spec-driven-development
Spec-Driven Development (SDD) methodology based on GitHub's SpecKit. Use for structured AI-assisted development with constitutional governance, phased workflows, and multi-agent coordination. Implements 7-phase process from constitution to implementation.
What this skill does
# Spec-Driven Development (SDD) This skill implements GitHub's SpecKit methodology for structured, AI-assisted software development. SpecKit transforms specifications into executable artifacts through a systematic, phase-based approach with built-in quality gates and multi-agent coordination. ## Core Philosophy **"Specifications become executable, directly generating working implementations rather than just guiding them."** ## When to Use This Skill - Starting new projects that require structured development - Coordinating multiple AI agents or developers on complex features - Ensuring consistent quality through constitutional governance - Breaking down complex features into manageable, parallel work - Preventing premature implementation before clear specifications - Enterprise projects with strict governance requirements - Teams needing real-time visibility across multiple features ## The 7-Phase Workflow ### Phase 0: Project Initialization **Purpose:** Create project structure and configure development environment **Artifacts:** - `.specify/` directory structure - Git repository - Automation scripts - Templates **Key Actions:** - Set up directory structure - Initialize version control - Configure AI agent preferences - Generate script variants (bash/powershell) ### Phase 1: Constitution **Purpose:** Establish project governance and development principles **Artifact:** `memory/constitution.md` **Core Principles:** 1. **Library-First Principle:** Every feature starts as a standalone library 2. **CLI Interface Mandate:** All libraries must have text-based interfaces 3. **Test-First Imperative:** Tests must precede implementation 4. **Simplicity and Anti-Abstraction:** Minimize complexity 5. **Integration-First Testing:** Prioritize realistic testing environments **Versioning:** Semantic versioning (MAJOR.MINOR.PATCH) - MAJOR: Backward-incompatible governance changes - MINOR: New principles or material expansions - PATCH: Minor clarifications or refinements **Orchestration:** Interactive principle definition with validation across all artifacts ### Phase 2: Specification **Purpose:** Create detailed feature specifications focused on WHAT and WHY, not HOW **Artifact:** `specs/[feature]/spec.md` **Required Sections:** - Feature branch name (2-4 words) - User scenarios (P1, P2, P3 prioritized) - Acceptance scenarios (Given/When/Then format) - Edge cases - Functional requirements (FR-XXX) - Key entities - Success criteria (measurable, technology-agnostic) **Key Constraints:** - Focus on business value, not implementation - Write for stakeholders, not developers - Maximum 3 clarification markers for critical unknowns - Each user story must be independently testable **Quality Gates:** - Content quality validation - Requirement completeness check - Feature readiness assessment - Success criteria measurability ### Phase 3: Clarification **Purpose:** Systematically identify and resolve ambiguities in specifications **Artifact:** Updates `specs/[feature]/spec.md` **Clarification Dimensions:** - Functional scope - Data model - User experience (UX) - Non-functional attributes (performance, security, etc.) - Integration points **Key Constraints:** - Maximum 5 questions per session - Multiple-choice or short-answer format - Focus on high-impact, implementation-critical uncertainties - One question at a time for iterative refinement **Orchestration:** Interactive questioning workflow with incremental spec updates after each answer ### Phase 4: Planning **Purpose:** Create technical implementation strategy and resolve technical unknowns **Sub-Phases:** **Phase 0 - Research:** - Identify and research technical unknowns - Output: `research.md` with all uncertainties resolved - **Gate:** ERROR on unresolved clarifications **Phase 1 - Design:** - Create data models and API contracts - Outputs: `data-model.md`, contract schemas, agent-specific context **Artifacts:** - `specs/[feature]/plan.md` - `specs/[feature]/research.md` - `specs/[feature]/data-model.md` - `specs/[feature]/contracts/` **Plan Sections:** - Feature summary - Technical context (language, dependencies, platform) - Project structure - Repository layout - Complexity tracking for non-standard approaches ### Phase 5: Analysis **Purpose:** Validate cross-artifact consistency before implementation **Artifacts Analyzed:** - `specs/[feature]/spec.md` - `specs/[feature]/plan.md` - `specs/[feature]/tasks.md` **Detection Passes:** 1. Duplications 2. Ambiguities 3. Underspecified items 4. Constitution conflicts **Output:** Analysis report with severity-ranked findings (max 50 high-signal issues) **Key Constraints:** - Read-only operation (cannot modify files) - Must run after task breakdown - Prioritizes constitution principles ### Phase 6: Task Breakdown **Purpose:** Generate actionable, dependency-ordered task list from plan **Artifact:** `specs/[feature]/tasks.md` **Task Structure:** - Checkbox for completion tracking - Sequential Task ID - Optional parallelization marker (`||`) - Story label (P1, P2, P3 when applicable) - Precise file path - Clear description **Phase Structure:** 1. **Phase 1:** Project Setup 2. **Phase 2:** Foundational Prerequisites (BLOCKING - must complete before user stories) 3. **Phase 3+:** User Story Implementation (priority order: P1 → P2 → P3) 4. **Final Phase:** Polish & Cross-Cutting Concerns **Key Principles:** - Tasks grouped by user story for independent implementation - Each story independently testable and deliverable - Clear dependency tracking - Explicit parallelization markers - No user story work until foundational phase complete ### Phase 7: Implementation **Purpose:** Execute implementation phase-by-phase with built-in validation **8-Stage Process:** 1. **Prerequisite Checking:** Validate project readiness 2. **Checklist Validation:** Count completed/incomplete items, require confirmation if incomplete 3. **Context Analysis:** Read required artifacts (tasks.md, plan.md) and optional ones 4. **Project Setup:** Create/verify ignore files for detected technologies 5. **Task Processing:** Parse tasks, extract phases, dependencies, execution flow 6. **Phased Implementation:** Execute tasks phase-by-phase following TDD 7. **Error Handling:** Report progress, handle failures, provide debugging context 8. **Final Validation:** Confirm completion, validate implementation, check test coverage **Orchestration:** Systematic multi-stage execution with built-in checks and balances ## Orchestration & Parallel Execution ### Core Orchestration Philosophy **Sequential phase progression with parallel execution within phases where dependencies allow.** ### Coordination Mechanisms #### 1. Phase-Based Gates - Each phase must complete and validate before next phase begins - Gates block on errors or unresolved issues - Implementation: Template validation, checklist requirements, constitution alignment checks #### 2. Dependency Tracking - Tasks marked with dependencies that must be resolved before execution - Foundational phase blocks all user story work - Tasks reference prerequisites explicitly #### 3. Parallelization Markers - Tasks explicitly marked for parallel execution when no dependencies exist - Optional `||` marker in task format - Indicates tasks can run concurrently #### 4. User Story Grouping - Tasks grouped by user story for independent, parallel implementation - Each user story is independently testable and deliverable - Enables multiple agents/developers to work simultaneously #### 5. Constitutional Consistency - All phases reference constitution to maintain consistent practices - Constitution loaded and validated across all commands - Ensures alignment across parallel work streams ### Parallel Execution Patterns #### Pattern 1: User Story Parallelization After foundational phase completes, user stories (P1, P2, P3) can be implemented in parallel by different agents **Benefits:** - Independen
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.