dependency_auditor__audit_pip

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

With no annotations, the description carries the full burden. It usefully discloses the version-resolution strategy (exact versions from lock files, falling back to requirements.txt/pyproject.toml) and the OSV data source, but says nothing about network/auth requirements, rate limits, or result format.

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 tight sentences with the core purpose front-loaded and the resolution fallback trailing as supporting detail. No filler, though the manifest list slightly blurs into schema territory.

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 3-parameter tool with no annotations and no output schema, the description covers what it does and how it resolves versions but omits any sense of the return shape or the read-only nature of the operation. Adequate for selection, incomplete for invocation expectations.

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%, so the baseline is 3. The description adds no parameter-level detail: it never mentions exploitData (CISA KEV/EPSS enrichment) or includeDevDeps, leaving the schema to carry all three parameters.

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 pairs a specific verb ('Audit') with a specific resource ('Python dependencies') and states the threat model ('known CVEs using the OSV database'). The Python-specific lock-file list implicitly separates it from sibling audit_npm, though it never explicitly names a sibling.

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 only implied: an agent can infer this is for Python projects because the description enumerates the Python manifests it reads. It never says when to prefer this over audit_package, audit_directory, or slopsquat_scanner__scan_pip, and offers no exclusions or prerequisites.

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