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

With no annotations, the description carries the burden, and it explains the response is intentionally small ('Registries answer with hundreds of kilobytes; this returns only the facts'), implying a read-only call. It also discloses the cost ($0.005 USDC) and payment route (x402 on Base). It does not cover failure cases like unknown packages, but the disclosed behavior is still strong.

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?

Three sentences, each pulling weight: the first defines scope and outputs, the second gives usage timing, the third justifies the filtered response and pricing. Purpose information is front-loaded before cost/performance notes.

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 simple two-parameter lookup with no output schema, the description covers the returned facts, the use cases, and the cost model. A minor gap is that it doesn't specify the response shape or behavior for unknown packages, but these are not critical for selecting and invoking the tool correctly.

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%, and the schema already documents both parameters with examples and allowed ecosystem values. The description's mention of the three registries reinforces ecosystem choices but adds no new parameter syntax or constraints, so it merits the baseline 3.

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 opens with an explicit action ('Look up a package') and resource scope ('npm, PyPI or crates.io') and enumerates the exact facts returned: latest version, licence, deprecated/yanked status, last publish date, dependency count, and repository. This clearly separates it from siblings like package_audit and package_vulnerabilities, which imply broader analysis rather than a quick registry facts lookup.

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 triggers: 'Use before writing a dependency line, or to check whether a pinned version is behind.' This is clear when-to-use context, but it never names sibling tools as alternatives or states when not to use it, so it falls short of explicit exclusion guidance.

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