Map CVE/vulnerability to internal ICT providers and systems. Auto-creates findings for critical matches. DORA Art. 10.
| Name | Required | Description | Default |
|---|---|---|---|
| cve_id | No | CVE identifier | |
| vendor | No | Vendor/software name to check | |
| entity_id | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses a key side effect (auto-creating findings for critical matches) and references DORA Art. 10, but does not explain what happens to non-critical matches, whether existing findings are modified, or any permission/reversibility aspects. It provides some behavioral context but lacks depth.
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 extremely concise, with three short sentences: purpose, side-effect, and regulatory context. It is front-loaded with the main purpose and contains no fluff. Every sentence earns its place.
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 3 parameters, no output schema, and no annotations. The description is too brief to cover important contextual aspects: it does not explain the meaning of DORA Art. 10 in this context, what 'critical matches' means, what the output format is, whether the operation is reversible, or how entity_id relates to the mapping. Given the side effects, this is a significant gap.
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 67% (cve_id and vendor have descriptions, entity_id does not). The tool description adds no parameter meaning beyond the schema; it does not clarify what entity_id represents or how the three parameters interact. The schema descriptions themselves are minimal, so the agent gets little help in using parameters correctly.
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 tool's function with a specific verb ('Map') and resource ('CVE/vulnerability to internal ICT providers and systems'), and adds a distinct side-effect ('Auto-creates findings for critical matches'). It differentiates from sibling tools by focusing on CVE-to-asset mapping with automatic finding creation, which is unique among the listed siblings.
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 description implies usage when one needs to map CVEs to internal providers/systems, especially for DORA Art. 10 compliance, but does not explicitly state when to use this tool over alternatives or provide exclusions. No sibling tools are mentioned, so guidance is only implied.
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.
Several tools overlap in purpose, particularly contract analysis (check_contract, contract_analyze, llm_clause_check) which could confuse agents. Assessment-related tools (readiness_check, assess_all, article_status) also have partially overlapping functionality. However, most tools have distinct resources and actions with detailed descriptions.
Tool names are consistently snake_case and mostly follow a verb_noun pattern (e.g., create_entity, generate_report, register_provider). Minor deviations like contract_analyze and llm_clause_check invert the verb-noun order, but the overall pattern is predictable.
50 tools is a very large surface for a single server, exceeding the threshold for 'too many' tools. While the DORA domain is broad, this breadth makes it challenging for agents to navigate and select the right tool efficiently.
The tool set covers the full DORA compliance lifecycle: entity onboarding, contract analysis, provider management, assessments, evidence, reporting, and incident workflows. Simulation and cross-regulation tools add depth. Minor missing CRUD operations (e.g., update/delete entity) but agents can work around.