Creates and maintains project context artifacts (product.md, tech-stack.md, workflow.md, tracks.md) in a `conductor/` directory. Scaffolds new projects from scratch, extracts context from existing codebases, validates artifact consistency before implementation, and synchronizes documents as the project evolves.
NewMaintained
Automatic
◆AI Engineer pack
Last verified 8/7/2026
What it changes
Passed 8 of 22 test cases with the skill, and 14 of 22 without it.
Without skill63%
With skill38%
Checks it passed that the model alone missed
The response specifies referencing context markdown files from the .context/ directory at the start of the AI prompting session.
The response specifies requiring that modified files in the .context/ directory are reviewed alongside code changes before PR approval.
The response recommends adding the TypeDoc HTML output directory docs/ to .gitignore so generated build artifacts are excluded from git.
3 fixed8 passed either way6 still failing5 broke
Pass-rate lift
-25 pp
Tokens
-17%
Agent turns
0%
Response time
-31%
Model gemini-3.6-flashMeasured 8/7/2026v111 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 3
Prompt
An engineer is preparing to prompt an AI agent to implement a new feature. Before sending the prompt, what specific step should be taken regarding repository context files, and which file path convention is used?
What was checked, without and with the skill
Checked
Without skill
With skill
The response specifies referencing context markdown files from the .context/ directory at the start of the AI prompting session.
Missed
Passed
case-07 · gemini-3.6-flash · 8/7/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md29 lines3 files
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.
When to Use This Skill
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
Detailed patterns and worked examples
Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.
Best Practices
Read context first: Always read relevant artifacts before starting work
Small updates: Make incremental context changes, not massive rewrites
Link decisions: Reference context when making implementation choices
Version context: Commit context changes alongside code changes
Review context: Include context artifact reviews in code reviews
Validate regularly: Run context validation checklist before major work
Communicate changes: Notify team when context artifacts change significantly
Preserve history: Use git to track context evolution over time
Question staleness: If context feels wrong, investigate and update
Keep it actionable: Every context item should inform a decision or behavior