Clarify ambiguous plans and requirements through rigorous questioning and assumption testing.
This skill appears to be prompt-only, open source, and does not declare any secrets, remote endpoints, or execution capabilities, so the overall risk is low. The main caveat is limited evidence of community adoption and unknown maintenance status, so supply-chain trust should still be manually verified.
The material explicitly states that no keys or environment variables are required; as a prompt-only skill, there is no indicated credential collection, storage, or misuse path.
No remote endpoints or network connectivity are declared; based on the provided material, it does not involve sending user data to third-party services.
The objective check marks it as prompt-only, and the README only describes a questioning/clarification workflow, with no indication of spawning local processes, running scripts, or invoking system capabilities.
The material does not declare file I/O, database access, or other resource permissions; although it mentions 'checking the codebase,' the skill description itself shows no actual data-access mechanism or overbroad permission request.
The source points to an open-source GitHub repository associated with Microsoft, and the code is auditable, which is a positive factor; however, the license is undeclared, stars are 0, and maintenance status is unknown, so evidence of community validation and ongoing upkeep is limited. Verify repository ownership and recent commits before use.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "deep-clarification" skill from askskill: 1. Download https://raw.githubusercontent.com/microsoft/devsquad-copilot/main/.github/plugins/devsquad/skills/deep-clarification/SKILL.md 2. Save it as ~/.claude/skills/deep-clarification/SKILL.md 3. Reload skills and tell me it's ready
Deeply clarify this feature request: we want to build a team task board. Do not jump to solutions. First, act like a senior product manager and ask a sequence of critical questions that unpack target users, use cases, edge cases, permissions, failure modes, success metrics, and possible conflicts until major ambiguities are exposed.
A structured set of clarification questions and risks that helps complete the requirement definition.
Challenge this project plan: we aim to launch a new signup flow in two weeks. Question it across dependencies, resourcing, acceptance criteria, test coverage, rollback planning, analytics instrumentation, cross-team coordination, and timeline assumptions, and expand each potential failure branch.
A systematic critique of the plan, including failure paths and prerequisites that need strengthening.
Help me deeply probe this production issue: users report successful payment but the order status is not updated. Do not jump to conclusions. Use clarifying questions to map possible flows, challenge current assumptions, separate knowns from unknowns, and enumerate key branches as fully as possible.
A troubleshooting clarification framework listing investigation paths, key branches, and assumptions to verify.
Premature convergence is the root cause of underspecified features. When uncertainty is high, exhaustive exploration of the decision space produces better artifacts than bounded clarification rounds.
| Caller | Trigger |
|---|---|
devsquad.specify | Spec touches multiple bounded contexts, has high complexity rating, or user requests deep exploration |
devsquad.plan | High-impact design decisions with 2+ viable options and no clear winner |
devsquad.envision | Business context has competing objectives or unclear pain points |
debugging-recovery | Bug report is incomplete or ambiguous; need to build a complete reproduction |
| Any agent | User explicitly says "challenge this", "stress-test this", or "deep dive on requirements" |
Before asking the first question, map the branches:
For each decision point:
Before asking the user a question, check if the answer is already in the codebase:
Can the codebase answer this question?
YES → State the finding: "I found that [X]. Is this still current?"
NO → Ask the user
This reduces unnecessary questions and grounds the conversation in reality.
The clarification session ends when ANY of the following are true:
As decisions are made during the session, capture them immediately:
domain-glossary skill if available)Present a summary at the end using the reasoning skill format:
## Clarification Summary
### Decisions Made
| # | Decision | Justification | Confidence |
|---|----------|---------------|------------|
| 1 | [what was decided] | [why] | [High/Medium/Low] |
### Assumptions
- [assumption made during the session]
### Open Items
- [anything that could not be resolved and needs follow-up]
### Suggested Next Steps
- [ADR needed for X]
- [Spec update needed for Y]
Use these patterns to probe deeper:
| Technique | When to use | Example |
|---|---|---|
| Concrete scenario | Vague requirement | "Give me a specific example of when this would happen" |
| Edge case probe | Happy path only discussed | "What happens if [unusual input]? What about [concurrent access]?" |
| Contradiction surfacing | User states conflict with code/docs | "Your code does X, but you just said Y. Which is correct?" |
| Terminology sharpening | Overloaded or vague terms | "You said 'account'. Do you mean the billing entity or the login identity?" |
…
Systematically triage failures and fix broken builds or unexpected runtime issues.
Design and review software architecture diagrams for clearer, documentation-friendly visuals.
Create, switch, and verify Git branches before starting implementation work.
Initialize projects or verify and generate up-to-date SDD documentation templates.
Verify and create standard community and governance files for new projects.
Standardize formatting and writing style for project Markdown documentation.
Clarify ambiguous changes into testable acceptance criteria and implementation requirements.
Turn vague problems into structured intent specs for better product and engineering decisions.
Turn rough ideas into actionable designs through structured questioning and validation.
Capture and reuse codebase learnings to avoid repeating implementation and review mistakes.
Create debug tests and iterate to reliably reproduce and diagnose tricky bugs.
Create and maintain ADRs with checks, references, and planning support.