Unnamed Skill
Comprehensive feature artifact analysis for loading and understanding complete feature context. Use when needing to: (1) Load all feature documentation before implementation, (2) Build mental model of feature requirements and architecture, (3) Prepare context for downstream operations like checklist generation or task execution, (4) Analyze feature completeness and artifact availability. Triggers on: analyze feature, load feature context, prepare feature, check feature prerequisites, understand feature scope.
$ Installieren
git clone https://github.com/petbrains/mvp-builder /tmp/mvp-builder && cp -r /tmp/mvp-builder/.claude/skills/feature-analyzer ~/.claude/skills/mvp-builder// tip: Run this command in your terminal to install the skill
name: feature-analyzer description: Comprehensive feature artifact analysis for loading and understanding complete feature context. Use when needing to: (1) Load all feature documentation before implementation, (2) Build mental model of feature requirements and architecture, (3) Prepare context for downstream operations like checklist generation or task execution, (4) Analyze feature completeness and artifact availability. Triggers on: analyze feature, load feature context, prepare feature, check feature prerequisites, understand feature scope. allowed-tools: Read, Write, Bash (*)
Feature Analyzer
Load and analyze all feature artifacts to build comprehensive understanding for downstream operations.
Workflow Overview
- Scan - Check artifact availability
- Load - Read all feature documents
- Build - Construct complete mental model
- Confirm - Ready for operations
Step 1: Scan Feature Directory
Run prerequisites scanner to identify available artifacts:
.claude/skills/feature-analyzer/scripts/check-prerequisites.sh <feature-directory>
Scanner checks for:
- Core artifacts: spec.md, ux.md, plan.md, tasks.md
- Data artifacts: data-model.md, contracts/
- Support artifacts: research.md, setup.md
Outputs JSON with AVAILABLE and MISSING arrays. Exits with error if core files missing.
Step 2: Load Feature Artifacts
Read all available artifacts in priority order:
Core Documents (Required)
spec.md- Requirements (FR-XXX), user stories, acceptance criteriaux.md- User flows, interactions, states, errorsplan.md- Architecture, components, technology stacktasks.md- Implementation phases, TDD cycles, execution order
Data & Contracts
data-model.md- Entities, validation, state machinescontracts/- APIs, messages, schemas- openapi.yaml
- contracts.md
Supporting Documents
research.md- Technical decisions, rationalesetup.md- Environment, dependencies, commands
Step 3: Build Mental Model
Extract and internalize from each artifact:
From spec.md:
- Main journey and goal
- All requirements with IDs
- Test scenarios
- Edge cases and constraints
From ux.md:
- Complete flow with triggers
- States and transitions
- Error handling patterns
From plan.md:
- Code structure (A/B/C/D patterns)
- Requirement→Component mapping
- Technical constraints
From tasks.md:
- Implementation sequence
- TDD coverage targets
- File creation paths
- Dependencies
From data-model.md:
- Field definitions and rules
- Constants and limits
- Entity relationships
From contracts:
- Endpoint specifications
- Message formats
- Protocol definitions
Step 4: Confirm Readiness
Output minimal confirmation:
✅ Feature context loaded: [feature-name]
Available: [list of loaded artifacts]
Ready for: implementation | checklist | queries
Error Handling
- Missing core files: Stop and report specific missing file
- Malformed content: Report file and parsing error
- Access denied: Report permission issue
Usage Notes
This skill prepares context for:
- Task execution (implementation from tasks.md)
- Checklist generation (requirements validation)
- Architecture queries
- Technical guidance
Context remains in memory for entire conversation.
Repository
