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secondlife.it: lavoro, luoghi e soldi per ripartire

Ordina un servizio per l'utente

create_order

Orders a paid report. With an API key that has credit, it is paid at once and generated; otherwise it returns a checkout_url to hand to the human (Stripe), who pays and receives the report by email. Input depends on the product: verifica/bozza need ref (incentive id) and input (business profile + project); piano needs input (questionnaire answers); luogo needs ref (place id); kit needs input.cv, input.role and input.jobs (remote-job ids).

Input Schema

NameRequiredDescriptionDefault
refNoId della scheda (bando o comune) quando serve
emailYesEmail dell'utente che riceverà il report
inputNoDati per il report (profilo, progetto, risposte, CV)
productYesProdotto

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Goes well beyond the readOnlyHint=false/openWorldHint=false annotations: it discloses that the order is charged and generated immediately when credit exists, that otherwise a Stripe checkout_url must be handed to a human, and that the report is delivered by email. That is exactly the payment/auth/delivery context an agent needs before calling a non-idempotent purchase tool.

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-loads the core behavior and billing outcome in the first two sentences, with the per-product input rules last. The final sentence is a dense run-on packing five product variants, but every clause carries actionable information.

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?

No output schema exists, yet the description covers return outcomes (report generated immediately vs. checkout_url for human payment, email delivery) and resolves the ambiguous nested `input` object per product. Combined with the annotations, an agent has enough to invoke this correctly.

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

Parameters5/5

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

Schema coverage is 100% (baseline 3), but the description adds materially more: it specifies conditional requirements per product (verifica/bozza need ref + input; piano needs input; luogo needs ref; kit needs input.cv, input.role, input.jobs) that the schema's flat required list does not express. This prevents invalid calls the schema alone would allow.

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 ("Orders a paid report") and immediately clarifies the scope/billing model, which distinguishes it from read-side siblings like get_order and list_products. An agent knows this is the purchase/creation entry point, not a lookup.

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?

Explains the two execution paths (API key with credit vs. no credit returning a checkout_url) and which inputs each product requires, which is strong contextual guidance. It stops short of naming alternatives (e.g., use plan_preview first, or list_products to discover the product enum), so no explicit when-not routing.

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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