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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds a meaningful behavioral guarantee: mismatched source concepts or missing history will never be coerced into comparable numerical values. It also signals USD and provenance expectations, which are not present in the 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?

Two terse sentences convey the operation, constraints, and an important negative guarantee with no filler. The primary limits are front-loaded, and every clause adds value beyond the schema.

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 only two required parameters, a targeted description, strong annotations, and an output schema, an agent can construct a valid call without guessing. The main remaining gap is explicit alternative routing, but that is more of a usage-guidance issue than a blocker to correct invocation.

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 descriptions are absent (0% coverage), and the description compensates with key constraints: symbols must represent two to six companies, period_end is a single quarter-end date in YYYY-MM-DD format, and the comparison is in USD history terms. It does not explicitly say symbols are tickers, but the core invocation constraints are clear.

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 identifies the operation: comparing reported company quarters across multiple companies. The title and phrase 'reported company quarters' distinguish it from sibling tools like compare_company_revisions and check_company_forecasts, which target different data types.

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?

Usage is implied: this tool is appropriate when an agent needs to compare historical reported quarter data across two to six companies. However, it never explicitly says when not to use it or points to a sibling alternative, leaving some routing to inference from tool names.

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