docs: add developer and api reference tabs (#190)

* docs: add developer and api reference tabs

* fix: remove duplicate image

docs/core-concepts/context-and-variables.mdx

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+---
+title: "Context & Variables"
+description: "How data flows into, through, and out of a conversation"
+---
+
+Dograh has a simple data model for passing information through a call. Understanding it is key to building agents that feel personalised and to extracting useful results after a call.
+
+## The three context objects
+
+```
+initial_context ──► Agent ──► gathered_context
+                       │
+                 [template variables](/voice-agent/template-variables)
+                 (used in prompts)
+```
+
+### initial_context
+
+Data available to the agent before the call starts — the contact's name, account details, appointment information, anything the agent should know upfront. It can be set from several places:
+
+- **API trigger** — pass it in the request body when calling `POST /public/agent/{uuid}` or `POST /telephony/initiate-call`
+- **Campaign CSV** — columns beyond `phone_number` automatically become `initial_context` fields for each contact's call
+- **Dashboard** — set default template context variables on the agent, used when no external context is provided
+
+```json
+{
+  "phone_number": "+14155550100",
+  "initial_context": {
+    "customer_name": "Jane Smith",
+    "plan": "premium",
+    "renewal_date": "April 1"
+  }
+}
+```
+
+### Template variables
+
+Values from `initial_context` are available in your agent's prompt using `{{double_brace}}` syntax.
+
+```
+You are calling {{customer_name}} about their {{plan}} plan,
+which renews on {{renewal_date}}. Be friendly and confirm
+whether they'd like to continue.
+```
+
+When the call starts, Dograh substitutes the values before sending the prompt to the LLM — so the agent speaks naturally as if it already knows the contact.
+
+### gathered_context
+
+Data the agent collects *during* the call. You configure what to extract in the agent node's extraction settings — each variable has a name, type, and a prompt that tells the LLM what to look for.
+
+<img src="../images/extracted_variables.png" alt="Extracted variables" style={{border: "1px solid #d1d5db", borderRadius: "8px", maxWidth: "100%"}} />
+
+`gathered_context` is returned in the run record after the call completes and is available in [webhook payloads](/developer/webhooks) for downstream processing.
+
+## Data flow example
+
+```mermaid
+sequenceDiagram
+    participant App as Your System
+    participant Dog as Dograh
+    participant LLM as LLM
+
+    App->>Dog: initial_context: {customer_name: "Jane", plan: "premium"}
+    Dog->>LLM: Prompt with {{customer_name}} and {{plan}} substituted
+    LLM-->>Dog: Conversation response
+    Note over Dog,LLM: Call progresses...
+    Dog->>LLM: Extract: did the customer confirm renewal?
+    LLM-->>Dog: gathered_context: {renewal_confirmed: true}
+    Dog-->>App: Run record with gathered_context
+```
+
+## Where variables are available
+
+| Location | Variables available |
+|---|---|
+| Agent node prompts | `initial_context` fields via `{{variable_name}}` |
+| Edge conditions | Evaluated against the live conversation — no explicit variable syntax needed |
+| Webhook payload templates | All context objects via `{{initial_context.field}}`, `{{gathered_context.field}}` etc. |
+| Campaign CSV columns | CSV columns beyond `phone_number` become `initial_context` fields automatically |