trending_signal

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

No annotations provided, so description carries full burden. It discloses cost ($0.02 USDC on Base mainnet) which is helpful, but does not explicitly state whether the tool is read-only or has side effects. The use case suggests safe querying, but the description could be more explicit.

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 three sentences: core purpose, detection details, and cost. No redundant words, front-loaded with main action, and efficiently provides context.

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 single-parameter detection tool, the description covers main functionality, detection targets, and cost. No output schema is provided, but the description implies the tool returns a list of repos with signals. Some detail about output structure would improve completeness.

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 100% for the single parameter 'days' with enum values and description. The description adds no new semantic information beyond what the schema already provides, so baseline score of 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?

Description explicitly states the tool finds GitHub repos with anomalous star velocity as early signals, and lists specific detection cases (viral repos, fork surges). This clearly distinguishes it from sibling tools like github_watch or repo_scan by focusing on trending anomalies.

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?

Description mentions use cases (trend hunting, VC scouting) and emphasizes 'early signals before mainstream discovery,' implying when to use. It does not explicitly compare to alternatives or state when not to use, but context from siblings and tool name provides some guidance.

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