peaka_get_table_statistics

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds meaningful behavior beyond that by disclosing that distinctFraction is an 'estimated fraction' and that the response includes table identifiers. 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?

The description is two tight paragraphs with no filler. The first front-loads purpose and output semantics; the second provides a practical agent instruction about projectId discovery. Every sentence earns its place.

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 description adequately covers return values and the projectId prerequisite, which is important given there is no output schema. However, with four required parameters and 25% schema coverage, the lack of input semantics for catalogId/schemaName/tableName leaves a meaningful gap, and error/edge-case behavior is unaddressed. It is workable but not fully 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 description coverage is only 25%, with only projectId documented in the schema. The description mentions catalog/schema/table identifiers in the output but gives no guidance on the meaning or format of catalogId, schemaName, or tableName as inputs. It only adds workflow context for projectId, so it fails to compensate for the low coverage.

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 uses a specific verb-resource pairing, 'Get column-level statistics for a table,' and spells out the exact return contents (catalog/schema/table identifiers and distinctFraction). This clearly separates it from sibling tools that list tables or columns, so an agent can distinguish it without opening the schema.

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 states that the tool is 'useful for cardinality estimation and query optimization,' providing explicit usage context. It also gives a concrete prerequisite workflow: if projectId is unknown, call peaka_list_projects and ask the user. It stops short of naming alternative tools or saying when not to use it, so it doesn't earn a 5.

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