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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds real value: the response is byte-for-byte what a paid call returns, so results mirror production. It omits any note on sample size or truncation, which matters for a preview tool.

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 sentences, no filler. The core value proposition leads, and the workflow detail (where to get the endpoint key) follows as supporting information.

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 one-parameter tool with no output schema, the definition supplies the essentials: what comes back, how to obtain the argument, and why you'd call it. Only the absence of any statement about response size or preview limits leaves a small gap.

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% with a 24-value enum, so the schema does most of the work. The description still adds provenance by naming list_endpoints as the authoritative source of valid keys, though its inline examples duplicate enum values already visible in the schema.

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?

States a specific verb and outcome: fetch a real paid-endpoint response for free to inspect structure and coverage before paying. It is clearly distinct from list_endpoints (which supplies the key) but never mentions how it differs from the sibling get_free_series, which plausibly offers overlapping free data.

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?

Gives a clear when-to-use rule: run this before paying to validate fields, dates and coverage. It also implies the prerequisite workflow by pointing at list_endpoints for the key. It stops short of stating exclusions, e.g. when to prefer get_free_series or how often sampling is appropriate.

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