context-driven-development
Guide for implementing and maintaining context as a managed artifact alongside code, enabling consistent AI interactions and team alignment through structured project documentation.
About this skill
The 'Context-Driven Development' skill equips AI agents with a structured methodology for managing project context as a first-class artifact. It enables agents to consistently implement and maintain crucial project information—such as goals, constraints, existing codebase patterns, and team agreements—alongside code and documentation. By formalizing context, this skill ensures AI interactions are highly consistent, relevant, and aligned with overall project objectives. It fosters better collaboration between AI agents and human teams, leading to more coherent outputs, reduced inconsistencies, and a robust, shared understanding of the project state.
Best use case
AI-assisted software development where maintaining a consistent understanding of project goals, constraints, and existing architecture is critical. Onboarding new AI agents or human team members to a complex project by providing a structured context. Generating consistent code, design proposals, or documentation that adheres to established project patterns and principles. Facilitating AI agents in making informed decisions by providing access to a well-managed and up-to-date project context. Automating the creation and maintenance of project documentation that reflects the current context.
Guide for implementing and maintaining context as a managed artifact alongside code, enabling consistent AI interactions and team alignment through structured project documentation.
AI agents that produce more relevant, consistent, and context-aware outputs (code, documentation, solutions). Improved alignment between AI agent actions and overall project goals, constraints, and existing patterns. A clearer, more structured, and consistently updated body of project documentation, benefiting both human and AI collaborators. Reduced need for repetitive clarification for AI agents, as context is managed and readily accessible. Enhanced team productivity through a shared and well-maintained understanding of project context.
Practical example
Example input
Task: Develop a new feature for our existing customer portal: 'Subscription Management Dashboard'. Current Context (managed artifact): - Tech Stack: React (frontend), Node.js/Express (backend), PostgreSQL (database), AWS S3 (static assets). - Design System: Uses Material-UI v5 with custom theme overrides. - API Standards: RESTful, JSON payload, authentication via JWT. - Error Handling: Global error middleware for HTTP 5xx, custom error types for 4xx. - Existing Modules: User profiles, product catalog, payment gateway integration. Instructions: As an AI agent utilizing the 'Context-Driven Development' skill, clarify the specific requirements for displaying active subscriptions, allowing users to upgrade/downgrade, and viewing billing history. Propose backend API endpoints, database schema changes, and frontend component structure, ensuring full adherence to our established context.
Example output
Understood. Applying the 'Context-Driven Development' framework, I will proceed by:
1. **Clarifying Goals:** Determine precise user interactions for viewing, modifying, and reviewing subscriptions. Confirm data points required from the backend.
2. **Defining Constraints:** Ensure compliance with existing API standards, Material-UI theme, and PostgreSQL schema best practices.
3. **Proposing Backend Changes:**
* **Endpoints:**
* `GET /api/subscriptions/active`: Fetch current subscriptions.
* `POST /api/subscriptions/update`: Update subscription plan.
* `GET /api/billing-history`: Retrieve past invoices/transactions.
* **Database Schema:**
* `subscriptions` table: `id`, `user_id`, `plan_id`, `start_date`, `end_date`, `status`, `price`.
* `billing_records` table: `id`, `user_id`, `subscription_id`, `amount`, `currency`, `transaction_date`, `status`.
4. **Proposing Frontend Structure (React/Material-UI):**
* `SubscriptionDashboard.jsx`: Main component.
* `ActiveSubscriptionsTable.jsx`: Displays current plans.
* `SubscriptionUpgradeModal.jsx`: Handles plan changes.
* `BillingHistoryList.jsx`: Shows past transactions.
* Ensuring Material-UI components are used with our custom theme, and API calls are handled via an agreed-upon service layer, respecting our error handling conventions.
This approach guarantees that the new feature is fully integrated and consistent with the project's managed context.When to use this skill
- When an AI agent needs to operate with a deep and consistent understanding of a project's specific context, including existing code, design principles, or business rules.
- When striving for high consistency in AI-generated outputs (code, documentation, designs) across different tasks or interactions within a project.
- When developing complex software systems where misinterpretations of context can lead to significant issues.
- When formalizing project knowledge and documentation for both human and AI team members.
When not to use this skill
- For simple, one-off tasks that do not require an understanding of a persistent project context.
- When the task's scope is entirely outside the realm of software development or project context management.
- When the AI agent is intended to operate in a completely unconstrained or exploratory manner, without specific project guidelines.
- If the primary need is for a different domain-specific tool or API (e.g., direct code generation without context, sentiment analysis, image processing).
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/context-driven-development/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How context-driven-development Compares
| Feature / Agent | context-driven-development | Standard Approach |
|---|---|---|
| Platform Support | Claude | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | easy | N/A |
Frequently Asked Questions
What does this skill do?
Guide for implementing and maintaining context as a managed artifact alongside code, enabling consistent AI interactions and team alignment through structured project documentation.
Which AI agents support this skill?
This skill is designed for Claude.
How difficult is it to install?
The installation complexity is rated as easy. You can find the installation instructions above.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Context-Driven Development
Guide for implementing and maintaining context as a managed artifact alongside code, enabling consistent AI interactions and team alignment through structured project documentation.
## Do not use this skill when
- The task is unrelated to context-driven development
- You need a different domain or tool outside this scope
## Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open `resources/implementation-playbook.md`.
## Use this skill when
- Setting up new projects with Conductor
- Understanding the relationship between context artifacts
- Maintaining consistency across AI-assisted development sessions
- Onboarding team members to an existing Conductor project
- Deciding when to update context documents
- Managing greenfield vs brownfield project contexts
## Core Philosophy
Context-Driven Development treats 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.
Key principles:
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
Follow the **Context → Spec & Plan → Implement** workflow:
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
## Artifact Relationships
### product.md - Defines 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
- Business priorities evolve
### product-guidelines.md - Defines HOW to Communicate
Purpose: Establishes brand voice, messaging standards, and communication patterns.
Contents:
- Brand voice and tone guidelines
- Terminology and glossary
- Error message conventions
- User-facing copy standards
- Documentation style
Update when:
- Brand guidelines change
- New terminology is introduced
- Communication patterns need refinement
### tech-stack.md - Defines 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 - Defines HOW to Work
Purpose: Establishes development practices, quality gates, and team workflows.
Contents:
- Development methodology (TDD, 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 - Tracks 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 directories
Update when:
- New tracks are created
- Track status changes
- Tracks are completed or archived
## Context Maintenance Principles
### Keep Artifacts Synchronized
Ensure changes in one artifact 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
### Update product.md When Features Complete
After completing a feature track:
1. Move feature from "planned" to "implemented" in product.md
2. Update any affected success metrics
3. Document any scope changes from original plan
### Verify Context Before Implementation
Before starting any track:
1. Read all context artifacts
2. Flag any outdated information
3. Propose updates before proceeding
4. Confirm context accuracy with stakeholders
## Greenfield vs Brownfield Handling
### Greenfield Projects (New)
For new projects:
1. Run `/conductor:setup` to create all artifacts interactively
2. Answer questions about product vision, tech preferences, and workflow
3. Generate initial style guides for chosen languages
4. Create empty tracks registry
Characteristics:
- Full control over context structure
- Define standards before code exists
- Establish patterns early
### Brownfield Projects (Existing)
For existing codebases:
1. Run `/conductor:setup` with existing codebase detection
2. System analyzes existing code, configs, and documentation
3. Pre-populate artifacts based on discovered patterns
4. Review and refine generated context
Characteristics:
- Extract implicit context from existing code
- Reconcile existing patterns with desired patterns
- Document technical debt and modernization plans
- Preserve working patterns while establishing standards
## Benefits
### Team Alignment
- New team members onboard faster with explicit context
- Consistent terminology and conventions across the team
- Shared understanding of product goals and technical decisions
### AI Consistency
- AI assistants produce aligned outputs across sessions
- Reduced need to re-explain context in each interaction
- Predictable behavior based on documented standards
### Institutional Memory
- Decisions and rationale are preserved
- Context survives team changes
- Historical context informs future decisions
### Quality Assurance
- Standards are explicit and verifiable
- Deviations from context are detectable
- Quality gates are documented and enforceable
## Directory Structure
```
conductor/
├── index.md # Navigation hub linking all artifacts
├── product.md # Product vision and goals
├── product-guidelines.md # Communication standards
├── tech-stack.md # Technology preferences
├── workflow.md # Development practices
├── tracks.md # Work unit registry
├── setup_state.json # Resumable setup state
├── code_styleguides/ # Language-specific conventions
│ ├── python.md
│ ├── typescript.md
│ └── ...
└── tracks/
└── <track-id>/
├── spec.md
├── plan.md
├── metadata.json
└── index.md
```
## Context Lifecycle
1. **Creation**: Initial setup via `/conductor:setup`
2. **Validation**: Verify before each track
3. **Evolution**: Update as project grows
4. **Synchronization**: Keep artifacts aligned
5. **Archival**: Document historical decisions
## Context Validation Checklist
Before starting implementation on any track, validate context:
### Product Context
- [ ] product.md reflects current product vision
- [ ] Target users are accurately described
- [ ] Feature list is up to date
- [ ] Success metrics are defined
### Technical Context
- [ ] tech-stack.md lists all current dependencies
- [ ] Version numbers are accurate
- [ ] Infrastructure targets are correct
- [ ] Development tools are documented
### Workflow Context
- [ ] workflow.md describes current practices
- [ ] Quality gates are defined
- [ ] Coverage targets are specified
- [ ] Commit conventions are documented
### Track Context
- [ ] tracks.md shows all active work
- [ ] No stale or abandoned tracks
- [ ] Dependencies between tracks are noted
## Common Anti-Patterns
Avoid these context management mistakes:
### Stale Context
Problem: Context documents become outdated and misleading.
Solution: Update context as part of each track's completion process.
### Context Sprawl
Problem: Information scattered across multiple locations.
Solution: Use the defined artifact structure; resist creating new document types.
### Implicit Context
Problem: Relying on knowledge not captured in artifacts.
Solution: If you reference something repeatedly, add it to the appropriate artifact.
### Context Hoarding
Problem: One person maintains context without team input.
Solution: Review context artifacts in pull requests; make updates collaborative.
### Over-Specification
Problem: Context becomes so detailed it's impossible to maintain.
Solution: Keep artifacts focused on decisions that affect AI behavior and team alignment.
## Integration with Development Tools
### IDE Integration
Configure your IDE to display context files prominently:
- Pin conductor/product.md for quick reference
- Add tech-stack.md to project notes
- Create snippets for common patterns from style guides
### Git Hooks
Consider pre-commit hooks that:
- Warn when dependencies change without tech-stack.md update
- Remind to update product.md when feature branches merge
- Validate context artifact syntax
### CI/CD Integration
Include context validation in pipelines:
- Check tech-stack.md matches actual dependencies
- Verify links in context documents resolve
- Ensure tracks.md status matches git branch state
## Session Continuity
Conductor supports multi-session development through context persistence:
### Starting a New Session
1. Read index.md to orient yourself
2. Check tracks.md for active work
3. Review relevant track's plan.md for current task
4. Verify context artifacts are current
### Ending a Session
1. Update plan.md 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
### Handling Interruptions
If interrupted mid-task:
1. Mark task as `[~]` with note about stopping point
2. Commit work-in-progress to feature branch
3. Document any uncommitted decisions in plan.md
## Best Practices
1. **Read context first**: Always read relevant artifacts before starting work
2. **Small updates**: Make incremental context changes, not massive rewrites
3. **Link decisions**: Reference context when making implementation choices
4. **Version context**: Commit context changes alongside code changes
5. **Review context**: Include context artifact reviews in code reviews
6. **Validate regularly**: Run context validation checklist before major work
7. **Communicate changes**: Notify team when context artifacts change significantly
8. **Preserve history**: Use git to track context evolution over time
9. **Question staleness**: If context feels wrong, investigate and update
10. **Keep it actionable**: Every context item should inform a decision or behaviorRelated Skills
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