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

Annotations already cover safety (readOnly, idempotent, non-destructive) and open-world access, so the description's job is added context — and it delivers: parser-backed static import analysis, ImportError fallback handling, SHA-256 evidence, explicitly bounded module-layout output, and a stated UNKNOWN policy for ambiguous cases. What is missing is failure behaviour, cost/latency, and what happens at the target/consumer caps, so it stops short of a 5.

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?

Two sentences, front-loaded with the core comparison, with no filler or marketing language. It is dense to the point of being clause-stacked, but each clause carries distinct information.

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 four required nested objects, no output schema, and zero schema descriptions, the definition is behaviourally rich but structurally thin — it does not explain what the JSON response contains or how targets affect the report. An agent could form the right call conceptually but would be guessing at field formats and limits.

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%, and nested objects are used, so the description must carry the full explanatory load. It conceptually maps the release, source, and consumers inputs, but says nothing about sourceRoot, artifactKind wheel-vs-sdist behaviour, the string-or-object shape of targets, or the 40-char commit and 32/8 item limits — targets in particular is never explained, only implied by "module-layout results".

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?

"Compares one exact PyPI artifact with a full-commit public GitHub Python source tree and named public consumer files" states a specific verb and three specific resources, and the second clause enumerates what is reported. It never names a sibling, so an agent must infer the boundary with pypi_wheel_evidence and network_set_evidence, which keeps it below a 5.

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?

There is no when-to-use or when-not-to-use statement, and no routing to pypi_wheel_evidence or network_set_evidence despite an obvious overlap in PyPI/artifact evidence. The only contextual hints are baked-in constraints ("one exact" artifact, "full-commit" ref), which describe input shape rather than tool selection.

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