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

Substantially exceeds the annotations (readOnly/idempotent/openWorld/non-destructive). It discloses what is flagged (unseen human publisher after 180+ days inactivity in last 365 days), what is reported but explicitly not flagged (trusted OIDC publishing, pre-release, established handover), and a known blind spot (hijacked existing accounts). This is unusually rich behavioral disclosure.

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?

Dense but mostly earned: every clause informs detection scope or output meaning, which matters with no output schema. One minor inefficiency is leading with the ecosystem caveat before stating the core purpose, but overall it is tight for the amount of behavior conveyed.

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?

With no output schema, the description carries return-value explanation (found, first_published, package_age_days, new_package threshold) and detection caveats thoroughly. An agent has enough to call it correctly and interpret results for either ecosystem.

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 coverage is 100% and both parameters are described there, including the npm-vs-pypi split. The description largely restates the ecosystem semantics (npm full analysis, PyPI existence and age only) rather than adding syntax or format details beyond the schema, so the baseline 3 applies.

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 names a specific analysis (publisher-change detection) and states precisely what is reported (found, first_published, package_age_days, new_package), plus the ecosystem scope. It is clearly distinguishable from siblings like typosquat_check or vulnerability_check by focusing on maintainer handover patterns.

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 clear context: npm-only for publisher analysis, PyPI limited to existence/age, and explicitly frames output as 'a heuristic for review, not proof.' It does not say which sibling to call instead when you need vulnerability or reputation data, so it stops short of full when-not guidance.

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