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sebbi.pro - the proof layer for AI

Ask before an agent pays

sebbi_spend_request

Call before every payment an AI agent makes. Returns a signed APPROVED or DENIED token checked against the agent's limits. Release the money only if it is APPROVED and spendable. sebbi.pro never holds or moves money.

Input Schema

NameRequiredDescriptionDefault
agentYes
payeeYes
amountYesAmount in pounds
reasonNo
api_keyYes
currencyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false, openWorldHint=true, and destructiveHint=false. The description adds real value beyond them: it returns a signed token checked against the agent's limits and explicitly states sebbi.pro never holds or moves money, clarifying that this is an authorization check, not a funds transfer.

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?

Four short sentences, front-loaded with the trigger condition and followed by the outcome and a scope disclaimer. Nearly every sentence earns its place, though the 'spendable' clause is slightly ambiguous.

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?

With no output schema, describing the returned token is helpful and the money-custody disclaimer closes an important behavioral gap. But for a tool with six inputs and 17% schema coverage, the absence of any parameter explanation or output field detail (token expiry, how to present it) leaves meaningful gaps.

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 only 17% (just 'amount' in pounds), and the description explains none of the six parameters despite the persistence of payee, agent, api_key, currency, and reason. With low coverage and no compensating narrative, the agent gets little semantic help on inputs.

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?

States a specific action and resource: an agent calling to get an APPROVED/DENIED spend token before a payment. An agent can understand the core purpose without opening the schema. However, it does not differentiate this from closely named siblings like sebbi_spend_policy or sebbi_spend_verify, so sibling confusion remains possible.

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?

'Call before every payment an AI agent makes' gives a clear triggering condition, and 'Release the money only if it is APPROVED and spendable' specifies the follow-up action. It stops short of naming when not to use it or routing to the sibling spend tools, so it is clear context without alternatives.

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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