research-leads

name	research-leads
description	Research new capabilities and changes for tracked AI coding agents. Use this skill when assigned a research-leads issue to discover new features, or when asked to revise a research PR.

Research Leads Skill

You proactively research developments for AI coding agents tracked in this repository.

Context

This repository tracks capabilities of these AI coding agents:

• claude-code (Anthropic) — CLI agent for code generation, editing, debugging
• copilot-cli (GitHub) — CLI companion for terminal workflows
• gemini-cli (Google) — CLI agent powered by Gemini models
• vscode-copilot (GitHub) — VS Code integrated AI coding assistant

Each agent's capabilities are stored in agents/<name>/capabilities/current.json.

Lead Types

Research these categories of changes:

1. New capability — A feature not yet tracked (e.g. a new tool, mode, or integration)
2. Changed capability — An existing feature that evolved significantly (renamed, expanded, restructured)
3. Version / model release — A new version, model update, or platform change
4. Deprecation notice — A feature being removed or replaced
5. New agent — A new AI coding agent worth adding to the tracker

Confidence Levels

• High — Official documentation or changelog explicitly confirms the change
• Medium — Blog post, release notes, or credible announcement confirms it
• Low — Inference from indirect evidence only (pre-uncheck these in the PR)

Research Mode

When assigned an issue labelled research-leads:

Step 1: Understand current state

Read each agents/<name>/capabilities/current.json to understand what's already tracked. Note capability names, descriptions, and source URLs.

Step 2: Research each agent

For each tracked agent, check:

• Official documentation sites for new or restructured pages
• Changelog / release notes for recent updates
• GitHub releases (for open-source agents)
• Product announcement blogs
• Any other authoritative sources you find

Look for capabilities, features, or integrations not yet in the data.

Step 3: Create the PR

Open a PR with the actual proposed changes to current.json files in the diff.

PR description format — this IS the triage interface:

## Research Leads — YYYY-MM-DD

Uncheck items to skip. Edit inline to correct a source URL.
Comment `@copilot revise` after making changes.

---

### claude-code (N leads)
- [x] **New: <Capability Name>** · High confidence
      Source: <url>
      Action: Add entry to current.json

- [x] **Update: <Capability Name>** · Medium confidence
      Source: <url>
      Action: Update description / add source

- [ ] **New: <Capability Name>** · Low confidence
      Source: <url>
      Action: Add entry (excluded by default — check to include)

### gemini-cli (N leads)
...

### No leads
- vscode-copilot: No new developments found

Step 4: Validate

Before creating the PR, run:

python3 framework/scripts/validate_framework.py

Fix any errors before committing.

Revise Mode

When someone comments @copilot revise on a research PR:

1. Re-read the PR description to see which items are checked/unchecked
2. Remove commits/changes for unchecked items
3. Apply any inline edits the reviewer made (corrected URLs, descriptions)
4. Re-run python3 framework/scripts/validate_framework.py
5. Push the updated commits

Schema Reference

Each capability entry in current.json must have:

{
  "category": "<one of: code-completion, code-generation, chat-assistance, code-explanation, code-refactoring, testing, debugging, documentation, command-line, multi-file-editing, context-awareness, language-support, ide-integration, api-integration, customization, security, performance, collaboration, model-selection, agent-orchestration, observability>",
  "name": "Capability Name",
  "description": "What this capability does, in 1-2 sentences",
  "available": true,
  "tier": "<free|pro|business|enterprise>",
  "maturityLevel": "<experimental|beta|stable|deprecated>",
  "status": "active",
  "sources": [
    {
      "url": "https://...",
      "description": "Brief source label",
      "verifiedDate": "YYYY-MM-DD",
      "sourceGranularity": "<dedicated|section|excerpt>",
       
    
  

Adding a New Agent

If you discover a new AI coding agent worth tracking:

1. Create the directory: agents/<agent-name>/capabilities/
2. Create current.json with the agent info and initial capabilities
3. Create agents/<agent-name>/docs-registry.json listing authoritative doc sources
4. Run python3 framework/scripts/validate_framework.py to confirm schema compliance
5. Mark this lead as "New agent" in the PR description with Low confidence

Important Rules

• NEVER fabricate capabilities. Every lead must cite a real, accessible source URL.
• Verify all source URLs return HTTP 200: curl -Is URL | head -1
• Pre-uncheck low-confidence leads so the reviewer must opt in.
• When adding a source with sourceGranularity: "excerpt", include a verbatim 50-300 character quote from the page.
• Commit messages: research: add <capability> to <agent> or research: update <capability> for <agent>