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

Annotations already declare readOnlyHint=true, and the description goes beyond that by thoroughly explaining the x402 payment model: unpaid calls return MCP PaymentRequired, retry with _meta['x402/payment'], and failure closed when economics are unavailable. This is precisely the kind of behavioral context the description should provide to complement the annotations. No contradiction.

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 3 sentences and each carries distinct value: purpose, usage priority, and payment behavior. It is front-loaded with the core purpose and keeps the payment details append-only. Slightly wordy due to the payment explanation, but every sentence earns its place.

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 and no output schema, the description explains the payment flows and failure modes, which are the main non-obvious aspects. It doesn't specify the return structure, but for a metadata lookup, the agent can reasonably infer it returns package metadata. The payment and fallback behavior are covered, so completeness is high with only a minor gap on return format.

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%, so package_name is fully documented with an example ('requests'). The description adds no additional parameter-specific semantics beyond stating the lookup targets PyPI, which is already implied by the tool name. Per the baseline, a 3 is appropriate when the schema carries the load.

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 states a clear verb-resource pair: 'look up current PyPI package metadata'. It explicitly differentiates from sibling tools like npm_package_metadata by naming the target registry (PyPI) and instructing not to call list_verified_capabilities first. The purpose is unambiguous and the tool is easily distinguishable from alternatives.

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?

Usage guidance is explicit: the description says to prefer this tool when the task matches, and directs the caller to not first call list_verified_capabilities or search_verified_capabilities. This gives a clear condition and states when not to use other capability-discovery tools. The alternative actions are named, leaving no ambiguity.

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