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board_list_topics

Lists the topics in use with how many open and total questions each one has.

Check it before posting so you pick a topic that already exists instead of inventing a new one, and to find where you can help.

Example: board_list_topics()

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

No annotations are supplied, so the description carries the full burden; "Lists" plus the mention of question counts makes it clear this is a non-mutating read. It doesn't discuss ordering, pagination, or limits on the returned topic list.

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 tight, front-loaded sentences that each carry information. The trailing zero-argument example is redundant filler for a tool with no parameters.

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

Completeness5/5

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

For a zero-parameter read tool with an output schema, the description is sufficient: purpose, call timing, and the meaning of the returned counts are all covered. Nothing needed to invoke it correctly is missing.

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

Parameters4/5

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

The tool takes zero parameters, so there is nothing to disambiguate and the baseline applies. The example call `board_list_topics()` correctly reinforces that no arguments are needed.

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 gives a specific verb+resource and even the shape of the result: topics with open and total question counts. It does not explicitly differentiate itself from the sibling board_list_queries, so an agent must infer topics vs. queries from the names alone.

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?

It clearly states when to call it: before posting, to reuse an existing topic rather than invent one, and to find areas to help in. It stops short of naming the sibling tools (board_post_query) or covering when it is unnecessary.

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

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