ThinkNEO Control Plane

thinkneo_start_trace

Start a new agent observability trace. Creates a session that tracks all tool calls, model calls, decisions, and errors for an AI agent run. Returns a session_id to use with thinkneo_log_event and thinkneo_end_trace. Requires authentication.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`metadata`	No	Optional dict with additional context (e.g., {"task": "email-draft", "user_id": "u123"})
`agent_name`	Yes	Name of the agent being traced (e.g., 'marketing-agent', 'support-bot')
`agent_type`	No	Type of agent: 'assistant', 'autonomous', 'workflow', 'pipeline', or 'generic'	generic

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed5 schema fields changedJun 26, 2026

addedInput schema / properties / agent_name

Added value: +{
+  "description": "Name of the agent being traced (e.g., 'marketing-agent', 'support-bot')",
+  "title": "Agent Name",
+  "type": "string"
+}

addedInput schema / properties / agent_type

Added value: +{
+  "default": "generic",
+  "description": "Type of agent: 'assistant', 'autonomous', 'workflow', 'pipeline', or 'generic'",
+  "title": "Agent Type",
+  "type": "string"
+}

addedInput schema / properties / metadata

Added value: +{
+  "anyOf": [
+    {
+      "additionalProperties": true,
+      "type": "object"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Optional dict with additional context (e.g., {\"task\": \"email-draft\", \"user_id\": \"u123\"})",
+  "title": "Metadata"
+}

removedInput schema / properties / operation

Removed value: -{
-  "default": "ai_request",
-  "description": "Name of the operation being traced",
-  "title": "Operation",
-  "type": "string"
-}

addedInput schema / required
```
Added value: +[
+  "agent_name"
+]
```

Changed5 schema fields changedMay 11, 2026

removedInput schema / properties / agent_name

Removed value: -{
-  "description": "Name of the agent being traced (e.g., 'marketing-agent', 'support-bot')",
-  "title": "Agent Name",
-  "type": "string"
-}

removedInput schema / properties / agent_type

Removed value: -{
-  "default": "generic",
-  "description": "Type of agent: 'assistant', 'autonomous', 'workflow', 'pipeline', or 'generic'",
-  "title": "Agent Type",
-  "type": "string"
-}

removedInput schema / properties / metadata

Removed value: -{
-  "anyOf": [
-    {
-      "additionalProperties": true,
-      "type": "object"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "description": "Optional dict with additional context (e.g., {\"task\": \"email-draft\", \"user_id\": \"u123\"})",
-  "title": "Metadata"
-}

addedInput schema / properties / operation

Added value: +{
+  "default": "ai_request",
+  "description": "Name of the operation being traced",
+  "title": "Operation",
+  "type": "string"
+}

removedInput schema / required
```
Removed value: -[
-  "agent_name"
-]
```

AddedApr 18, 2026

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds context beyond annotations by noting 'Requires authentication' and stating that it 'Creates a session' and returns a session_id. It also describes the tracking scope (all tool calls, model calls, decisions, errors). Annotations already indicate non-read-only, so no contradiction; the description complements them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the primary action, and includes only essential information: what it does, return value, companion tools, and authentication. Every sentence contributes value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simple role in the trace lifecycle and the presence of an output schema (not shown here but indicated), the description covers the key aspects: purpose, return, and next steps. It could mention cleanup or error handling, but for a start-trace tool it is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and each parameter already has descriptive text (agent_name, agent_type, metadata). The description adds no further parameter-specific guidance, so it stays at the baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Start a new agent observability trace. Creates a session...' It specifies the action (start), the resource (trace/session), and the context (tracks tool calls, model calls, decisions, errors). It also distinguishes from siblings by mentioning the returned session_id and the companion tools thinkneo_log_event and thinkneo_end_trace.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage as the first step in tracing, explicitly naming thinkneo_log_event and thinkneo_end_trace as subsequent tools. It does not explicitly state when not to use it or list alternative tools for different scenarios, but the companion-tool reference provides clear guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All ThinkNEO Control Plane tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.