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

Annotations already declare read-only, idempotent, non-destructive behavior, so the bar is lower, yet the description still adds substantive behavior: an edit-distance threshold scaled to name length, a >=3-character matching cutoff, and a curated-list limitation warning that a clean result does not prove safety. It also discloses a negative scope (does not verify existence), which is exactly the kind of boundary an agent needs.

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 earning its place: the first is the call trigger, the second the mechanism, the third the caveat plus the hand-off to supply_chain_check. Front-loaded with the action, no filler.

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 two-parameter, read-only lookup with no output schema, the description supplies everything an agent needs: when to call, how the check works, its precision limits, and where to go for the complementary existence check. Return-value semantics are implied ('a clean result does not prove a package is safe').

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% for both parameters, so the baseline is 3; the description earns a step above by naming the concrete ecosystems ('npm or PyPI') and framing the package parameter as the name to be fuzzy-matched in that ecosystem, which reinforces the pairing between the two required params.

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?

States a specific verb and resource (checks whether a package name is a near-miss of a well-known package, i.e. typosquatting) and scopes it to npm or PyPI. It also explicitly demarcates itself from the sibling supply_chain_check, so an agent can route without opening either 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?

Gives an explicit trigger ('Call before installing a package whose name you typed or recalled'), a when-not edge case (names of 3 characters or fewer are not fuzzy-matched), and names the alternative tool for the adjacent question (existence) via supply_chain_check. Nothing 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.