Refactor high-complexity React components in Dify frontend. Use when `pnpm analyze-component...
npx skills add dceoy/speckit-agent-skills --skill "speckit-baseline"
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# Description
Generate feature specifications by analyzing existing source code.
# SKILL.md
name: speckit-baseline
description: Generate feature specifications by analyzing existing source code.
Spec Kit Baseline Skill
When to Use
- You need a spec for existing or legacy code.
- You want to document a feature before refactoring.
- You inherited a codebase without written requirements.
Inputs
- A target path, file list, or glob pattern describing the code to analyze.
- Repo context with
.specify/scripts and templates.
If the target is missing or ambiguous, ask a focused question before continuing.
Goal
Generate a technology-agnostic spec for existing code, then create the feature branch/spec file using the standard Spec Kit templates.
Workflow
- Parse target input: Identify files, directories, or patterns to analyze.
- Accept file paths, glob patterns, or directory paths.
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If empty: stop and ask for a concrete target.
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Discover and read source files:
- Expand globs to a file list.
- Read file contents for analysis.
- Identify primary language(s) and frameworks.
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Map key file relationships and dependencies.
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Analyze code structure:
- Identify entry points and public interfaces.
- Extract function/method signatures and behaviors.
- Find data models and entities.
- Detect API endpoints and routes.
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Identify user-facing functionality.
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Generate a short name (2-4 words) from the analyzed code:
- Use action-noun format (e.g., "user-auth", "payment-processing").
- Base on primary functionality discovered.
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Preserve technical terms where meaningful.
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Create the feature branch and spec file:
- Find the highest existing feature number for this short name (branches/specs).
- Run
.specify/scripts/bash/create-new-feature.sh --jsonwith the calculated number and short name. - Read BRANCH_NAME, FEATURE_DIR, and SPEC_FILE paths from the script JSON output.
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For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
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Load the spec template from
.specify/templates/spec-template.md. -
Draft the specification using the template structure:
- User Stories: Infer from user-facing code paths and interactions.
- Acceptance Scenarios: Derive from validation logic, error handling, and tests.
- Functional Requirements: Extract from business rules and constraints.
- Key Entities: Identify from data models and schemas.
- Success Criteria: Infer from metrics, logging, or performance-related code.
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Assumptions: Document inferences made during analysis.
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Abstract implementation details:
- Convert technical patterns to user-focused requirements.
- Remove framework-specific terminology.
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Focus on WHAT the code does, not HOW it does it.
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Create spec quality checklist at
FEATURE_DIR/checklists/requirements.md. -
Report completion with:
- Branch name and spec file path.
- Summary of analyzed files.
- Key features discovered.
- Areas needing clarification or review.
Outputs
specs/<feature>/spec.mdspecs/<feature>/checklists/requirements.md
Key rules
- Focus on extracting WHAT and WHY from HOW.
- Abstract away implementation details in the generated spec.
- Document assumptions made during code analysis.
- Flag areas where code behavior is unclear.
- Preserve discovered business rules and constraints.
- Use
[NEEDS CLARIFICATION]for ambiguous code sections (max 3). - Generated specs should be validated by someone who knows the feature.
Examples
Code Pattern β Spec Requirement:
if (user.role === 'admin')β "System MUST restrict action to administrator users"password.length >= 8β "Passwords MUST be at least 8 characters"cache.set(key, value, 3600)β "System MUST cache results for improved performance"try { ... } catch (e) { notify(e) }β "System MUST notify users when errors occur"
Code Pattern β User Story:
- Login endpoint with OAuth β "As a user, I can sign in using my social account"
- Shopping cart logic β "As a customer, I can add items to my cart for later purchase"
- Report generation β "As an analyst, I can generate reports on system activity"
Next Steps
After generating spec.md:
- Clarify with domain experts using speckit-clarify.
- Plan modernization/refactoring with speckit-plan.
- Compare the generated spec with actual requirements to identify gaps.
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.