Rolli MCP

get_topic_tree

Retrieve a keyword search's conversation topic tree to see how topics and subtopics are distributed across search results.

Instructions

Get the conversation topic tree for a keyword search. Shows how topics and subtopics are distributed across the search results.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "search_id": "<search_id>"
    },
    "name": "get_topic_tree"
  }
}

Input Schema

Name	Required	Description	Default
`platform`	No	Filter by platform
`search_id`	Yes	Keyword search ID

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv1.5.0Nov 4, 2026
- removedInput schema / additionalProperties
```
Removed value: -false
```
- addedInput schema / properties / search_id / maximum
```
Added value: +9007199254740991
```

Changed1 schema field changedv1.4.0Aug 13, 2026

changedInput schema / properties / platform / enum

Previous value: -[
-  "twitter",
-  "bluesky",
-  "youtube"
-]New value: +[
+  "twitter",
+  "reddit",
+  "bluesky",
+  "youtube",
+  "facebook",
+  "instagram",
+  "threads"
+]

First observedv1.1.7Mar 18, 2026

TDQS

B3.2/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It implies a read-only 'Get' operation, but does not disclose permissions, whether the tree is computed or cached, how deep the hierarchy goes, or how the platform filter affects the result—all important context for a tool with zero annotation coverage.

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

Conciseness4/5

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

Two short sentences that are front-loaded with the core purpose and contain no filler. The second sentence adds a small but useful clarification of what the tree shows, though it could be slightly tighter.

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

Completeness3/5

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

With no output schema and no annotations, the description gives only a high-level sense of the return value (topics/subtopics distribution). It omits practical details an agent would want—such as return shape, tree depth, or how results relate to search_id—making it adequate but not fully complete for a tool of this nature.

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%, so the schema already documents search_id as the keyword search ID and platform as an enum filter. The description only loosely references the keyword search and says nothing about the platform parameter, so it adds no meaningful semantic detail beyond what the schema provides; a baseline 3 is appropriate.

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

Purpose4/5

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

The description pairs a specific verb ('Get') with a specific resource ('conversation topic tree for a keyword search') and explains what the tree represents (topics and subtopics distributed across results). This distinguishes it from siblings like get_keyword_search or get_keyword_search_posts, which retrieve raw search or posts, though it does not explicitly name those alternatives.

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

Usage Guidelines3/5

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

Usage is only implied: an agent can infer this follows a keyword search, but the description never states when to choose this over get_keyword_search, get_keyword_search_posts, or other search-related tools, nor does it mention prerequisites such as needing an existing search_id.

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