run_aggregate_check

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

No annotations are provided, so the description must carry the burden. It only states it compares aggregates but does not disclose behavioral traits like read-only, side effects, or performance implications. More detail is needed.

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 with three sentences, each earning its place: purpose, prerequisites, and usage. It front-loads the core function.

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 5 parameters, nested objects, no output schema, and no documentation of return values. The description only covers prerequisites and usage timing, missing details on source/target objects and partition_config.

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%, with only 'columns' having a brief description. The description adds context for the aggregates parameter by listing the options, but source, target, and partition_config remain underspecified. Baseline 3 is appropriate as it adds some value but not enough.

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 'Compare' and the resource 'column-level aggregates', specifying the aggregate functions. It distinguishes from sibling tools like run_row_count_check or run_schema_check.

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 provides explicit prerequisites (validate_table_exists, validate_columns_exist) and usage guidance ('After row counts match, to verify numeric data integrity'). It does not mention when not to use it, but the guidance is sufficient.

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