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eliaskress

FlowCheck Financial API MCP Server

by eliaskress

Reconciliation Detail

flowcheck_get_reconciliation

Retrieve detailed reconciliation for a Stripe payout, showing confidence score breakdown and matched bank transaction data.

Instructions

Get detailed reconciliation for a specific payout. Shows confidence score breakdown (amount, date, description, bank ID) and the matched bank transaction.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
payout_idYesStripe payout ID

Implementation Reference

  • The handler for the 'flowcheck_get_reconciliation' tool is registered and implemented within the registerReconciliationTools function in src/tools/reconciliation.ts.
    server.registerTool(
      "flowcheck_get_reconciliation",
      {
        title: "Reconciliation Detail",
        description:
          "Get detailed reconciliation for a specific payout. " +
          "Shows confidence score breakdown (amount, date, description, bank ID) " +
          "and the matched bank transaction.",
        inputSchema: z.object({
          payout_id: z.string().describe("Stripe payout ID"),
        }),
      },
      async ({ payout_id }) => {
        const result = await client.request(
          "GET",
          `/reconcile/${payout_id}`,
        );
        return { content: [{ type: "text" as const, text: result }] };
      },
    );
Behavior2/5

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

No annotations are provided, so the description carries full burden. It describes what the tool returns (confidence score breakdown and matched bank transaction) but doesn't disclose behavioral traits like whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or data freshness. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.

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 efficiently structured in a single sentence that front-loads the core purpose ('Get detailed reconciliation for a specific payout') followed by specific output details. Every word earns its place with no redundancy or unnecessary elaboration, making it easy to scan and understand quickly.

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?

Given the tool has no annotations and no output schema, the description provides basic completeness by explaining what information is returned (confidence score breakdown and matched bank transaction). However, for a tool that presumably returns complex reconciliation data, it doesn't describe the structure of the confidence score breakdown, what 'matched bank transaction' entails, or potential error scenarios. This is adequate but has clear gaps in contextual detail.

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?

The input schema has 100% description coverage (payout_id is clearly documented as 'Stripe payout ID'), so the baseline is 3. The description doesn't add any parameter-specific information beyond what the schema provides—it mentions 'specific payout' but doesn't elaborate on parameter format, validation, or examples. This meets the minimum viable standard when schema coverage is complete.

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 clearly states the tool's purpose: 'Get detailed reconciliation for a specific payout' specifies the verb (get) and resource (reconciliation detail). It distinguishes from sibling tools like 'flowcheck_get_reconciliation_summary' by emphasizing 'detailed' breakdown, though it doesn't explicitly name the sibling for comparison.

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

Usage Guidelines3/5

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

The description implies usage context by specifying 'for a specific payout' and mentioning confidence score breakdown components, suggesting it's used when detailed reconciliation analysis is needed. However, it doesn't provide explicit guidance on when to choose this over alternatives like 'flowcheck_get_reconciliation_summary' or 'flowcheck_list_discrepancies', nor does it mention prerequisites or 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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