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AGENTS.md

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AGENTS.md

This repository contains AI agent skills for building with Agora — covering RTC, RTM, Conversational AI, server-side tokens, and Cloud Recording.

Repository Structure

skills/
├── scripts/validate-skills.sh
└── skills/
    └── agora/                       # Skill root
        ├── SKILL.md                 # Entry point, product index
        ├── intake/SKILL.md          # Intake router for vague requests
        └── references/
            ├── mcp-tools.md         # MCP tool reference + freeze-forever table
            ├── rtc/  rtm/  conversational-ai/  server/  cloud-recording/

4-Layer Progressive Disclosure

Layer What Size When Loaded
1 — Description Trigger keywords in SKILL.md frontmatter ~100 words Always (skill index)
2 — SKILL.md body Core concepts, product index, framework notes ~72 lines On activation
3 — Product README Overview, critical rules, topic links 20–100 lines Per product
4 — Topic files Implementation detail, code examples, API reference 34–500 lines Per topic

Freeze-Forever Rule

Ask: will this still be correct in 6 months without any updates? If yes, put it inline. If no, route to MCP or an external link. See skills/agora/references/mcp-tools.md for the full decision table.

Naming Conventions

  • Directory names: lowercase kebab-case
  • Use agora- prefix for new product skill directories
  • Never use shengwang- prefixes

Adding a New Product

  1. Create skills/agora/references/{product}/README.md (Layer 3 — 20–100 lines)
  2. Add an entry to the Products section of skills/agora/SKILL.md
  3. Create topic files: skills/agora/references/{product}/{topic}.md (Layer 4 — 34–500 lines)
  4. Apply the freeze-forever test to all inline content
  5. Add at least one eval case to tests/eval-cases.md

Validation

bash scripts/validate-skills.sh