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Glama

Osv

by io.github.pipeworx-io

Query Package Vulns

query_package_vulns
Read-onlyIdempotent

Find all known vulnerabilities for an open-source package, optionally at a specific version, via the OSV.dev database. Omit version to get every vuln known for the package. Returns a compact summary array (id, summary, aliases, severity, references). Keyless.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesPackage name, e.g. "lodash", "django", "log4j-core", "serde".
versionNoOptional package version, e.g. "4.17.20". If given, only vulns affecting that version are returned; if omitted, all vulns for the package are returned.
ecosystemYesPackage ecosystem. Examples: "npm", "PyPI", "Go", "Maven", "crates.io", "RubyGems", "NuGet".

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "ecosystem": "npm",
+    "name": "lodash"
+  },
+  {
+    "ecosystem": "PyPI",
+    "name": "django",
+    "version": "3.2.0"
+  }
+]
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds output format details ('compact summary array') and notes it is keyless (no auth), going beyond the annotations.

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?

Two sentences front-load the core purpose and usage, with no wasted words. Every sentence earns its place.

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?

Given the tool's simplicity, annotations, and no output schema, the description covers the main aspects: purpose, filtering, and output shape. It could mention rate limits or pagination, but it's sufficient for a straightforward query tool.

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

Parameters4/5

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

Schema coverage is 100% with examples. The description adds value by noting that omitting version returns all vulnerabilities for the package and that the tool is 'Keyless', which provides additional context beyond the schema.

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 it finds vulnerabilities for an open-source package, with optional version filtering, via the OSV.dev database. It distinguishes from siblings like get_vulnerability (single vuln) and scan_dependency (project-level).

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?

The description explains when to omit the version parameter to get all vulnerabilities, providing clear usage context. It does not explicitly exclude alternatives, but the purpose is well-scoped.

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

All Osv toolsInspect
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TDQS

A4/5.0
Disambiguation3/5

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are very similar, as are the suite of polymarket_* tools. While descriptions help differentiate, an agent may struggle to choose the correct one without careful reading.

Naming Consistency3/5

All tool names use snake_case, but they mix verb-first patterns (ask_pipeworx, compare_entities, validate_claim) with noun-first patterns (bet_research, entity_profile, pipeworx_feedback). This inconsistency makes it harder to guess tool names by convention.

Tool Count3/5

35 tools is on the high side but not unreasonable for a platform covering vulnerability queries, data retrieval, prediction markets, and utilities. However, the server name 'Osv' suggests a narrow focus, making the large count feel bloated.

Completeness4/5

The tool set covers a wide range of operations: querying data, comparing entities, managing user data, monitoring subscriptions, and even onboarding. Minor gaps exist (e.g., no direct API for updating user profiles), but overall it is well-rounded for its domain.

Resources