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vuln_exploitability_forecast

Read-onlyIdempotent

As a CTO, assess the exploitability risk of CVEs using EPSS scores and cloud asset exposure data. Input a CVE ID (e.g., CVE-2021-44228) to receive exploitability likelihood, affected cloud services, and threat intelligence context. Returns structured risk metrics for prioritization. Sources: CVE NVD, OpenCVE, GitHub Advisories. Pass async:true to avoid timeout.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
cveIdYes
cloudProviderNo
includeDetailsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cveIdYes
statusYes
sourcesYes
warningsYes
epssScoreNo
lastUpdatedNo
cloudExposureNo
epssPercentileNo

TDQS

A3.8/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds valuable context by naming data sources (CVE NVD, OpenCVE, GitHub Advisories) and disclosing potential timeout behavior with an async option. This goes beyond the annotations to inform the agent about response latency and external dependencies.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences long, each serving a purpose: stating the core function, specifying input/output, and providing sources and async guidance. It is front-loaded with the main action and contains no redundant or filler wording.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With annotations and an output schema present, the description covers the core use case and adds source/async context. However, it omits explanations for cloudProvider and includeDetails, and lacks guidance on choosing this tool over related vulnerability tools, making it adequate but not fully complete for a 4-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 25% (only async has a description). The description explains the core cveId parameter with an example and mentions async to avoid timeouts, but it does not explain cloudProvider or includeDetails, leaving half of the parameters unspecified. This only partially compensates for the low schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb ('assess') with a specific resource ('exploitability risk of CVEs') and distinguishes itself by mentioning EPSS scores and cloud asset exposure data. It also identifies the input (CVE ID) and output (exploitability likelihood, affected cloud services, threat intelligence context), making the tool's purpose unmistakable and distinct from generic CVE lookup tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies a use case for CTOs prioritizing vulnerabilities but does not explicitly state when to use this tool versus siblings like cve_security_lookup or vuln_patch_priority_engine. It includes an operational hint about passing async:true to avoid timeout, but offers no exclusions or alternative tool references.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

C2.4/5.0
Disambiguation1/5

Over 50 tools share the identical template 'Gapup agent-payable C-suite expertise' with similar French descriptions and reference cases, making their boundaries indistinguishable. Clusters like competitor_intel, competitive_deep_dive, competitor_moves, competitor_profiles, competitor_pricing_radar, competitor_pricing_scrape, and competitor_recommendations heavily overlap in purpose.

Naming Consistency1/5

Names are chaotic: mix of French and English, snake_case and camelCase, verb_noun, noun, and adjective forms with no uniform pattern. Examples like 'bp_narratif', 'content_enrichment', 'ai_governance_full_report_async', and 'job_result' show no coherent naming convention.

Tool Count1/5

271 tools is far beyond any reasonable MCP server scope, creating an overwhelming selection burden for agents. This count vastly exceeds the 25+ threshold for 'too many' and makes navigation impractical.

Completeness2/5

While the server covers many business domains, it lacks lifecycle operations (e.g., no update/delete tools for the deliverables it generates) and the input specifications are vague ('documented case fields' without documentation), creating functional dead ends. The sheer breadth does not compensate for these gaps.