Sync To Copilot

Codex compatibility note:

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- Invoke repository skills with $skill-name in Codex; this mirrored copy rewrites legacy Claude /skill-name references.

- Task tracker mandate: BEFORE executing any workflow or skill step, create/update task tracking for all steps and keep it synchronized as progress changes.

- User-question prompts mean to ask the user directly in Codex.

- Ignore Claude-specific mode-switch instructions when they appear.

- Strict execution contract: when a user explicitly invokes a skill, execute that skill protocol as written.

- Subagent authorization: when a skill is user-invoked or AI-detected and its protocol requires subagents, that skill activation authorizes use of the required spawn_agent subagent(s) for that task.

- Do not skip, reorder, or merge protocol steps unless the user explicitly approves the deviation first.

- For workflow skills, execute each listed child-skill step explicitly and report step-by-step evidence.

- If a required step/tool cannot run in this environment, stop and ask the user before adapting.

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Codex Project-Reference Loading (No Hooks)

Codex does not receive Claude hook-based doc injection. When coding, planning, debugging, testing, or reviewing, open project docs explicitly using this routing.

Always read:

• docs/project-config.json (project-specific paths, commands, modules, and workflow/test settings)
• docs/project-reference/docs-index-reference.md (routes to the full docs/project-reference/* catalog)
• docs/project-reference/lessons.md (always-on guardrails and anti-patterns)

Situation-based docs:

• Backend/CQRS/API/domain/entity changes: backend-patterns-reference.md, domain-entities-reference.md, project-structure-reference.md
• Frontend/UI/styling/design-system: frontend-patterns-reference.md, scss-styling-guide.md, design-system/README.md
• Spec/test-case planning or TC mapping: feature-docs-reference.md
• Integration test implementation/review: integration-test-reference.md
• E2E test implementation/review: e2e-test-reference.md
• Code review/audit work: code-review-rules.md plus domain docs above based on changed files

Do not read all docs blindly. Start from docs-index-reference.md, then open only relevant files for the task.

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Quick Summary

Purpose: Keep Copilot instructions in sync with Claude Code workflows, dev rules, and project-reference docs.

Architecture (Two-Tier):

1. .github/copilot-instructions.md — Project-specific (always loaded by Copilot)

• TL;DR golden rules, decision table
• Project-reference docs index with READ prompts
• Key file locations, dev commands

2. .github/instructions/common-protocol.instructions.md — Generic protocols (applyTo: **/*)

• Prompt protocol, before-editing rules
• Workflow catalog (from workflows.json)
• Workflow execution protocol
• Development rules (from development-rules.md)

3. .github/instructions/{group}.instructions.md — Per-group (applyTo: file patterns)

• Enhanced summaries per doc with READ prompts
• Groups: backend, frontend, styling, testing, project

What gets synced:

• Workflow catalog (from workflows.json) — SCRIPT-GENERATED
• Dev rules (from development-rules.md) — SCRIPT-GENERATED
• Project-reference summaries (from copilot-registry.json) — SCRIPT-GENERATED
• Enriched section headings and key patterns — AI-GENERATED (this skill)

Usage:

$sync-to-copilot

Script: .claude/scripts/sync-copilot-workflows.cjs

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Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

When to Use This Skill

Scope vs related skills: Syncs Claude→Copilot knowledge (docs, dev-rules, workflow catalog) into Copilot instructions via script + AI enrichment. For the `workflows.json` catalog only (fast, no AI pass) → $sync-copilot-workflows. For bidirectional sync incl. skills/prompts/agents → $ai-dev-tools-sync.

Trigger this skill when:

• Workflows added/modified — After editing .claude/workflows.json
• Development rules changed — After editing .claude/docs/development-rules.md
• Project-reference docs updated — After modifying files in docs/project-reference/
• Registry entries changed — After editing docs/copilot-registry.json
• Regular maintenance — Quarterly sync to ensure Copilot parity
• Copilot setup — First-time Copilot instructions creation

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Workflow

Phase 1: Script Generation (Automated)

node .claude/scripts/sync-copilot-workflows.cjs

This generates:

• .github/copilot-instructions.md — project-specific with registry summaries
• .github/instructions/common-protocol.instructions.md — generic protocols
• .github/instructions/{group}.instructions.md — per-group instruction files
• Removes old .github/common.copilot-instructions.md if it exists

Phase 2: AI Enrichment (This Skill)

After the script runs, the AI MUST ATTENTION enrich the generated instruction files:

1. For each per-group instruction file in .github/instructions/:

• Read the corresponding docs/project-reference/*.md source file
• Extract the ## section headings from the source file
• Add a "Key Sections" list under each doc entry showing the headings
• Keep it concise — headings only, no content duplication

2. For `.github/copilot-instructions.md`:

• Verify the TL;DR golden rules in docs/copilot-registry.json → projectInstructions.goldenRules still match CLAUDE.md
• Check if any new project-reference files exist but are missing from docs/copilot-registry.json
• If missing entries found, add them to the registry and re-run the script

3. For `docs/copilot-registry.json`:

• Verify each summary field accurately describes the current file content
• Update stale summaries based on actual file content
• Add entries for any new docs/project-reference/*.md files

Phase 3: Verification

Check that:

• [x] .github/copilot-instructions.md contains project-specific content
• [x] .github/instructions/common-protocol.instructions.md contains protocols + workflow catalog
• [x] Per-group instruction files contain READ prompts
• [x] No old common.copilot-instructions.md file remains
• [x] Workflow count matches workflows.json
• [x] All project-reference files are represented in the registry

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AI Enrichment Protocol

When enriching per-group instruction files, follow this pattern for each doc entry:

## [Doc Title](relative/path)

**Summary:** One-line summary from registry.

**Key Sections:**

- Section 1 Name
- Section 2 Name
- Section 3 Name
- ...

> **READ** `docs/project-reference/filename.md` when: trigger description

Rules:

• Extract ONLY ## level headings from the source file (not ### or deeper)
• List heading names only — do NOT copy content
• Keep the READ prompt from the registry whenToRead field
• If a file is very large (>30KB), note the file size: (~59KB - read relevant sections)

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Output Files

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Copilot Limitations

Copilot can't enforce protocols like Claude Code hooks:

• No blocking operations (edit-enforcement)
• Relies on LLM instruction-following (not guaranteed)
• Protocols are advisory, not enforced
• No runtime context injection — all context must be in instruction files

Benefits:

• Consistent guidance across AI tools
• Same workflow detection for Claude and Copilot users
• READ prompts enable on-demand context loading
• Automated sync reduces configuration drift

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Troubleshooting

Issue: "workflows.json not found"

Solution: Ensure you're running from project root

Issue: Missing project-reference files in registry

Solution: Add entries to docs/copilot-registry.json, then re-run script

Issue: Stale summaries

Solution: Run this skill — AI will read files and update summaries

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Related Skills

• $ai-dev-tools-sync — Broader Claude/Copilot sync (skills, prompts, agents)
• $sync-copilot-workflows — Workflow-only sync (subset of this skill)

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References

• Script: .claude/scripts/sync-copilot-workflows.cjs
• Registry: docs/copilot-registry.json
• Sources: .claude/workflows.json, .claude/docs/development-rules.md
• Main output: .github/copilot-instructions.md
• Instruction files: .github/instructions/*.instructions.md

---

Skill: sync-to-copilot

Sync Claude Code knowledge to GitHub Copilot instructions. Two-tier output: project-specific + common protocol.

---

<!-- SYNC:ai-mistake-prevention -->

AI Mistake Prevention — Failure modes to avoid on every task:

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Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal.

Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing.

Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain.

Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path.

When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site.

Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code.

Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks.

Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis.

Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly.

Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

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<!-- SYNC:critical-thinking-mindset -->

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act.

Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

<!-- /SYNC:critical-thinking-mindset -->

<!-- SYNC:critical-thinking-mindset:reminder -->

MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

<!-- /SYNC:critical-thinking-mindset:reminder -->

<!-- SYNC:ai-mistake-prevention:reminder -->

MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

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Closing Reminders

IMPORTANT MUST ATTENTION break work into small todo tasks using task tracking BEFORE starting IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act) IMPORTANT MUST ATTENTION add a final review todo task to verify work quality

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using task tracking.

<!-- CODEX:SYNC-PROMPT-PROTOCOLS:START -->

Hookless Prompt Protocol Mirror (Auto-Synced)

Source: .claude/hooks/lib/prompt-injections.cjs + .claude/.ck.json

[WORKFLOW-EXECUTION-PROTOCOL] [BLOCKING] Workflow Execution Protocol — MANDATORY IMPORTANT MUST CRITICAL. Do not skip for any reason.

Generic portability boundary: Reusable skills and protocol text stay project-neutral; project-specific conventions are discovered from docs/project-config.json and docs/project-reference/. Apply shared AI-SDD from shared/sdd-artifact-contract.md. Read docs/project-config.json and docs/project-reference/docs-index-reference.md, then open the project reference docs named there. Any supported AI tool may execute when this shared context and local docs are available.

1. DETECT: Match prompt against workflow catalog 2. ANALYZE: Find best-match workflow AND evaluate if a custom step combination would fit better 3. ASK (REQUIRED FORMAT): Use a direct user question with this structure unless the user explicitly invoked a workflow/skill and the local protocol treats explicit invocation as confirmation:

• Question: "Which workflow do you want to activate?"
• Option 1: "Activate [BestMatch Workflow] (Recommended)"
• Option 2: "Activate custom workflow: [step1 → step2 → ...]" (include one-line rationale)

4. ACTIVATE (if confirmed): Call $workflow-start <workflowId> for standard; sequence custom steps manually 5. CREATE TASKS: task tracking for ALL workflow steps 6. EXECUTE: Follow each step in sequence [CRITICAL-THINKING-MINDSET] Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination principle: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination. AI Attention principle (Primacy-Recency): Put the 3 most critical rules at both top and bottom of long prompts/protocols so instruction adherence survives long context windows. Goal-driven execution: Define success criteria first, loop until verified, and stop only when observable checks pass. Tests verify intent: Tests must protect business rules/invariants and fail when the protected intent breaks, not only mirror current behavior.

[LESSON-LEARNED-REMINDER] [BLOCKING] Task Planning & Continuous Improvement — MANDATORY. Do not skip.

Break work into small tasks (task tracking) before starting. Add final task: "Analyze AI mistakes & lessons learned".

Extract lessons — ROOT CAUSE ONLY, not symptom fixes:

1. Name the FAILURE MODE (reasoning/assumption failure), not symptom — "assumed API existed without reading source" not "used wrong enum value". 2. Generality test: does this failure mode apply to ≥3 contexts/codebases? If not, abstract one level up. 3. Write as a universal rule — strip project-specific names/paths/classes. Useful on any codebase. 4. Consolidate: multiple mistakes sharing one failure mode → ONE lesson. 5. Recurrence gate: "Would this recur in future session WITHOUT this reminder?" — No → skip $learn. 6. Auto-fix gate: "Could $code-review/$code-simplifier/$security/$lint catch this?" — Yes → improve review skill instead. 7. BOTH gates pass → ask user to run $learn. [TASK-PLANNING] [MANDATORY] BEFORE executing any workflow or skill step, create/update task tracking for all planned steps, then keep it synchronized as each step starts/completes.

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