datasets_github_users_nearby

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

No annotations are provided, so the description carries the burden. It discloses that results are sorted by distance and that the dataset is 'enriched' GitHub users, which adds context. However, it doesn't mention pagination behavior, result limits, or whether the search is read-only, though the schema's page/page_size hints at pagination.

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

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

The description is two sentences, front-loading the core action and resource, then adding the dataset and enum context. It is efficient with no wasted words, though the enum listing could be considered redundant with the schema.

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

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

For a geospatial search tool with 8 parameters and no output schema, the description covers the core behavior (nearby, sorted by distance) but omits details like result format, pagination semantics, and the meaning of 'enriched'. The schema covers parameters, but the description doesn't fully compensate for the lack of output schema and behavioral details.

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

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 all 8 parameters. The description adds the enum values for influence_tier and the dataset id, but these are also present in the schema. It doesn't add meaning beyond the schema, so baseline 3 is appropriate.

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

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

The description states a specific verb ('Search') and resource ('nearby GitHub users'), and clarifies it operates on the 'github-users' dataset. It distinguishes itself from sibling tools like datasets_github_users_search and datasets_github_users_item by focusing on geospatial proximity, though it doesn't explicitly name those siblings.

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

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

The description implies usage context: use this when you need GitHub users near a coordinate, sorted by distance. It does not explicitly state when not to use it or name alternatives like datasets_github_users_search for non-geographic queries, leaving some inference to the agent.

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