Complete AI TrainingYourJobSkills for your job

Skills / ai-ml

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.

AI & Automation

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.
  • Use the workflow, artifact relationships, and validation checklist below when
  • detailed implementation guidance is required.

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:

Subscribers only

The full skill, its 1 bundled files and every download is included with every paid Complete AI plan.

Details

Sourcecommunity
License
Risk labelcritical ("critical" means the skill may run commands or touch files — read before use)
FilesSKILL.md
Added2026-02-27

Related skills

advanced-evaluation

This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

agent-creator

Create custom AI subagents with proper plugin structure, persona generation, and companion routing skills.

agent-framework-azure-ai-py

Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK.

agent-memory

A hybrid memory system that provides persistent, searchable knowledge management for AI agents.

agent-memory-mcp

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

agent-orchestration-improve-agent

Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.