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

Annotations only declare readOnly/openWorld/idempotent, so the description carries the real behavioral load and does so well: it discloses data redaction (emails omitted, only display names), truncation (requires_dist capped), yank-status reporting, and the entire payment model (x402 USDC on Base, $0.002 per successful call, PaymentRequired object returned on unpaid calls). That is substantial context an agent cannot get from the 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?

Front-loaded with the usage trigger, then a tight field enumeration, then redaction and payment caveats — every clause carries information. The field list reads as a dense run-on, which slightly blurs scanability but not at the cost of wasted content.

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 compensates by enumerating the returned fields, and it covers privacy (email redaction), data capping (requires_dist), and billing/auth behavior. An agent has everything needed to decide to call it and to interpret the response.

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?

There is a single `name` parameter with 100% schema description coverage, so the schema already documents it fully. The description adds no syntax, format, or normalization guidance beyond what the schema provides, which is the baseline-3 case for high coverage.

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?

Names a specific verb-like action (fetch the public PyPI project card) and enumerates exactly which fields are returned, which cleanly separates it from the release-level sibling pypi_release and the search siblings. An agent can identify the resource and scope without opening the 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?

"Use when you need the public PyPI project card" gives a clear triggering condition. It does not, however, name alternatives (e.g. pypi_release for version-level data or pypi_search for discovery) or state when NOT to use it, so routing between siblings is left to inference.

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