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get_topic
Read-only

All sources (llms.txt, docs, MCP servers, skills, rules), detection signals and the role of one tool, by id such as vercel, nextjs or drizzle.

Input Schema

NameRequiredDescriptionDefault
idYesTopic id, as returned by search or list_topics

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description usefully enumerates the categories of data returned, which matters since there is no output schema, but says nothing about behavior on an unknown id, response size, or whether full content versus summaries are returned.

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?

A single compact sentence with no filler. It is slightly front-loaded on return contents rather than the action, and 'the role of one tool' is an awkward phrase, but nothing is wasted.

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?

For a one-parameter read lookup with no output schema, the description does the minimum-plus job of listing what comes back. It leaves open what a topic actually represents and what happens when the id is not found, which an agent may need to know before calling.

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?

Schema coverage is 100%, so the baseline is 3; the description earns above that by supplying example id values (`vercel`, `nextjs`, `drizzle`), which reveal the expected lowercase slug convention better than the schema's generic 'Topic id' text.

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 names the resource (a topic, identified by id) and enumerates what the response contains: sources such as llms.txt, docs, MCP servers, skills and rules, plus detection signals. Concrete example ids (`vercel`, `nextjs`, `drizzle`) make the resource type tangible. It falls short of 5 because it never contrasts with siblings list_topics/search, and the phrase 'the role of one tool' is ambiguous about whether a topic is a tool or a technology.

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: the requirement that an id be supplied suggests the lookup pattern (find an id via search or list_topics, then fetch details here), but the description itself states no when-to-use rule and names no alternative. An agent must infer the search-then-get workflow.

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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