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FLOCORE Governed MCP

Request governance onboarding

flocore_onboard_request

Request onboarding to FLOCORE governance for your world-affecting actions (human-gated approval, Ed25519 signed receipts, EU AI Act Article 12 audit evidence). Public: no token needed. This registers a request for HUMAN review and issues NO token; you get a request id and are contacted once approved.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orgNooptional: the organisation the agent acts for
agentYesyour agent name or identifier
referred_byNooptional: the governed agent or partner that sent you here (so credit flows to whoever brought you)
intended_useNooptional: what world-affecting actions you want governed
owner_contactYesan email or handle we can reach to confirm onboarding

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / referred_by
      Added value: +{
      +  "description": "optional: the governed agent or partner that sent you here (so credit flows to whoever brought you)",
      +  "type": "string"
      +}
  2. Added

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations, it discloses the key behaviors: the call registers a request for human review, deliberately issues NO token, returns only a request id, and results in later contact after approval. This is essential non-obvious behavior an agent needs to set expectations.

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 dense, front-loaded sentences cover purpose, access requirement, behavioral outcome, and follow-up. Every clause earns its place with no filler or repetition.

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

Completeness5/5

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

For a request-submission tool with no output schema, the description explains what response to expect (request id and later contact) and what not to expect (no token). Combined with the fully documented schema, an agent has enough to invoke it correctly.

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?

Input schema has 100% description coverage and all five parameters are described, so the baseline applies. The tool description does not add parameter-level meaning beyond the schema, though it reinforces the idea that the requester will be contacted after approval.

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?

States a specific verb+resource ('Request onboarding to FLOCORE governance') and clarifies scope ('world-affecting actions'). Distinguishes itself from sibling tools by emphasizing it is the onboarding request path and issues no token, which differentiates it from ticket creation or governance queries.

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?

Clear context is given: use it for governance onboarding of world-affecting actions, it is public and needs no token, and it is for human-gated review rather than immediate token issuance. It does not explicitly name alternative sibling tools or conditions when not to use it, so a small gap remains.

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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