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

Annotations already cover read-only/open-world/idempotent, so the description's job is incremental – and it delivers: page size of 30, result fields returned (description, stars, topics, owner type, dates), the exact-query echo, no star floor by default, and 'Free'. It stops short of stating rate limits or total-result caps beyond the 10-page ceiling.

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?

Capability and result shape are front-loaded, with usage and query-strategy advice following. It is a single dense run of clauses; splitting the strategy tips from the capability statement would improve scanability, but no sentence is filler.

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?

No output schema exists, yet the description enumerates the returned fields and pagination behavior, and all 9 optional parameters are covered by a high-coverage schema. An agent has everything needed to call it correctly and interpret the result.

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 coverage is already 89%, yet the description still adds real meaning: AND semantics for query ('every word must match, so use few'), the default sort of stars, and the absence of a star floor. That goes beyond the schema's per-field text rather than repeating it.

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?

States a specific verb (search) plus resource (GitHub repositories) and enumerates the filter axes (words, topic, language, owner org, stars, dates) and ordering. It is clearly distinguishable from siblings like search_people or analyze_github_user, and it names find_people_behind_repos as the natural follow-on.

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?

Gives concrete use cases (seed lists, role-relevant projects, small serious repos with no star floor) plus an explicit alternative heuristic: 'Topic searches are usually cleaner than keywords'. It also specifies the chaining step to find_people_behind_repos(repo=...), so an agent knows both when to pick it and what to do next.

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