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Boundra — Payment Approval Gateway for AI Agents

evaluate_payment

Evaluate a payment intent. MUST be called before executing any payment. ALLOW = you may pay; DENY = you must abandon; ASK = a challenge is returned — relay the reason to the user, then retry with approval_token once the user signs. An optional mandate parameter carries a user-issued single-task authorization.

Input Schema

NameRequiredDescriptionDefault
ownerNo
amountYes
mandateNo
purposeYes
agent_idNo
recipientYes
approval_tokenNo
source_contentNo
expected_amountNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does disclose the decision protocol, the challenge/retry flow, and the mandate's authorization semantics. It omits other behavioral traits such as side effects, idempotency, and whether evaluation itself is read-only, which is a real gap for a no-annotation tool.

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?

Front-loads the mandatory call ordering, then maps each outcome to an action in compact clauses. Every sentence carries operational meaning with no filler.

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?

The decision and retry protocol is complete, and the output schema relieves the description of explaining return values. However, for a 9-parameter tool with no annotations and 0% schema coverage, the near-total absence of parameter guidance leaves the agent under-informed on inputs.

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% across 9 parameters, so the description must compensate and largely does not: it explains only mandate ('user-issued single-task authorization') and implies approval_token. It never distinguishes amount from expected_amount, nor clarifies owner, agent_id, source_content, or purpose.

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 and resource ('Evaluate a payment intent') and then defines the tool's decision vocabulary (ALLOW/DENY/ASK). No sibling in the list performs payment evaluation, so the agent can immediately place this tool relative to the policy/audit siblings.

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?

Gives a hard precondition ('MUST be called before executing any payment') and branch-specific next actions for each decision outcome, including the approval_token retry path. It does not name a when-not case or an alternative tool, but no sibling overlaps functionally.

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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