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BradMorphsters

tuskledger-mcp

get_recurring_subscriptions

List detected recurring subscriptions from your financial data, showing merchant, billing cadence, last amount, next expected date, and confidence.

Instructions

List detected recurring subscriptions: Netflix, Spotify, gym, etc. Returns merchant, cadence (monthly/annual/etc.), last amount, next expected date, and confidence. The user often asks 'what subscriptions do I have' — this answers it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Registration of the 'get_recurring_subscriptions' tool in the TOOLS list with its name, description, and input schema (no inputs).
    Tool(
        name="get_recurring_subscriptions",
        description=(
            "List detected recurring subscriptions: Netflix, Spotify, gym, "
            "etc. Returns merchant, cadence (monthly/annual/etc.), last "
            "amount, next expected date, and confidence. The user often "
            "asks 'what subscriptions do I have' — this answers it."
        ),
        inputSchema={"type": "object", "properties": {}, "additionalProperties": False},
    ),
  • The dispatch handler that calls client.recurring_subscriptions() when the tool name matches.
    if name == "get_recurring_subscriptions":
        return client.recurring_subscriptions()
  • The recurring_subscriptions() method on TuskLedgerClient that sends a GET request to '/api/analytics/recurring'.
    def recurring_subscriptions(self) -> Any:
        return self._request("GET", "/api/analytics/recurring")
Behavior3/5

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 but does not explicitly state that it is read-only or disclose any potential side effects. The name and context strongly imply safety, but the description lacks explicit disclosure.

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 two sentences, front-loaded with the main action, and every sentence adds value. No redundant information.

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?

Given no output schema and zero parameters, the description adequately covers the tool's functionality by specifying return fields. However, it could offer more detail on detection confidence or limitations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the baseline is 4. The description adds value by listing the output fields, which helps the agent understand what data to expect, compensating for the lack of input parameters.

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 it lists detected recurring subscriptions, provides concrete examples (Netflix, Spotify), and explicitly names the returned fields (merchant, cadence, etc.), making it distinct from siblings like get_upcoming_bills.

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?

The description includes a direct cue for common user queries ('what subscriptions do I have') and clearly indicates when to use the tool. However, it does not explicitly state when not to use or mention 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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