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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds genuinely new behavioral context: the units of mean_return/median_return/positive_share (fractions, 0.0125 = 1.25%), the meaning of n and of p_adjusted as multiple-comparison-corrected, and an interpretive constraint that nominally significant effects must not be presented as regularities. That is substantive guidance beyond structured fields.

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?

It is a dense single block but front-loads the core purpose, then scope, then usage, then units, then caveat. Nearly every sentence earns its place, though the family/code enumeration slightly overlaps the schema and could be trimmed.

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 read-only statistics tool with an output schema, the description covers everything needed: what it returns conceptually, how to read the numeric fields, and how to interpret significance. Nothing an agent needs in order to call or interpret it correctly is missing.

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 already documents code, family and subject including the 'omitted — all' default and the weekday_1 = Monday example. The description largely repeats that (family list, code examples), adding little syntax or semantics beyond what the schema provides, so the baseline 3 applies.

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 (calendar effects computed from history) and enumerates the exact scope: subjects IMOEX/RGBITR and the five effect families with their code prefixes. An agent can distinguish this from siblings like analysis_by_ticker or get_indicator without opening any 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?

It gives concrete trigger phrasings ('is there a January effect', 'are Mondays weak', 'what happens around rate decisions') and an explicit exclusion ('Do not use it for a forecast or for one stock'), which is exactly the when/when-not/alternative routing an agent needs.

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