Analyze rerank score distribution

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

Annotations already declare readOnlyHint=true. The description adds value by specifying the data source (mcpg_rag.rerank_events), the computation details (equal-width histogram, top-decile share), and the advisory finding logic (score_clustering warning). This provides useful behavioral context beyond the 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?

The description is concise (three sentences), front-loads the main action, and each sentence adds essential information. There is no redundancy or unnecessary detail.

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 five parameters, the description explains the core analysis, the source table, the advisory finding, and the return fields. With an output schema available, the description is complete enough for an agent to understand the tool's behavior and results.

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 only 20% (database parameter). The description adds meaning for 'days' (window) and 'n_buckets' (bucket count), but does not explain the 'model' or 'retrieval_index' parameters. It partially compensates for low coverage, but not fully.

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 it produces an equal-width histogram of cross_encoder_score values and calculates the top-decile share, distinguishing it from sibling analysis tools that focus on other metrics (distance, recall, etc.). The verb 'analyze' is specific to this resource.

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 implies usage for rerank score distribution analysis and flagging score clustering, but provides no explicit guidance on when to choose this tool over the many sibling analysis tools. It does not mention when not to use it or suggest alternatives.

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