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klodr

mercury-invoicing-mcp

mercury_list_transactions

Need to audit deposit-account activity? List transactions from a Mercury deposit account with filters for date range, status, and search to reconcile statements or build ledger views.

Instructions

List transactions for a Mercury deposit account, with optional filters (date range, status, search).

USE WHEN: auditing deposit-account activity, reconciling a statement, or building a per-account ledger view. Filters server-side: status, start, end, search, limit, offset.

DO NOT USE: for IO Credit transactions (use mercury_list_credit_transactions, which targets the IO Credit account surface). For Treasury, use mercury_list_treasury_transactions.

RETURNS: { transactions: [{ id, amount, status, postedAt, counterpartyName, ... }] }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountIdYesThe Mercury account ID
limitNoMax results to return (1-500). Default: 500
offsetNoPagination offset
statusNoFilter by transaction status
startNoFilter posted on/after this date (YYYY-MM-DD)
endNoFilter posted on/before this date (YYYY-MM-DD)
searchNoSearch query (counterparty name, memo, etc.)
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses the return format with key fields and notes that filters are server-side. However, it does not mention rate limits or potential performance implications, leaving minor gaps.

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 brief, structured into clear sections (purpose, USE WHEN, DO NOT USE, RETURNS), and front-loaded with the main action. Every sentence adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only list tool with 7 parameters and no output schema, the description adequately covers purpose, usage guidelines, alternatives, and return format. It is complete enough for an AI agent to understand when and how to use it.

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%; all 7 parameters have descriptions in the schema. The description summarizes the filter parameters but adds little new semantic value beyond organizing them. Baseline 3 is appropriate.

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?

The description clearly states 'List transactions for a Mercury deposit account' with a specific verb and resource. It distinguishes from siblings by explicitly naming mercury_list_credit_transactions and mercury_list_treasury_transactions for different account types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Includes both 'USE WHEN' (auditing, reconciling, building ledger) and 'DO NOT USE' sections, naming alternative tools (mercury_list_credit_transactions, mercury_list_treasury_transactions) and the contexts where they should be used instead.

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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