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OpenMonetis MCP

OpenMonetis MCP

by Welington98

Compromissos futuros

list_commitments
Read-onlyIdempotent

Projects contracted financial commitments between a start and end month, inclusive, covering installments, recurring charges, and invoices for up to 24 months.

Instructions

Projeta os compromissos financeiros entre dois meses (inclusive): parcelas, recorrências e faturas já contratadas. Limite de até 24 meses.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "startPeriod": "<startPeriod>",
      "endPeriod": "<endPeriod>"
    },
    "name": "list_commitments"
  }
}

Input Schema

NameRequiredDescriptionDefault
endPeriodYes
startPeriodYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.3

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare this read-only, idempotent, non-destructive and closed-world, so the safety profile needs no restating. The description does add one genuinely new behavioral constraint — the 24-month maximum span — but says nothing about what the projection returns, ordering, or how partial months are handled.

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 short sentences with no waste; the scope and inclusions come first and the 24-month limit closes it. Nothing is redundant or padded.

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?

With no output schema, the description carries the burden of saying what comes back, and it does identify the three commitment types it projects plus the range limit. A note on the expected response shape or behavior at the 24-month boundary would make it fully complete for a two-parameter read 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 0%, so the description must carry meaning, and it does explain that the two parameters are month boundaries and that the range is inclusive with a 24-month ceiling. It still does not state the expected YYYY-MM text format or what happens when the span exceeds the limit, leaving a gap the 0%-described schema cannot fill.

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?

States a specific verb ('Projeta') and resource ('compromissos financeiros') and enumerates what is included: parcelas, recorrências e faturas já contratadas. It is clear enough to distinguish from raw-entity siblings like list_installments or list_invoices, though it never names them explicitly.

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 forward-looking verb 'Projeta' implies this is the tool for a future multi-month projection rather than a raw listing, and the 24-month cap tells the agent a boundary exists. However, there is no explicit when-to-use/when-not guidance or named alternative (e.g. list_installments for a single entity type), so the routing must be inferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.