Agora Intake — Product Routing & Needs Analysis

First entry point for vague or multi-product Agora requests. This skill understands the full product landscape, identifies what the user needs, and routes to the right place.

Note: Skip-intake logic is defined in skills/agora/SKILL.md (root router). If you are here, the root router has already determined that intake is needed. Do NOT second-guess the routing decision — proceed with the intake flow below.

Product Landscape

Product	What it does	Typical user says
RTC SDK	Real-time audio/video between humans	"video call", "live streaming", "voice chat"
RTM	Real-time messaging / signaling	"chat", "messaging", "signaling", "notifications"
ConvoAI	AI voice agent (ASR→LLM→TTS over RTC)	"AI assistant", "voice bot", "conversational AI"
Cloud Recording	Record RTC sessions server-side	"recording", "archive sessions", "record calls"
Server/Tokens	Auth token generation	"token server", "authentication", "App Certificate"
Server Gateway SDK	Server-side media streaming (Linux)	"server SDK", "Linux SDK", "send audio from server", "server gateway"

Product Relationships

                    ┌─────────────┐
                    │   RTC SDK   │  ← foundation layer
                    └──────┬──────┘
                           │
          ┌────────────────┼────────────────┐
          │                │                │
    ┌─────┴─────┐   ┌─────┴─────┐
    │  ConvoAI  │   │  Cloud    │
    │ (AI Agent)│   │ Recording │
    └─────┬─────┘   └───────────┘
          │
    ┌─────┴─────┐
    │    RTM    │  ← often paired with RTC/ConvoAI
    └───────────┘

Key relationships:

ConvoAI depends on RTC — the AI agent joins an RTC channel; the client needs RTC SDK
Cloud Recording depends on RTC — records what happens in an RTC channel
RTM is independent but often paired with RTC or ConvoAI for signaling (call invitation, presence, chat history)

Common Product Combinations

Use case	Products needed
1v1 / group video call	RTC SDK
Video call + chat	RTC SDK + RTM
AI voice assistant	ConvoAI + RTC SDK (client)
AI voice assistant + chat history	ConvoAI + RTC SDK + RTM
Live streaming with recording	RTC SDK + Cloud Recording
Record AI conversations	ConvoAI + RTC SDK + Cloud Recording

Intake Flow

Step 1: Understand the Use Case

If the user's intent is not immediately clear, ask:

"What are you trying to build? Please describe the use case."

Listen for keywords and map to products using the Product Landscape table above.

Step 2: Identify Products

Based on the user's description, determine:

Primary product — the main capability they need
Supporting products — additional products required by the primary, or that enhance the use case
Optional products — nice-to-haves the user may not have considered

Use the Product Relationships and Common Combinations tables to make this determination.

Server-side disambiguation — "backend", "Python/Go/Node.js server", or "server-side" alone is ambiguous. Clarify which server role is needed before routing:

User says	They need
"authenticate users", "issue tokens", "token server"	Server/Tokens → `references/server/`
"start an AI agent", "call the ConvoAI API", "Python ConvoAI backend"	ConvoAI → `references/conversational-ai/`
"my server sends audio/video", "server joins RTC channel", "Linux media SDK"	Server Gateway → `references/server-gateway/`

If unclear, ask: "Does your server need to (a) generate auth tokens, (b) call the ConvoAI REST API to start agents, or (c) send/receive audio-video media directly?"

Example analysis:

User: "I want to build an AI customer service bot where users call in and an AI answers"

Primary: ConvoAI (AI voice agent)

Supporting: RTC SDK (client-side for user to join channel)

Optional: Cloud Recording (record conversations for QA), RTM (send chat transcript)

Step 3: Confirm with User

Present your analysis:

Needs Analysis:
─────────────────────────────────────
Use case:           [user's described use case]
Primary product:    [primary product]
Supporting:         [supporting products]
Optional:           [optional enhancements]
─────────────────────────────────────

Does this look right? Any adjustments needed?

Wait for user confirmation before proceeding.

Step 4: Route to Product Skill

For each identified product, route to its skill file:

Product	Product skill
ConvoAI	references/conversational-ai/README.md
RTC SDK	references/rtc/README.md
RTM	references/rtm/README.md
Cloud Recording	references/cloud-recording/README.md
Token generation	references/server/README.md
Server Gateway SDK	references/server-gateway/README.md

When multiple products are needed, run the primary product's skill first, then address supporting products in order.

Decision Shortcuts

For common patterns, skip the full intake flow:

User says	Shortcut
"video call" / "live stream" / "RTC"	→ `references/rtc/README.md` directly
"screen share" / "screen sharing"	→ `references/rtc/README.md` → `cross-platform-coordination.md`
"chat" / "messaging" / "signaling"	→ `references/rtm/README.md` directly
"voice bot" / "AI assistant" / "ConvoAI"	→ `references/conversational-ai/README.md` directly
"recording" / "record sessions" / "record calls"	→ `references/cloud-recording/README.md` directly
"generate token" / "token server" / "App Certificate"	→ `references/server/README.md` directly
"Server Gateway" / "Linux SDK" / "server sends audio"	→ `references/server-gateway/README.md` directly

agora-intake