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

The description discloses rate limits (25 calls/day/IP), reset time (00:00 UTC), and the paid alternative route, adding behavioral context beyond the annotations (read-only, idempotent). It also mentions 'closest-match suggestions on misses,' which clarifies return behavior. Annotations already cover safety, so the description enriches without contradicting.

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 two concise sentences. The first sentence states the primary purpose and behavior, and the second provides rate-limit and pricing alternatives. There is no wordiness or redundancy—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?

Given the tool's simplicity, an output schema exists, and annotations are present, the description covers the core purpose, behavior on misses, and usage limits. It does not explain the output schema or error cases, but those are covered by structured data. Missing version semantics is a minor gap, but overall the description is contextually sufficient.

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 0%, so the description must compensate. It explains that ecosystem is PyPI or npm, and symbol refers to a function, class, or constant, covering two key parameters. However, it omits the optional 'version' parameter entirely, leaving its meaning and default to the schema. Partial compensation is provided, but not complete.

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 function: checking whether a function, class, or constant exists in a PyPI or npm package. It uses specific verbs ('exist') and resources ('symbol', 'package'), and distinguishes itself from siblings like package_exists or symbol_signature by focusing on existence with closest-match suggestions.

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 is implied: you would use this tool when you need to check symbol existence before using it. The description does not explicitly name alternative tools or conditions for when not to use it, but it does provide guidance on free vs. paid routes for high-volume usage, which is a form of usage context.

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