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

With no annotations, the description carries the full burden, and it does disclose meaningfully: what it blocks, that typosquat detection depends on supplying an expected name, that OSV advisories are consulted, and that it costs $0.01 USDC on Base. It remains silent on auth/permission needs, rate limits, and whether the call is strictly read-only.

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?

A single dense sentence with the core purpose front-loaded, followed by the cost. Zero 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?

No output schema and no annotations, so the description should say more about what a caller gets back (verdict shape, advisory details) and any prerequisites. It conveys the check's intent and cost but leaves result format and version handling unaddressed.

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 clarifies expectedName's role ('when an expected name is supplied') and the ecosystem values (npm or PyPI), but leaves 'version' entirely undocumented in both schema and description.

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+resource ('install preflight' for npm/PyPI) and enumerates the three things it does: block missing packages, detect typosquats, check OSV advisories. This clearly separates it from siblings like mcp_payment_preflight, whose domain is payments rather than package registries.

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?

The word 'preflight' and 'install' imply usage before installing a package, but there is no explicit when-to-use, no exclusions, and no comparison to alternatives. Usage is implied rather than stated.

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