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Batch vulnerability scan (lockfile)

scan_vulnerabilities_batch
Read-onlyIdempotent

Scan many packages in one call — ideal for a whole lockfile. Pass a queries[] array (max 100) of { ecosystem, name, version? }; results are returned positionally aligned, one row per query, each with a count and a hydrated vulns[] array. Advisories are de-duplicated and hydrated across the batch. ecosystem is CASE-SENSITIVE (OSV spelling).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queriesYesUp to 100 { ecosystem, name, version? } queries, ideal for a whole lockfile.

TDQS

A4.4/5.0
Behavior5/5

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

While annotations already declare readOnly, idempotent, and non-destructive, the description adds critical behavioral details: positional alignment of results, de-duplication and hydration of advisories, and case-sensitive ecosystem values. These go beyond the annotations and are essential for correct invocation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, each delivering distinct value: purpose, input/output structure, and a key caveat. It is front-loaded with the primary use case and contains no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description must explain return values. It does outline positional rows with count and hydrated vulns[], and mentions de-dup, but leaves details like count semantics and exact vuln fields ambiguous. For a batch tool of moderate complexity, this is adequate but not exhaustive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description does not significantly add to parameter meaning; it repeats max 100 and case-sensitivity. It does describe the query object shape, but there is a slight ambiguity: it lists ecosystem without a question mark while the schema only requires name, which could confuse on requiredness.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Scan many packages in one call' with a specific verb and resource, and explicitly positions it as ideal for lockfiles. This distinguishes it from the sibling get_vulnerabilities tool, which handles single package scans.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides strong usage context ('ideal for a whole lockfile') and parameters (max 100 queries). It does not explicitly mention alternatives or when not to use it, but the lockfile focus makes the intended scenario clear.

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

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TDQS

A4.4/5.0
Disambiguation4/5

Most tools have clear, distinct purposes, but get_package and get_ecosystems_package both return package metadata and could be confused; search_ecosystems and search_packages also share a similar naming pattern though their behavior differs (exact cross-registry lookup vs fuzzy within a registry). Overall, descriptions help disambiguate.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern: get_ for fetching specific data, search_ for searching. No mixed conventions or vague verbs, making the API predictable.

Tool Count5/5

10 tools is well-scoped for a package/dependency intelligence server. Each tool covers a distinct aspect (metadata, versions, dependencies, downloads, vulnerabilities, insights, search) without feeling bloated or thin.

Completeness4/5

The tool surface covers core package lookups, version listing, dependency graphs, download stats, vulnerabilities (single and batch), and security insights. Minor gaps exist, such as no direct tool for comparing packages or listing maintainer info, but these are not essential for the stated purpose.