Discover Schema

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds context about returning sample rows (not full data) and an optional filter, which adds behavioral insight beyond the annotations. It does not contradict annotations, and is consistent.

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, front-loaded with the main purpose and outputs, and provides usage guidance without unnecessary words. 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?

Despite no output schema, the description explains exactly what is returned (keys with row counts, sample rows). It also covers the workflow and usage context. For a simple tool with only 2 optional params, this is complete.

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 mentions 'Optional service filter' but doesn't add extra meaning beyond the schema description for 'since' (time window). Thus it adds marginal value.

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 verb 'Discover' and the resource 'shape of a data source', lists specific outputs (keys with row counts, sample rows), and distinguishes itself from siblings by pairing with list_services/list_metrics and outlining a workflow with search and save_query.

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?

It explicitly says 'Use to learn an unknown or newly-ingested source before querying it', pairs with list_services/list_metrics, and provides a sequence (search, then save_query). While it lacks explicit 'when not to use' or full alternatives, the guidance is strong and clear.

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