Skill: wpank/context-driven-development (version 1.0.0)

--- name: context-driven-development model: reasoning version: 2.0.0 description: > Treat project context as a managed artifact alongside code. Use structured context documents (product.md, tech-stack.md, workflow.md) to enable consistent AI interactions and team alignment. Essential for projects using AI-assisted development. tags: [context, documentation, ai-alignment, team-workflow, methodology] --- # Context-Driven Development Treat project context as a first-class artifact managed alongside code. Instead of relying on ad-hoc prompts or scattered documentation, establish a persistent, structured foundation that informs all AI interactions. ## Installation ### OpenClaw / Moltbot / Clawbot ```bash npx clawhub@latest install context-driven-development ``` ## WHAT This Skill Does Creates and maintains a set of context documents that: - Define what you're building and why (product.md) - Specify technology choices and constraints (tech-stack.md) - Establish how the team works (workflow.md) - Track what's happening (tracks.md) ## WHEN to Use **Use for:** - Setting up new projects with AI-assisted development - Onboarding team members to existing codebases - Ensuring consistent AI behavior across sessions - Documenting decisions that affect code generation - Managing projects with multiple contributors or AI assistants **Skip for:** - Solo experiments or throwaway prototypes - Single-file scripts - Projects without AI assistance **Keywords:** context, project setup, documentation, AI alignment, team workflow, product vision, tech stack ## Core Philosophy ``` Context precedes code. Living documentation. Single source of truth. AI alignment. ``` 1. **Context precedes code** — Define what you're building and how before implementation 2. **Living documentation** — Context artifacts evolve with the project 3. **Single source of truth** — One canonical location for each type of information 4. **AI alignment** — Consistent context produces consistent AI behavior ## The Workflow ``` Context → Spec & Plan → Implement ``` 1. **Context Phase:** Establish or verify project context artifacts exist and are current 2. **Specification Phase:** Define requirements and acceptance criteria for work units 3. **Planning Phase:** Break specifications into phased, actionable tasks 4. **Implementation Phase:** Execute tasks following established workflow patterns ## The Context Documents ### product.md — WHAT and WHY Purpose: Captures product vision, goals, target users, and business context. **Contents:** - Product name and one-line description - Problem statement and solution approach - Target user personas - Core features and capabilities - Success metrics and KPIs - Product roadmap (high-level) **Update when:** - Product vision or goals change - New major features are planned - Target audience shifts ### tech-stack.md — WITH WHAT Purpose: Documents technology choices, dependencies, and architectural decisions. **Contents:** - Primary languages and frameworks - Key dependencies with versions - Infrastructure and deployment targets - Development tools and environment - Testing frameworks - Code quality tools **Update when:** - Adding new dependencies - Upgrading major versions - Changing infrastructure - Adopting new tools or patterns ### workflow.md — HOW to Work Purpose: Establishes development practices, quality gates, and team workflows. **Contents:** - Development methodology (TDD, trunk-based, etc.) - Git workflow and commit conventions - Code review requirements - Testing requirements and coverage targets - Quality assurance gates - Deployment procedures **Update when:** - Team practices evolve - Quality standards change - New workflow patterns are adopted ### tracks.md — WHAT'S HAPPENING Purpose: Registry of all work units with status and metadata. **Contents:** - Active tracks with current status - Completed tracks with completion dates - Track metadata (type, priority, assignee) - Links to individual track specs **Update when:** - New work starts - Work status changes - Work completes ## Directory Structure ``` context/ ├── product.md # Product vision and goals ├── tech-stack.md # Technology choices ├── workflow.md # Development practices ├── tracks.md # Work unit registry └── styleguides/ # Language-specific conventions ├── python.md ├── typescript.md └── ... ``` ## Setup: New Project (Greenfield) For new projects, create all artifacts from scratch: 1. **Create `context/product.md`:** - Define the problem you're solving - Describe target users - List core features for v1 - Define success metrics 2. **Create `context/tech-stack.md`:** - Choose languages and frameworks - Document key dependencies with versions - Specify infrastructure targets - List development tools 3. **Create `context/workflow.md`:** - Define branching strategy - Set commit conventions - Establish testing requirements - Document deployment process 4. **Create `context/tracks.md`:** - Start with empty registry - Add work units as they're created ## Setup: Existing Project (Brownfield) For existing codebases, extract context from what exists: 1. **Analyze the codebase:** - Read package.json, requirements.txt, go.mod, etc. - Look at existing README and docs - Check git history for patterns 2. **Create `context/tech-stack.md`:** - Document discovered dependencies - Note infrastructure from configs (Docker, CI, etc.) 3. **Create `context/product.md`:** - Infer product purpose from code - Document current feature set - Note any README content 4. **Create `context/workflow.md`:** - Document existing practices - Note any established patterns ## Maintenance Principles ### Keep Artifacts Synchronized Changes in one artifact should reflect in related documents: - New feature in product.md → Update tech-stack.md if new dependencies needed - Completed track → Update product.md to reflect new capabilities - Workflow change → Update all affected track plans ### Update tech-stack.md When Adding Dependencies Before adding any new dependency: 1. Check if existing dependencies solve the need 2. Document the rationale for new dependencies 3. Add version constraints 4. Note any configuration requirements ### Verify Context Before Implementation Before starting any work: 1. Read all context artifacts 2. Flag any outdated information 3. Propose updates before proceeding 4. Confirm context accuracy ## Validation Checklist Before starting implementation, validate: **Product Context:** - [ ] product.md reflects current vision - [ ] Target users are accurately described - [ ] Feature list is up to date **Technical Context:** - [ ] tech-stack.md lists all current dependencies - [ ] Version numbers are accurate - [ ] Infrastructure targets are correct **Workflow Context:** - [ ] workflow.md describes current practices - [ ] Quality gates are defined - [ ] Commit conventions are documented ## Anti-Patterns | Anti-Pattern | Problem | Fix | |--------------|---------|-----| | Stale Context | Documents become outdated and misleading | Update context as part of each track's completion | | Context Sprawl | Information scattered across multiple locations | Use defined artifact structure; resist new document types | | Implicit Context | Relying on knowledge not captured in artifacts | If referenced repeatedly, add to appropriate artifact | | Over-Specification | Context so detailed it's impossible to maintain | Keep focused on decisions affecting AI behavior and team alignment | ## Session Continuity ### Starting a New Session 1. Read context/product.md to orient yourself 2. Check context/tracks.md for active work 3. Read relevant track specs for current task 4. Verify context artifacts are current ### Ending a Session 1. Update track status with current progress 2. Note any blockers or decisions made 3. Commit in-progress work with clear status 4. Update tracks.md if status changed ## Benefits **Team Alignment:** - New team members onboard faster with explicit context - Consistent terminology across the team - Shared understanding of product goals **AI Consistency:** - AI assistants produce aligned outputs across sessions - Reduced need to re-explain context - Predictable behavior based on documented standards **Institutional Memory:** - Decisions and rationale are preserved - Context survives team changes - Historical context informs future decisions ## NEVER Do 1. **NEVER start implementation without reading context** — context precedes code 2. **NEVER add dependencies without updating tech-stack.md** — keep the source of truth current 3. **NEVER let context documents get stale** — update them as part of completing work 4. **NEVER scatter context across ad-hoc documents** — use the defined structure 5. **NEVER assume AI remembers previous sessions** — context must be in artifacts 6. **NEVER skip context for "quick" changes** — small changes compound into drift


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)