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Fidensa MCP Server

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Check Fidensa Certification

check_certification
Read-only

Verify an AI capability's trust level before use. Returns certification status, trust score, grade, tier, and supply chain status with no API key required.

Instructions

Quick trust check for an AI capability (MCP server, skill, plugin, or workflow). Returns certification status, trust score, grade, tier, and supply chain status. No API key required. Use this before invoking any capability to verify it has been independently certified by Fidensa.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
capability_idYesCapability identifier (e.g. "mcp-server-filesystem")
versionNoSpecific version to check (e.g. "1.0.0"). Omit for latest.
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, indicating safe read operation. The description adds that 'No API key required' and lists the return fields, providing useful behavioral context beyond annotations.

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?

Two sentences, no unnecessary words. The first sentence defines the tool, the second provides usage guidance. Highly efficient.

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

Completeness4/5

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

For a simple trust-check tool with well-defined parameters and no output schema, the description adequately covers the return fields. Could mention edge cases (e.g., what happens if capability_id is invalid), but overall sufficient given the tool's simplicity.

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

Parameters3/5

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

Schema coverage is 100% with good parameter descriptions. The description repeats the examples from the schema (e.g., version: 'Omit for latest') but does not add new semantics beyond what the schema already provides. Baseline 3 is appropriate.

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?

Clearly states it performs a 'trust check' for an AI capability, returns multiple specific fields (certification status, trust score, grade, tier, supply chain status). The title and description consistently use 'Check Fidensa Certification', differentiating it from sibling tools like verify_artifact or compare_capabilities.

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

Usage Guidelines4/5

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

Explicitly advises 'Use this before invoking any capability to verify it has been independently certified by Fidensa.' This tells the agent when to use the tool, though it does not explicitly mention alternatives or when not to use it.

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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