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

The disclosure includes important behavioral traits beyond annotations: cost (2 credits), 30-min cache, Bearer auth, and data source. These are useful for an agent evaluating side effects and prerequisites. The annotations provide only openWorldHint and idempotentHint, so the description adds meaningful context, though it could mention rate limits or error behavior.

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 front-loaded: the first sentence summarizes the tool's role, and the second sentence packs detailed output specifications and operational metadata (source, cost, cache, auth). Every sentence earns its place, with no fluff or repetition of structured fields.

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 having no output schema, the description enumerates the exact data returned (top 30 repos with fields, top 15 AI/ML repos, aggregates, share) and gives operational constraints (cost, cache, auth). For a complex composed tool, this is very complete and leaves few unanswered questions.

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?

The tool has zero parameters, so the input schema is fully self-documenting (coverage 100% vacuously). Per the baseline, a 0-parameter tool gets a 4. The description correctly does not attempt to explain nonexistent parameters, and no additional semantic value is needed.

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 what the tool does: it returns a composed GitHub developer-attention snapshot with specific data (top 30 repos, top 15 AI/ML-focused repos, aggregates, and AI/ML share). The verb 'Returns' and explicit list of outputs distinguish it from sibling tools, which focus on other domains (e.g., climate, crypto, Hugging Face).

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 provides clear context for when to use the tool: when needing GitHub trending/velocity data with AI/ML focus. It mentions the source (GitHub Search API), cost, cache, and auth requirements, which help the agent judge operational fit. However, it does not explicitly state when not to use it or name alternatives, so it misses the explicit exclusion criterion.

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