Agent skill
auto-spec
Autonomously create and implement a complete spec workflow with multi-agent collaboration, bypassing manual review steps through intelligent consensus-building
Install this agent skill to your Project
npx add-skill https://github.com/Uniswap/ai-toolkit/tree/next/packages/plugins/spec-workflow/skills/auto-spec
SKILL.md
Auto-Spec Command
FULLY AUTONOMOUS spec-driven development that NEVER prompts the user for review. Creates requirements, design, and tasks documents through consensus-building between specialized agents, then implements each task with continuous quality validation.
Workflow Overview
This command automates the entire spec workflow WITHOUT ANY USER INTERACTION:
- Requirements Generation - With multi-agent review (NOT user review)
- Design Creation - With architectural consensus (NOT user approval)
- Task Planning - With implementation strategy validation (NOT user validation)
- Task Implementation - With continuous quality checks (NOT user checks)
- Final Deliverable - Comprehensive summary and test documentation
CRITICAL: This command is designed to run COMPLETELY AUTONOMOUSLY. It will:
- NEVER prompt you for review during the workflow
- NEVER wait for approval at any stage
- ALWAYS use agent collaboration instead of user review
- ONLY return to you with the final deliverable
Inputs
Accept natural language description and extract:
feature: The feature or task description to implementskip_final_review: Optional flag to skip final user review (default: false)project_path: Optional project path (defaults to current working directory)spec_name: Optional spec name (auto-generated from feature if not provided)steering_context: Optional flag to load steering documents (default: true)parallel_execution: Optional flag for parallel task execution (default: true)quality_threshold: Quality threshold for agent consensus (default: 0.8)
Examples:
/auto-spec user authentication with OAuth2 and JWT tokens/auto-spec add real-time notifications using WebSockets --skip-final-review/auto-spec implement event-driven order processing system
Task
Execute autonomous spec-driven development workflow with multi-agent collaboration.
CRITICAL INSTRUCTIONS FOR AUTONOMOUS EXECUTION
- NEVER prompt the user for review at ANY point during the workflow
- NEVER use
mcp__spec-workflow__request-approvaltool - NEVER wait for user interaction or approval
- ALWAYS spawn sub-agents instead of requesting user review
- ALWAYS continue autonomously through ALL phases
Phase 1: Context Preparation
-
Load Project Context
- Use
mcp__spec-workflow__get-steering-contextif steering documents exist - Use
mcp__spec-workflow__get-template-contextto understand document formats - Analyze existing codebase patterns and architecture
- Use
-
Feature Analysis
- Spawn planner-agent agent to analyze feature requirements
- Identify complexity level and required capabilities
Phase 2: Requirements Document Creation
-
Initial Requirements Generation
- Use
mcp__spec-workflow__spec-workflow-guideto understand workflow - Create initial requirements using
mcp__spec-workflow__create-spec-doc
- Use
-
Multi-Agent Requirements Review (INSTEAD of user review)
- Spawn plan-reviewer-agent to validate architectural alignment
- Spawn security-analyzer-agent to identify security requirements
- Spawn performance-analyzer-agent to define performance criteria
- Iterate until consensus reached
Phase 3: Design Document Creation
-
Initial Design Generation
- Create design document based on finalized requirements
- Include architectural decisions, data models, and interfaces
-
Multi-Agent Design Review (INSTEAD of user review)
- Spawn plan-reviewer-agent for architectural patterns validation
- Spawn refactorer-agent for implementation feasibility
- Spawn test-writer-agent for testability assessment
Phase 4: Task Planning
-
Task Decomposition
- Use
mcp__spec-workflow__create-spec-docto create tasks document - Break down implementation into granular, testable tasks
- Use
-
Task Validation (INSTEAD of user review)
- Spawn planner-agent to validate task completeness
- Spawn code-explainer-agent to assess task dependencies
Phase 5: Implementation Execution
For each task in the implementation plan:
-
Task Implementation
- Mark task as in-progress using
mcp__spec-workflow__manage-tasks - Spawn appropriate specialized agent(s) for implementation
- Mark task as in-progress using
-
Quality Validation Loop (INSTEAD of user review)
- Spawn refactorer-agent to review implementation
- Spawn test-writer-agent to verify test coverage
- Iterate until quality threshold met
-
Task Completion
- Mark task as completed
- Move to next task (parallel execution if enabled)
Phase 6: Final Quality Assurance
- Integration Testing - Spawn test-writer-agent to create integration tests
- Performance Validation - Spawn performance-analyzer-agent to assess performance
- Security Audit - Spawn security-analyzer-agent for final security review
Phase 7: Deliverable Generation
Create comprehensive summary including:
- Key architectural decisions and rationale
- Trade-offs made during implementation
- Technical debt incurred (if any)
- Test documentation and coverage report
Output
Structured Response Format
# Autonomous Spec Implementation: [Feature Name]
## Implementation Summary
- Spec Name: [spec-name]
- Total Tasks: [X completed / Y total]
- Execution Time: [duration]
- Quality Score: [X/10]
## Key Decisions and Rationale
[List major architectural choices with reasoning]
## Testing Guide
- Unit Tests: [X% coverage]
- Integration Tests: [Y scenarios]
## Next Steps
[Recommended follow-up actions]
Usage Examples
/auto-spec add user profile picture upload with image resizing
/auto-spec implement event-driven microservices architecture for order processing
/auto-spec refactor authentication system --quality-threshold=0.9
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
review-plan
Review implementation plans for completeness and feasibility. Use when user says "review this plan before I start", "is this implementation plan complete", "check if this plan aligns with our patterns", "give me feedback on my implementation strategy", or "validate this plan before we execute it".
plan-implementation
Create implementation plans for features and changes. Use when user says "plan how to implement user authentication", "how should I add dark mode to the app", "what's the best way to refactor the database layer", "create a plan for migrating to the new API", or "I need to implement [feature] - help me plan it out".
execute-plan
Execute implementation plans step-by-step. Use when user says "execute the plan", "implement the plan we created", "start building based on the plan", "go ahead and implement it", "proceed with the implementation", "execute as a stack", "create a PR stack while implementing", "implement with one PR per step", or references a plan file and wants to begin coding.
generate-commit-message
Generate well-structured git commit messages. Use when user says "generate commit message", "write a commit", "what should my commit message be", "create commit message for these changes", or needs help crafting conventional commit messages.
plan-swarm
Refine plans through multi-agent expert discussion. Use when user says "get multiple expert opinions on this plan", "I want different perspectives on this approach", "have the agents discuss this strategy", "refine the plan through collaborative review", or "what would different specialists think about this design".
create-pr
Create or update pull requests with conventional commits. Use when user says "create a PR for these changes", "submit this for review", "open a pull request", "push these changes and create a PR", "I'm ready to submit this work", or "create PR and link to issue
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