# Scoping

> Scoping

- Skill: `lantisprime/scoping` (Agent Skill)
- Install (CLI): `npx skillmds@latest add lantisprime/scoping`
- Raw SKILL.md: https://api.skillmd.com/api/skills/lantisprime/scoping/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: lantisprime (https://skillmd.com/u/lantisprime)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/lantisprime/scoping

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# Scoping

Turn a vague ask into something a plan can be written against.

## When to trigger

Proactively, whenever the request is missing any of:

- Trigger condition (when does this happen / when should it happen?)
- Expected behavior
- Actual behavior (for bugs)
- Specific user flow or entry point
- Environment (dev / staging / prod)
- Measurable success criteria

Don't guess. Claude's guesses become scope creep later.

## The clarification checklist

Ask only the questions whose answers aren't already clear. Typical set:

1. **What is the user trying to do?** (business outcome, not technical symptom)
2. **What happens now?** (current behavior, reproduction steps if a bug)
3. **What should happen?** (target behavior with acceptance criteria)
4. **Which users or flows?** (scope of impact)
5. **Which environment?** (local, staging, prod)
6. **How will we know it's done?** (test or observation)
7. **What's explicitly out of scope?** (prevents "while you're at it")

## Output

Append the clarified scope to the plan artifact under a **Clarifications** section. If no plan exists yet, create one via the `plan` skill using the clarified inputs.

## What this skill must NOT do

- Do not fill in ambiguous fields with plausible-sounding defaults.
- Do not ask every question every time — only the ones not already answered.
- Do not proceed to Plan until the blocking ambiguities are resolved.

## References

- `skills/plan/SKILL.md`
- `templates/plan.md`