Free-text CVE search with optional date range. Matches keyword against CVE description text in the NVD.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results to return (1-2000, default 20). | |
| keyword | Yes | Free-text search phrase. | |
| pub_end_date | No | Optional YYYY-MM-DD upper bound. | |
| pub_start_date | No | Optional YYYY-MM-DD lower bound. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only, idempotent, open-world behavior. The description adds useful context by specifying that matching occurs against CVE description text and that an optional date range is supported, but it does not disclose output format, pagination, or other runtime behavior.
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 short sentences with no filler. The primary action is front-loaded, and the matching semantics are stated directly. Every word contributes to understanding the tool.
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 lightweight read-only search tool with complete parameter schema and safety annotations, the description covers the core invocation semantics: what is searched, where, and with an optional date filter. It lacks explicit output structure details and alternative routing, but nothing required to call it correctly is missing.
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 coverage is 100%, so the baseline is 3. The description adds meaning beyond the schema by clarifying that the keyword is matched against CVE description text, which informs what search terms are appropriate. Date range is already visible in the schema, so only modest extra value is provided.
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?
Description states a specific verb ('search') and resource ('CVE') with precise scope: free-text matching against CVE description text in the NVD. This clearly distinguishes it from sibling tools like cve_lookup, cve_recent, and cve_search_by_vendor.
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 intended use is implied through 'Free-text CVE search' and 'Matches keyword against CVE description text,' but no explicit guidance is given about when to prefer this over cve_lookup, cve_search_by_vendor, or other alternatives. Usage context is clear, but exclusion/alternative guidance is absent.
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.
Many tools overlap heavily across domains: caselaw_search vs court_case_search vs court_opinion_search, caselaw_citation_lookup vs court_citation_resolver, and a cluster of company due-diligence tools (company_trust_check, counterparty_risk_score, entity_dossier, issuer_diligence_dossier, kyb_aml_evidence_case_file) that all screen a company for sanctions/risk/standing. With 290 tools, an agent will frequently face multiple equally plausible choices for the same user intent.
The vast majority of tools follow a clean domain-prefix + snake_case pattern (census_, eia_, fmcsa_, npi_, cfpb_, etc.), but there are notable exceptions: entity_resolve and resolve_entity are reversed duplicates, reg_search (Federal Register) sits next to reg_cfr_search (CFR) with confusingly similar names, and carrier_monitor_recheck deviates from the carrier_vetting_* family.
290 tools is an extreme count under any rubric, far exceeding even the 50+ threshold for the lowest score. While the group-filtering mechanism and meta-tools like list_tool_groups and search_available_datasets mitigate the practical burden, the raw surface is still massively oversized for an agent to select from accurately and efficiently.
For a read-only data-aggregation server, coverage is remarkably comprehensive across 59 domains, and generic fallbacks like cdc_dataset_query, eia_series_lookup, fred_observations, and bls_series prevent most dead ends. Minor gaps exist (a single GitHub tool, demo-only property_lookup coverage, no write/update operations anywhere), but the stated data-access purpose is well served.