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list-transaction-cashcoding-recommendations

Read-only

List account recommendations for cashcoding a transaction. Use the numeric AcDocument ID from Websome/Roberto transaction.acDocument.id, then pass a returned accountId to apply-transaction-cashcoding-recommendation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topKNoNumber of account recommendations to return, 1 to 3, default 3
companyIdYesCompany ID
vendorNameNoOptional vendor name to improve recommendations
descriptionNoOptional transaction purpose/description to improve recommendations
transactionIdYesTransaction accounting document ID from Websome/Roberto transaction.acDocument.id
vendorContactIdNoOptional existing accounting contact ID for the vendor

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description adds real context beyond that: it discloses the tool's place in a two-step workflow and that it emits an accountId intended for the apply tool. It doesn't mention pagination, ranking behavior, or failure modes, but those are minor for a capped read operation.

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?

Two sentences, zero waste. The 'what it does' statement comes first and the input-source plus follow-up-tool routing comes second, so the most decision-relevant information is front-loaded.

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?

There is no output schema, so the description carries some return-value burden; it explains that results are account recommendations yielding an accountId for the apply tool, which is the essential contract. It omits the shape of the returned list (ranking, number returned relative to topK), a modest gap for a 6-parameter tool.

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 description coverage is 100%, so all six parameters are already documented, including topK, vendorName, and description. The description restates the transactionId source but adds nothing about parameters the schema doesn't already cover. Baseline 3 is correct when the schema does the heavy lifting.

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 ('List account recommendations for cashcoding a transaction') that distinguishes it from all siblings, and names the paired tool apply-transaction-cashcoding-recommendation. An agent can tell this is the lookup half of a two-step cashcoding flow without opening the schema.

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 clear when-to-use context: it identifies the exact input source (the numeric AcDocument ID from Websome/Roberto transaction.acDocument.id) and states what to do with the output (pass a returned accountId to apply-transaction-cashcoding-recommendation). It does not state when NOT to use it or how it differs from search-accounting-transactions, so it falls short of explicit exclusions.

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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