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Search GitHub topics

github_search_topics
Read-onlyIdempotent

Search GitHub topics. Read-only: returns public data and changes nothing. Costs 1 credit per request.

Input Schema

NameRequiredDescriptionDefault
countYesNumber of results to return (1–10). Defaults to 10.
queryNoFree-text search terms, matched against the default fields for this search type, e.g. "web framework".
startNoNumber of results to skip (0–999). Defaults to 0. Only the first 1,000 results of a search can be paged through.
createdNoFilter by topic creation date. Provide any of gt / gte / lt / lte as YYYY-MM-DD dates; combine a lower and upper bound for a range.
curatedNoOnly curated topics. Maps to `is:curated`.
featuredNoOnly featured topics. Maps to `is:featured`.
repositoriesNoFilter by number of repositories using the topic. Provide any of gt / gte / lt / lte; combine a lower and upper bound for a range.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

The annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint, so the sentence 'Read-only: returns public data and changes nothing' largely restates structured data. The one genuinely new behavioral fact is the cost ('1 credit per request'), which is not captured in annotations and is useful for planning; nothing is said about result caps, rate limits, or page size.

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?

Three short sentences, front-loaded with the action, with no filler. The cost sentence earns its place because it is not derivable from structured fields, though the read-only sentence is largely redundant with annotations.

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 7-parameter search tool with nested objects and no output schema, the description is complete on identity and safety but silent on result shape, the 10-per-page and 1,000-result paging ceilings (only implicit in the schema), and how topics are matched. It is minimally adequate rather than thorough.

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% across all 7 parameters, including nested date-range and repository-count bound objects, so the schema fully carries parameter meaning. The description adds no filtering syntax, default behavior, or interpretation beyond what the schema already states; baseline 3 applies.

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?

States a specific verb and resource ('Search GitHub topics') that is unambiguous and distinguishes it from sibling searches like github_search_repositories or github_search_code by resource type. It does not explicitly contrast with those siblings, but the named resource is distinct enough for an agent to select correctly.

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

Usage Guidelines2/5

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

There is no guidance on when to use this rather than github_search_repositories, github_search_code, or any other sibling search tool. The only implicit signal is the word 'topics'; no exclusions, prerequisites, or alternative routing are offered.

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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