Use this skill when working with Conductor's context-driven development methodology, managing project context artifacts, or understanding the relationship between product.md, tech-stack.md, and workflow.md files.
SkillScore95Maintained
Automatic
◆AI Engineer pack
Last verified 8/23/2026
What it changes
Passed 21 of 22 test cases with the skill, and 7 of 22 without it.
Without skill32%
With skill95%
Checks it passed that the model alone missed
Includes index.md in the track folder
Lists loop-fixer as the final agent role
Directs checking tracks.md for active work
and 21 more in the full report
15 fixed6 passed either way0 still failing1 broke
Pass-rate lift
+64 pp
Tokens
+100%
Agent turns
0%
Response time
-44%
Model gemini-3.6-flashMeasured 8/23/2026v121 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 15 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 15
Prompt
Our team needs to document product vision, target personas, roadmaps, and feature capabilities. Which Conductor context document holds this information?
What was checked, without and with the skill
Checked
Without skill
With skill
Identifies product.md as the target artifact
Missed
Passed
case-05 · gemini-3.6-flash · 8/23/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md385 linessingle file
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
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:
Context precedes code: Define what you're building and how before implementation
Living documentation: Context artifacts evolve with the project
Single source of truth: One canonical location for each type of information
AI alignment: Consistent context produces consistent AI behavior
The Workflow
Follow the Context -> Spec -> Evaluate-Loop workflow:
Context Phase: Establish or verify project context artifacts exist and are current
Specification Phase: Define requirements and acceptance criteria for work units
Evaluate-Loop Phase: Execute via the loop agents coordinated by conductor-orchestrator:
Step 1: loop-planner -- creates execution plan from spec
Step 2: loop-plan-evaluator -- verifies plan before coding