Fetch multiple CVEs (from NVD) and aggregate a severity distribution and worst-case summary for the set. Read-only; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| cveIds | Yes | CVE identifiers to summarize |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions 'Read-only' and 'price 0.0 (free)', which addresses side-effect concerns. However, it does not disclose other behavioral aspects like rate limits, handling of invalid CVE IDs, or that it makes external network calls to NVD, leaving room for more transparency.
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 one concise sentence stating the core function, followed by a short note on read-only and cost. Every part earns its place with no redundancy, making it efficiently front-loaded.
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?
The tool has no output schema, so the description should ideally explain the return structure. It mentions 'severity distribution and worst-case summary' but does not detail components (e.g., counts per severity level, which CVE is worst). This is a moderate gap, but the tool is simple, so a 3 is appropriate.
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% for the single parameter 'cveIds' ('CVE identifiers to summarize'). The description does not add extra meaning beyond the schema, such as format examples or constraints, 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 action: 'Fetch multiple CVEs (from NVD) and aggregate a severity distribution and worst-case summary for the set.' This specifies the verb (fetch and aggregate), resource (CVEs), and outcome (severity summary), distinguishing it from sibling tools like cve_lookup_get_cve which handles single CVEs.
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?
The context is clear: this tool is for summarizing severity across multiple CVEs, which implies when to use it over single-CVE lookup tools. However, it does not explicitly name alternative tools or state when not to use it, so it falls short of a 5.
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.