with current, what must stay unchanged.
  • Refactor — motivation, target shape, boundary (files/modules), how behavior-unchanged is verified (existing tests?).
  • Test — what's under test, level (unit/integration/e2e), cases incl. negative, test data/fixtures. Flaky → failure evidence.
  • Docs — audience (human/agent), file location, what's wrong or missing, source of truth.

Playback

Before editing, restate in a few lines: goal, scope in/out, approach, done-criteria. Get a yes. Correction → update and replay.

Mid-task

New unknown surfaces during implementation → stop and ask. Don't pick a default silently.

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