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Create a copilot-instructions.md file from an existing codebase. Identify technology versions, architecture, naming conventions, and testing practices, then turn observed patterns into project-specific guidance for GitHub Copilot without introducing unsupported assumptions.
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Optimize oversized agent instruction files using progressive disclosure. Handles CLAUDE.md (Claude Code), AGENTS.md (OpenAI Codex / GitHub Copilot agents), and copilot-instructions.md (GitHub Copilot). Auto-detects all three formats in your repo, analyzes content tiers, creates sub-documents using each format's native mechanism, and rewrites the main file with zero information loss. Triggers: optimize CLAUDE.md, AGENTS.md too long, reduce copilot-instructions.md, agent instructions file too large, shrink context file, apply progressive disclosure, instructions file bloated
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Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.
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Get instructions for installing and reviewing the full ai-ready skill in Copilot CLI. This wrapper explains how to add the latest version, reload skills, and request repository preparation for AI contributions.
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Technology-agnostic blueprint generator for creating comprehensive copilot-instructions.md files that guide GitHub Copilot to produce code consistent with project standards, architecture patterns, and exact technology versions by analyzing existing codebase patterns and avoiding assumptions.
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[omh] Agent instruction file for a repo -- AGENTS.md, CLAUDE.md, a Cursor rule: write or update what an agent cannot derive from the code, inside a marked region, with every command verified or marked unverified and no counts that drift. Use when the user says: agent-instructions, agents.md, claude.md, gemini.md, copilot-instructions.md, .cursorrules, cursor rules, cursor rule.
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Create, update, review, fix, or debug VS Code agent customization files (.instructions.md, .prompt.md, .agent.md, SKILL.md, copilot-instructions.md, AGENTS.md). Use for: saving coding preferences; troubleshooting why instructions/skills/agents are ignored or not invoked; configuring applyTo patterns; defining tool restrictions; creating custom agent modes or specialized workflows; packaging domain knowledge; fixing YAML frontmatter syntax.
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Run a retro for personal global ~/.copilot assets and turn incident learnings into updates for copilot-instructions, instructions, skills, agents, and hooks. Not for workspace/repository assets or a private skills repository. Triggers on retro, retrospective, incident learning, error analysis, copilot setup, instructions update, インシデント, and 知見反映.
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Use when creating or updating AGENTS.md files, .github/copilot-instructions.md, or other AI agent rule files, onboarding AI agents to a project, standardizing agent documentation, or when anyone mentions AGENTS.md, agent rules, project onboarding, or codebase documentation for AI agents.
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Suggest relevant GitHub Copilot instruction files from the awesome-copilot repository based on current repository context and chat history, avoiding duplicates with existing instructions in this repository, and identifying outdated instructions that need updates.
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Use when optimizing AGENTS.md or copilot-instructions.md — deduplicates against .augment/ content, enforces line budgets, and focuses each file on its audience.
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Tune the GitHub Copilot AI — `copilot-instructions.md`, PR-review patterns, suggestion behavior, output verbosity. NOT for dev-environment setup (use `devcontainer`).
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Use when reading, creating, or updating agent documentation, module docs, roadmaps, or AGENTS.md. Understands the full .augment/, agents/, and copilot-instructions structure.
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Semantic audit of the IDD instruction corpus for leaked session context, cross-file contradictions, fresh-memory completability gaps, automation blockers, and restatement-discipline drift. Use on request to audit .github/instructions, the issue-authoring skill bundle, and the installed agent entry files (CLAUDE.md, AGENTS.md, GEMINI.md, .github/copilot-instructions.md). Read-only — never edits files or mutates issues.
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Installs John Papa's ai-ready skill, which makes a repository AI-ready by generating AGENTS.md, copilot-instructions.md, CI workflows, and issue templates. Use when the user asks to make a repo AI-ready or set up AI agent configuration for a project.
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Perform repository-aware code reviews focused on bugs, regressions, architectural violations, missing tests, and operational risks. Use when the user asks for review of diffs, pull requests, patches, or implementation quality.
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Improve platform resilience with timeout/retry/circuit-breaker strategy, capacity controls, chaos testing, and disaster recovery readiness. Use when tasks involve reliability hardening, failure-mode testing, incident prevention, or recovery objectives.
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Audit and remediate dependency/package vulnerabilities across .NET backend, frontend (npm/pnpm/yarn), and Rust projects with severity-based quality gates. Use when the user asks for SCA checks, dependency hardening, or release security gates before build/package.
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Plan and sequence complex implementation work into deterministic, testable steps for this repository. Use when the user asks for planning, roadmap breakdown, execution strategy, effort estimation, or multi-step delivery coordination across domains.
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Route tasks using the repository's static routing catalog and load only the minimal context pack. Use before execution when the task spans multiple domains or the correct instruction set is unclear.
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Build and maintain CI/CD pipelines, containerization, Kubernetes manifests, and quality gates for this repository. Use when the user asks for Docker, Kubernetes, GitHub Actions/Azure DevOps pipelines, deployment, reliability, or static analysis workflows.
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Use as the single visible starter and controller for workspace work that may change files, runtime assets, planning state, docs, settings, or governance. Normalize the request into the Super Agent lifecycle: intake, spec registration for non-trivial work, planning registration, specialist routing, execution, testing, review, closeout, and planning-state updates before implementation begins.
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Design, implement, and stabilize automated tests (unit, integration, E2E) for .NET/C#, Rust, APIs, and frontend flows. Use when the user asks to create tests, increase coverage, fix flaky tests, or validate behavior changes.
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Use for non-trivial feature, behavior, workflow, or architecture work before execution planning. Create or update a versioned spec under planning/specs/active with design intent, alternatives, risks, acceptance criteria, and planning readiness.
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