gograph_hotspot

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

Annotations already indicate read-only, idempotent, non-destructive. The description adds value by explaining freshness checks, graph retry logic, and test exclusion rationale. No contradictions with annotations.

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 well-structured with clear sections (purpose, technical details, parameters, usage, returns). Minor redundancy but overall efficient. Every sentence adds value.

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, but description explicitly states returns: ranked list with function name, fan-in count, and package location. Covers behavioral nuances (freshness, test inclusion) completely for a 2-param tool.

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%, so baseline is 3. The description adds context beyond schema, such as default values and the reason for excluding tests ('test helpers don't dominate'). This extra context justifies a 4.

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 the tool ranks functions by incoming call count (fan-in) to identify most-depended-on symbols, with a specific verb and resource. It distinguishes from siblings by mentioning alternatives like gograph_focus, gograph_coupling, and gograph_complexity for other use cases.

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?

Explicit 'WHEN TO USE' and 'NOT TO USE' sections guide the agent, with direct references to sibling tools for alternative metrics. Default behavior for include_tests is also explained, providing clear context on when to set it.

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