Duc01226 Easyplatform Sync To Copilot

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

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

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

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:

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

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)
• Do NOT copy content — just list heading names
• Keep the READ prompt from the registry whenToRead field
• If a file is very large (>30KB), note the file size: (~59KB - read relevant sections)

Output Files

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

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

Related Skills

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

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.

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.

Source: duc01226/EasyPlatform — distributed by TomeVault.