Builds a normalized security-intelligence record from a CVE ID for downstream RAG or LLM reasoning, enabling consistent vulnerability context enrichment.
Build a normalized security-intelligence record suitable for downstream RAG or LLM reasoning.
| Name | Required | Description | Default |
|---|---|---|---|
| cve_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing: it does not say which sources are aggregated, whether external network calls or rate limits apply, what authentication is needed, or whether the output is cached or expensive to produce. For an aggregation-style tool that likely fans out to multiple intelligence sources, this is a substantial gap.
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 short, front-loaded, and contains no filler, which is structurally sound. However, brevity here reflects under-specification rather than efficiency: the single sentence is too thin to carry the tool's responsibilities.
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?
An output schema exists, so return values need not be explained, which helps. But with no annotations, no parameter documentation, no provenance of aggregated sources, and no routing guidance against many overlapping siblings, the definition is not complete enough for an agent to invoke this confidently.
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 0% and the description says nothing about the single parameter, so it does not compensate for the coverage gap as the rules require. The name 'cve_id' is largely self-explanatory, which keeps this from being a 1, but format expectations (e.g., CVE-YYYY-NNNN) and validation behavior are left entirely to inference.
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 gives a verb ('Build') and a resource ('normalized security-intelligence record'), which is more than a tautology. However, it does not distinguish this from close siblings like get_cve_intelligence and get_complete_cve_intelligence, which presumably also aggregate CVE intelligence, so an agent cannot reliably tell which one to pick. The stated purpose is also abstract ('suitable for downstream RAG or LLM reasoning') rather than naming what the record actually contains.
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?
There is no explicit when-to-use guidance and no naming of alternatives, despite a large sibling set containing several near-overlapping intelligence tools. The phrase 'suitable for downstream RAG or LLM reasoning' hints at a use case but stops short of telling the agent when this should be preferred over get_cve_intelligence or get_complete_cve_intelligence.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.