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xSpend — Spend Taxonomy Auto-Classifier

xspend-taxonomy
DestructiveIdempotent

Classify your GL or AP export into a four-level spend taxonomy with uncertain entries flagged.

Input Schema

NameRequiredDescriptionDefault
inputsYesOriginal buyer inputs. Service-specific CSV/date/rubric validation and a combined 75,000-character limit also apply.
sourceFieldsNo
sourceRunIdsNo
idempotencyKeyYesStable caller key for exactly one logical service request.
paymentInvoiceIdNoA separate confirmed service invoice when payment is required.
consentExternalProcessingYesExplicit authorization to send these sources and prior-agent context to the selected inference provider.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.8/5.0
Behavior2/5

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

Annotations already disclose destructiveHint=true, openWorldHint=true, and idempotentHint=true, but the description adds nothing about what is destroyed, external processing consent, required permissions, or rate limits. 'Uncertain entries flagged' is output behavior, not operational transparency, so the description does little beyond the safety profile already provided.

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?

The description is a single front-loaded sentence with no wasted words. It immediately states the action, input, output, and a notable output trait.

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?

This is a complex tool with a nested inputs object, required external-processing consent, destructive/open-world annotations, and no output schema. The one-sentence description does not explain consent requirements, data handling, what 'four-level taxonomy' entails, or what the response contains, leaving critical context missing.

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 moderate at 67%, with sourceFields and sourceRunIds lacking descriptions. The tool description provides no parameter-level meaning to compensate, so it adds nothing beyond what the schema already documents for the required 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?

The description states a specific verb (Classify) and resource (GL or AP export) and names the output (four-level spend taxonomy with uncertain entries flagged). It is clear enough to distinguish from most sibling tools, though it does not explicitly differentiate itself from related procurement workflow tools.

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?

The description implies usage by saying 'Classify your GL or AP export', but it gives no explicit when-to-use guidance, no prerequisites, no exclusions, and no alternatives among the many sibling procurement tools. It leaves selection entirely to inference.

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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