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Read completed queue result once

get_job_result
Read-onlyIdempotent

Retrieve one fal.ai job result by model ID and request ID; no waiting, media download, resubmission, or auto-upload.

Instructions

One result read using the receipt/model root. No wait loop, media download, re-submission or auto-upload. Signed credential URLs are redacted; ordinary output media URLs remain account data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNoExact configured isolated API-key profile label.
model_idYesExact current catalog endpoint ID. Never guess model names or parameter mappings.
request_idYesExact queue receipt ID; status/result/cancel use its owner/app root, without inference subpaths.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, open-world, so the safety profile is covered. The description adds real value beyond that: no polling/wait loop, no media download, no re-submission, and the fact that signed credential URLs are redacted while ordinary media URLs remain account data. This is meaningful behavioral context the annotations do not supply.

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?

Two tight sentences with the core action front-loaded and the exclusion list packed efficiently. Dense but no wasted filler, though the telegraphic phrasing borders on cryptic.

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 read-only result fetch with annotations covering the safety profile and no output schema to document, the description covers what it does, what it deliberately does not do, and how URLs are handled. Sufficient for correct invocation.

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 three parameters (account, model_id, request_id) are already well documented in the schema. The description only alludes to the 'receipt/model root' pairing without adding syntax or format detail, so baseline 3 is appropriate.

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+resource ('One result read') and names the identifier basis ('receipt/model root'), so an agent knows this retrieves a finished job's output. It does not explicitly contrast with the sibling get_job_status, leaving the boundary partly to inference.

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 negatives ('No wait loop, media download, re-submission or auto-upload') implicitly tell the agent this is a one-shot read rather than a poll or resubmit, which narrows usage. However, it never names get_job_status or states the condition under which this tool is preferred, so guidance remains implied.

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