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stables-money

Stables MCP Server

Official

submit_rfi_evidence

Submit answers and base64 documents for an RFI evidence requirement, moving it to compliance review and releasing held payment once approved.

Instructions

Submit the answers and documents an evidence requirement asks for, in one request, keyed as get_rfi_evidence_form lists them. Files are base64 data URLs ('data:application/pdf;base64,...'). The requirement moves to 'submitted' for Stables compliance to review; approving it releases the held payment once nothing else is outstanding. Confirm the content with a human before sending: it goes to compliance as the customer's answer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rfiIdYesThe RFI ID
answersYesAnswers keyed by the form's field keys and document wire_field names, e.g. { funds_origin, funds_origin_explanation, supporting_documents: ['data:application/pdf;base64,...'] }
customerIdYesThe customer ID
requirementIdYesThe requirement ID (type 'evidence')

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.4.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are present, so the description carries the burden and does well: it discloses the state transition to 'submitted', that compliance review follows, and that approval releases the held payment. It also specifies the file encoding format. It omits failure/validation behavior and required permissions.

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?

Three tight sentences, front-loaded with the action and format, followed by the downstream consequence and the safety caveat. No filler; every sentence earns its place.

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 mutation with nested objects, no annotations, and no output schema, the description covers the format, the workflow dependency, the post-submit state, and the payment-release consequence. It leaves out error handling and anything about the returned response, but nothing critical to correct invocation is missing.

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% and the schema already documents each parameter, including the answers object and its base64 example. The description adds only the pointer that keys must match get_rfi_evidence_form's listing, so the schema does the heavy lifting and baseline 3 applies.

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: submitting answers and documents for an `evidence` requirement in a single request. It differentiates from siblings by naming get_rfi_evidence_form as the source of the keying scheme, so an agent can distinguish it from the read-side RFI tools.

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?

Implies the correct workflow ('keyed as get_rfi_evidence_form lists them', 'in one request') and adds an explicit human-confirmation gate before sending. It does not spell out when NOT to use it (e.g. other requirement types), so it stops short of full guidance.

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