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

Beyond the annotations (which already declare readOnly/idempotent/non-destructive/openWorld), the description discloses rich behavior: restatements are never leaked into earlier dates, missing fields go into unavailable_fields rather than being zero-filled, and source/quality/limitations are returned. It also states the data universe (US SEC filers, annual only) and that it is not investment advice.

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?

Dense but well structured: purpose, inputs, return shape, and the anti-look-ahead rationale are front-loaded, and every sentence carries information. It is on the longer side, with some redundancy between the opening clause and the later 'not investment advice' disclaimer, but nothing is filler.

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 no output schema, the description carries the burden and does so: it enumerates the returned metrics (revenue, net income, diluted EPS, total assets, liabilities, operating cash flow), the temporal fields (data_time, publication_time), the unavailable_fields behavior, and the auxiliary source/quality/limitations. An agent has everything needed to call and interpret the result.

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 coverage is 100%, so the baseline is 3, but the description adds interpretation beyond the schema: as_of is not just a date format but the point-in-time cutoff determining which filings were public, and the symbol is constrained to US-listed companies. It leaves api_key and marketplace_license_key to the schema, which 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 gives a specific verb+resource (returns point-in-time company fundamentals) and precisely scopes it: annual SEC 10-K figures for a US-listed symbol on a given as_of date. It clearly distinguishes itself from the sibling analytics tools (market map, sentiment, technical analysis, events, feed), none of which return per-company point-in-time financials.

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 states the concrete use case and the condition that selects it ('for a symbol and an as_of date ... avoids look-ahead bias in backtests and research'), so an agent knows this is the correct tool when historical, as-of fundamentals are needed. It does not explicitly name alternatives or exclusions (e.g. non-US filers, quarterly data), but the 'US SEC filers, annual data only' note effectively sets boundaries.

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