query_language_summary

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It states it is a 'daily rollup' and derives data from 'session language detection', which implies read-only aggregation. However, it does not explicitly confirm non-destructive behavior, describe the rollup logic, or specify what data is excluded. The description is minimal but non-contradictory.

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 a single, front-loaded sentence that conveys purpose and use case without wasted words. It is appropriately concise for a tool with 7 parameters already documented in the schema.

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?

The tool has no output schema and 7 parameters, yet the description does not explain the return format, aggregation method, or how filters affect the output. For a summary tool, this omission leaves agents uncertain about what data they will receive. The description is too sparse to fully compensate for missing structural metadata.

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 description coverage is 100%, so each parameter is well described in the schema. The tool description adds no additional parameter-level meaning beyond the schema. Baseline score of 3 is appropriate as the description does not duplicate or subtract value from the 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?

The description clearly states the tool provides a 'daily rollup per programming language' and its use case ('identify which languages AI assistants are most often working in'). It distinguishes from sibling tools like query_project_summary by focusing specifically on language detection, making the purpose unambiguous.

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 gives a clear usage context ('identify which languages') but does not explicitly mention when not to use this tool or suggest alternatives among siblings. It is adequate but lacks exclusionary guidance.

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