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Final POS – Custom POS Builder

Ask Finai

ask_finai
Destructive

Hand a task in words to Finai, Final's own AI agent, and get its finished answer. It runs as this connection's user on its company, within the allowed packs, and uses Final's tools itself (looking records up, creating products, building or deploying an app). Use it for multi-step merchant jobs you would rather describe than orchestrate; call tools directly when you need the raw data. Pass conversationId to continue an earlier thread.

Input Schema

NameRequiredDescriptionDefault
taskYesWhat to do or find out, in plain language, with every id or value Finai needs.
conversationIdNoA conversationId from an earlier ask_finai result, to continue that thread.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare destructive=true, openWorld=true, and non-idempotent, so the safety profile is covered. The description adds genuine delegation context beyond that: it runs as the connection's user, on its company, within allowed packs, and can perform writes (creating products, deploying apps). It stops short of spelling out failure modes or result formatting, so not a 5.

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?

Front-loads the core action, then scope, then the when-to-use/alternative split, then the continuation hint. Every sentence earns its place with no padding.

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 an agent-delegation tool with no output schema, the description covers purpose, scope, permissions context, usage routing, and continuation. It could say more about what a 'finished answer' looks like or how failures surface, but it is complete enough to invoke correctly.

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%, including the meaning of both task and conversationId, so the schema carries the parameter burden. The description's mention of passing conversationId to continue a thread merely restates the schema, adding no new syntax or constraints. Baseline 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 action ('hand a task in words to Finai... get its finished answer') with the concrete resource (Final's own AI agent). It explicitly contrasts itself with the sibling tool family by describing that it uses Final's tools internally, so an agent can tell it apart from call_tool or individual hub_* tools.

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

Usage Guidelines5/5

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

Gives explicit when-to-use ('multi-step merchant jobs you would rather describe than orchestrate') and names the alternative condition ('call tools directly when you need the raw data'). Also instructs on thread continuation via conversationId, leaving nothing to inference.

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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