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Fatture in Cloud: Record expense

fatture-in-cloud_record_expense

Fatture in Cloud: Record an expense with supplier, date and net and VAT amounts. Creates a received document and returns its ID and totals. It reaches nobody and can be deleted in Fatture in Cloud, so this call runs without asking first. Check list_expenses first to avoid a duplicate. Needs the user's Cotlet API key with access to this app.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesDocument date, ISO.
supplierYesSupplier name.
amount_netYesNet amount.
company_idNoCompany ID. Optional when your account has one company.
descriptionNoWhat was bought.
vat_percentYesVAT rate in percent.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations mark it as a non-read-only, non-destructive, open-world write, and the description adds real context beyond them: it discloses the return ("returns its ID and totals"), the reversibility ("can be deleted in Fatture in Cloud"), why no confirmation is needed, and the auth requirement (Cotlet API key with app access). This is exactly the extra behavioral context annotations can't carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, then behavior, then the sibling alternative, then auth. Sentences are tight and each earns its place, though the "Fatture in Cloud:" prefix slightly duplicates the title.

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?

For a 6-param mutation tool with no output schema, the description covers creation effect, return values, reversibility, auth, and dedup guidance, which is close to complete. It could say more about what happens to the created document downstream, keeping it just under a 5.

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 in the schema. The description names some of them (supplier, date, net and VAT) but adds no syntax, format, or constraint detail beyond what the schema provides, so the baseline of 3 applies.

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 ("Record an expense") plus the key fields it captures (supplier, date, net and VAT amounts), and separately clarifies it "Creates a received document." This lets an agent distinguish it from siblings like list_expenses or create_invoice without opening any 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?

Explicitly routes to a sibling: "Check list_expenses first to avoid a duplicate," which is a concrete when-to-use-this-vs-alternative instruction. It also clarifies it "runs without asking first," giving context on confirmation behavior, though it stops short of stating full 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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