search_github

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

Discloses rate limits with and without token (60 vs 5000 req/h) and mentions using GitHub REST API v3. No annotations were provided, so the description carries the full burden of behavioral disclosure and does so effectively.

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?

Description is front-loaded with purpose, then rate limits, usage, and parameter details. Every sentence adds value, though the args section could be tighter. No wasted words.

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?

Given the presence of sibling tools and no output schema, the description adequately explains the tool's scope (repos), auth requirements, and return structure (SearchResponse fields). Sufficient for an agent to decide and invoke correctly.

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 has 0% description coverage, so description compensates by explaining query supports qualifiers (language:python, stars:>100, topic:ai) and max_results range 1-100. Adds meaning beyond bare schema.

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?

Description starts with 'Поиск репозиториев на GitHub' (Search repositories on GitHub), a specific verb+resource pairing. It distinguishes from sibling tools like search_github_code and search_github_issues, which target code or issues instead of repos.

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?

Explicitly lists suitable use cases: 'поиск open-source решений, анализ аналогов, мониторинг трендовых проектов' (open-source solutions, alternatives analysis, trend monitoring). Does not state exclusions or when not to use, but the context is clear.

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