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frothkoetter

data-marketplace-mcp-server

by frothkoetter

approve_access_request

Approve pending data access requests and trigger automated provisioning, enabling users to quickly gain authorized access to data products in the internal marketplace.

Instructions

Zugriffsanfrage genehmigen und automatisches Provisioning anstoßen.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commentNo
approverYes
request_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states that approving 'initiates automatic provisioning' which is useful, but doesn't disclose whether the action is reversible, whether the approver parameter must match a specific role or identity, whether comment is required, or what happens on failure. For a mutation action with zero annotation coverage, this is thin.

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

Conciseness4/5

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

A single concise sentence, front-loaded with the primary action. It is efficient and earns its place. However, given the completeness gaps, slightly more content would be warranted rather than maximum brevity.

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

Completeness2/5

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

Despite having an output schema, the tool is a mutation operation with no annotations and 0% parameter coverage. The description must do more to explain workflow context, approval semantics, and parameter formats. With 16 sibling tools in an approval workflow, the description leaves the agent without clarity on how this fits into request/data-governance flows.

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 0%, and the description adds no parameter-level detail beyond 'genehmigen'. It doesn't clarify what request_id refers to (a request object ID), what format the approver should take (username, email), or what the comment field is for. With 3 parameters and 0% coverage, the description fails to compensate, leaving parameter semantics to the agent to infer from names alone.

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

Purpose4/5

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

The description clearly states the verb-action (approve an access request) and that it triggers automatic provisioning. It's written in German, which matches the tool's domain context. However, it doesn't explicitly distinguish from sibling reject_access_request in its description, though the verb differentiation is inherent.

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

Usage Guidelines2/5

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

No when-to-use or when-not-to-use guidance is provided. With sibling tool reject_access_request and list_access_requests available, the description gives no guidance on workflow sequencing (e.g., should you list requests first, what state the request must be in, whether rejection is the alternative). No exclusions or alternatives are mentioned.

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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