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

Beyond the annotations (non-read-only, open world), the description discloses key behavioral traits: it returns a one-hour download URL instead of raw bytes, the last three days are rebuilt nightly, and it includes rows, bytes, and sha256 in the response. This addresses expected return format, data freshness, and integrity verification, which are critical for a paid data 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?

The description is long but information-dense, packing essential details (price, usage, input, data contents, return behavior) into a structured flow. It front-loads the purpose and explicitly states exclusions. While not minimal, every sentence earns its place, making it appropriately sized for a complex commercial dataset tool.

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 one parameter, no output schema, and a paid transaction, the description covers all necessary aspects: what data is included, how to get a free sample, the exact input format, return details, and update cadence. An agent has everything needed to call the tool correctly without additional lookups.

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?

The schema already fully describes the single parameter ('day') with format and source, achieving 100% coverage. The description repeats the same info ('UTC, YYYY-MM-DD, from the free HTTP index') without adding new meaning. Since schema coverage is complete, a baseline of 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 clearly states the tool's purpose: buying a day's worth of pump.fun launch data for backtesting or model training. It names the specific resource (UTC day dataset) and distinguishes it from live-decision tools by explicitly saying 'not for live decisions'. The title also reinforces the action, and the description provides concrete details about the data content and size.

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 explicitly states when to use the tool (backtesting/training) and when not to use it (live decisions), naming alternatives ('the compact check or the delta feed'). It also instructs the user to select the day from the free HTTP index, giving clear context for parameter selection. No ambiguity remains about when this tool is appropriate.

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