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

Annotations already declare readOnlyHint and destructiveHint, and the description adds critical behavioral nuance: cash-flow figures are cumulative (year-to-date) while income-statement figures are per-quarter, with an explicit warning against diffing adjacent columns. It also discloses the company_type fallback behavior, entity-level scope, and the CSV/candidates return format—substantially more context than the annotations provide.

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 compact and front-loaded: the first sentence states the main purpose, the second delivers a critical usage warning, and the third covers output format and ambiguity handling. Every sentence earns its place with no filler or repetition.

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?

For a tool with no output schema, the description precisely explains the return format, including the column structure and ambiguity fallback. It also covers quarterly granularity, entity-level scope, and company_type fallback logic, providing an agent with everything needed to invoke the tool correctly.

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 the schema fully documents symbol, statement, and company_type. The description adds some high-level context about statement types and output structure, but it does not add significant parameter-level meaning beyond the schema, so the baseline 3 is appropriate.

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 the exact verb ('Get'), resource (one financial statement), scope (CSE symbol), and granularity ('full line-item detail, one row per line item'). It explicitly names the three statement types, making it distinguishable from sibling data tools.

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 clearly defines the tool's domain (financial statements) and the type of data returned, giving sufficient context for when to use it. It does not explicitly name alternative tools or exclusions, but no sibling tool overlaps with this function, so clear context without exclusions is acceptable.

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