search_github_code

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only mentions using the 'GitHub Code Search API', but does not disclose rate limits, authentication needs, error behavior, or limitations on result content. The Return section describes structure but lacks operational details.

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 concise and well-structured: a one-line purpose, API source, use cases, and a clear Args/Returns block. Every element contributes without redundancy.

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?

Despite no output schema, the description includes a Return structure defining fields. However, it lacks details on pagination, total count, error handling, and how it differs from the sibling search_github tool, which could be relevant for selection.

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 0%, so the description compensates by adding value: it provides an example for query ('openai client lang:python') and specifies a range for max_results (1-100). This adds meaningful context beyond the schema property names.

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 clearly states 'Поиск кода на GitHub' (Search code on GitHub), identifying the specific verb and resource. It distinguishes the tool from siblings like search_github (repos) and search_github_issues by focusing on code, and provides example use cases (code examples, libraries, utilities).

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 explicitly notes suitability for searching code examples, libraries, and utilities, giving contextual guidance. However, it does not provide negative guidance (when not to use) or explicitly compare to siblings, though the resource differentiation is implied.

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