get_statement_summary

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds that output is organized by a `role` column with named values (total_assets, equity, revenue, ebit, net_income), which goes slightly beyond annotations, but since an output schema exists this is largely redundant and no scope caveats, defaults behavior, or data-freshness context are given.

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?

Two short sentences, front-loaded with the core purpose and then the return shape; no wasted phrasing. The parenthetical role list is slightly verbose but directly informative.

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?

With an output schema, annotations, and full schema parameter coverage, the description supplies enough to call the tool correctly. However, for a six-parameter tool with optional depth/doc_type/data_type knobs, it gives no orientation on how those shape the result, leaving the agent to rely entirely on structured fields.

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 all six parameters are documented in the schema, making 3 the baseline. The description adds the notion of a 'company-year' key that maps loosely to cvm_code plus year, but it does not clarify depth levels, doc_type composition, or the con/ind versus dfp/itr distinction.

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 states a specific verb+resource: a compact headline view of one company-year's statement totals (equity, revenue, profit). It implicitly differentiates itself from get_financial_statements by emphasizing 'compact headline' versus a full statement tool, though that contrast is never made explicit.

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?

There is no explicit when-to-use or when-not-to-use guidance and no sibling is named as an alternative. The agent must infer from 'compact headline view' that this is the lightweight counterpart to get_financial_statements, and must infer the depth/doc_type/data_type tradeoffs from the schema alone.

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