Look up known vulnerabilities for a package via the free OSV.dev API, optionally filtered to a specific version. Read-only; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Package name | |
| version | No | Optional package version to filter to | |
| ecosystem | Yes | Package ecosystem (e.g. npm, PyPI, Go) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full burden. It explicitly discloses read-only operation and that the API is free (price 0.0), which are key safety and cost traits. It does not detail response format or rate limits, but the essential behavioral aspects are covered.
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?
The description is two short sentences, front-loaded with the main purpose and free of unnecessary words. It earns its place by covering purpose, filtering behavior, and safety/cost in a compact form.
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 lookup tool with no output schema or annotations, the description adequately covers the purpose, data source, optional filtering, and read-only/free nature. Minor gaps remain regarding output structure and error behavior, but the tool is simple enough that this is sufficient.
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?
The schema already provides 100% coverage with clear descriptions for all three parameters. The description's mention of 'optionally filtered to a specific version' adds no new information beyond the schema's parameter description, so the baseline of 3 is appropriate.
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 clearly states the specific action ('Look up known vulnerabilities for a package') and the resource (via OSV.dev API), with an optional version filter. This distinguishes it from sibling CVE tools like cve_lookup_get_cve or cve_lookup_search_cve by focusing on package-level advisory lookup.
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 provides clear context: free, read-only, and optional version filtering, which implies appropriate use cases. However, it does not explicitly mention alternatives or exclusions, such as when to use cve_lookup_search_cve instead, so it misses the explicit when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly distinguished by domain prefixes (e.g., bid_watch, grant_watch) and specific action verbs. However, the high number of similarly structured watch tools could still cause confusion, though descriptions clarify exact purposes.
Every tool follows a consistent `domain_subdomain_action` pattern with underscores, e.g., `agent_audit_query`, `bid_watch_search`. Even long names like `commerce_catalog_agent_readiness_score` adhere to this structure.
With 147 tools, the server is far too broad, covering weather, carbon estimates, domain intel, and more—well beyond its stated 'Japan public-data ledgers' scope. This sheer volume overwhelms agents and dilutes focus.
The server offers many read-only tools for Japanese public data (bids, grants, licenses, etc.), but lacks create/update/delete operations for those domains. Additionally, numerous unrelated tools (e.g., carbon estimates, weather) feel tacked on, leaving gaps in core coverage.