name	sync-copilot-workflows
version	1.0.0
description	[AI & Tools] Use when you need to sync workflow catalog from workflows JSON to GitHub Copilot instructions.

Quick Summary

Goal: [AI & Tools] Sync workflow catalog from workflows.json to GitHub Copilot instructions. Run after adding/removing/modifying workflows to keep copilot-instructions.md up to date. Copilot has no hooks, so this manual sync replaces the auto-injection that Claude Code gets from workflow-router.cjs.

Workflow:

Detect — classify request scope and target artifacts.
Execute — apply required steps with evidence-backed actions.
Verify — confirm constraints, output quality, and completion evidence.

Key Rules:

MUST ATTENTION keep claims evidence-based (file:line) with confidence >80% to act.
MUST ATTENTION keep task tracking updated as each step starts/completes.
NEVER skip mandatory workflow or skill gates.

When to Use

After adding, removing, or modifying workflows in .claude/workflows.json
After running /ai-dev-tools-sync to ensure workflow parity
When copilot workflow catalog is stale or drifted

NOT for: Claude Code workflow issues (Claude gets auto-injected catalog via workflow-router.cjs hook).

What To Do

Run the sync script:

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

Verify the output shows the correct workflow count and "Updated" message
Optionally preview first with --dry-run:

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

How It Works

Source of truth: .claude/workflows.json (32 workflows, keyword matching, sequences)
Target: .github/copilot-instructions.md section ## Workflow Catalog
Script: .claude/scripts/sync-copilot-workflows.cjs
The script generates a keyword lookup table, full workflow details, handoff table, and execution protocol
The generated section has  markers to prevent manual edits

Why This Exists

Claude Code has workflow-router.cjs hook that auto-injects the workflow catalog on every prompt. GitHub Copilot has no hook system, so the catalog must be statically embedded in copilot-instructions.md. This skill bridges that gap with a one-command sync.

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

Sync Copilot Workflows

Generate and update the workflow catalog in .github/copilot-instructions.md from the source of truth .claude/workflows.json.

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

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.

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.

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

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

Closing Reminders

IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate 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 TaskCreate.

Sync Copilot Workflows

Generate and update the workflow catalog in .github/copilot-instructions.md from the source of truth .claude/workflows.json.

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

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.

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.

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

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

Closing Reminders

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