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varunk130varunk130/ai-workflow-playbooks/skills/requirement-extraction/SKILL.md

requirement-extraction

Skill2 starsChanged 6 months agoMITView on GitHub

Transform vague user inputs into structured, actionable requirements with explicit assumptions.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    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:

    Never assume silently: - If you fill in a gap, say so and ask for confirmation

    line 84
  2. Distinctive:

    Default conservatively: - When in doubt, choose the simpler interpretation and note it as an assumption

    line 88

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “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

Requirement Extraction

What This Skill Enables

An agent that can take ambiguous human input - "make the dashboard faster," "add authentication," "fix the search" - and systematically convert it into concrete, testable requirements before writing code. Agents without this skill build the wrong thing confidently.

Core Competencies

1. Signal Capture

Receive input without interpreting or filtering:

  • Record the exact words the user used
  • Note what was said AND what was left unsaid
  • Identify the stated goal vs the implied constraints
  • Distinguish between the problem description and a proposed solution

2. Ambiguity Detection

Flag vague language that needs clarification:

Vague InputWhat's MissingClarifying Question
"Make it faster"Faster by how much? Which operation?"What's the current latency, and what's the target?"
"Add user roles"Which roles? What permissions?"What actions should each role be able to perform?"
"Fix the bug"Which bug? How to reproduce?"Can you describe the steps to trigger this behavior?"
"It should be secure"Against what threats? What data?"What sensitive data does this handle, and who should access it?"
"Like Spotify does it"Which specific feature/behavior?"Can you describe the specific interaction you're referring to?"

3. Assumption Surfacing

Make every implicit assumption explicit before proceeding:

STATED: "Add a login page"

ASSUMPTIONS I'M MAKING:
- Email + password authentication (not OAuth/SSO)
- Single user type (no admin vs regular distinction)
- Session-based auth (not token-based)
- Standard form with email and password fields
- Redirect to home page after successful login
- Show error message for invalid credentials
- No "remember me" or "forgot password" in v1

RISKS IF WRONG:
- OAuth requirement would change the entire auth architecture
- Multiple user types affect the data model and routing

→ Please confirm or correct these before I proceed.

4. Requirement Structuring

Convert confirmed requirements into testable statements:

Format: WHEN [condition], the system MUST/SHOULD/MAY [behavior]

Examples:

  • WHEN a user submits valid credentials, the system MUST create a session and redirect to /dashboard
  • WHEN a user submits invalid credentials, the system MUST display "Invalid email or password" without revealing which field was wrong
  • WHEN a session expires, the system SHOULD redirect to /login with a "session expired" message
  • WHEN a logged-in user visits /login, the system MAY redirect to /dashboard

5. Scope Fencing

Define what's in and what's out:

IN SCOPE:
- Login form with email/password
- Session creation and validation
- Logout endpoint
- Protected route middleware

OUT OF SCOPE (for this iteration):
- Registration / signup
- Password reset
- OAuth / social login
- Multi-factor authentication
- Remember me functionality

Behavioral Rules

  1. Never assume silently - If you fill in a gap, say so and ask for confirmation
  2. Ask before building - One clarifying question saves hours of rework
  3. Separate problem from solution - "We need Redis" is a solution; "responses are slow" is the problem
  4. Quantify wherever possible - "Fast" means nothing; "<200ms p95 response time" is testable
  5. Default conservatively - When in doubt, choose the simpler interpretation and note it as an assumption

Failure Modes

FailureSymptomCorrection
Assuming requirementsBuilding features the user didn't ask forSurface every assumption explicitly
Gold-platingAdding OAuth when they asked for basic loginStick to stated scope; suggest enhancements separately
Not asking follow-upsImplementing based on first message aloneProbe for edge cases, error states, and constraints
Treating solutions as requirements"Use Redis" → implementing Redis without understanding the actual needAsk "what problem does this solve?" first

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