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falai

Run model (subscribe)

falai_run_model
Destructive

Convenience 'subscribe': submit a request, poll its status until COMPLETED, then return the result. Consumes fal credits. If it does not complete within the wait budget, returns a { status, request_id, status_url, note } object (NOT an error) so you can keep polling with falai_get_request_status / falai_get_request_result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesThe model's input object — arbitrary params for that model, e.g. { "prompt": "a cat" }. Use falai_get_model_schema to learn the fields.
model_idYesThe fal.ai model id, used raw as a path segment, e.g. 'fal-ai/flux/schnell'.
max_wait_secondsNoMax seconds to wait for completion (default 60, capped at 300).
poll_interval_secondsNoSeconds between status polls (default 3, min 1).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With only destructiveHint=true provided, the description does real work: it discloses credit consumption, that the call blocks/polls, and that a timeout returns a { status, request_id, status_url, note } object rather than an error. It is consistent with (and explains the reason behind) the destructive hint. It does not state whether a submitted request continues/charges after the client abandons polling, which would be the remaining behavioral detail.

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 sentences, both dense: the first defines the flow and cost, the second defines the failure/continuation path. No filler and the core behavior is front-loaded.

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 blocking convenience wrapper with no output schema, the description covers cost, control flow, and the timeout return shape. The one gap is the shape/meaning of a successful result (model output payload) versus the partial object it does describe.

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 default/cap semantics for max_wait_seconds and poll_interval_seconds, so the baseline is 3. The description adds no parameter-level meaning beyond the schema, though it does implicitly frame why wait/interval exist.

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 chain (submit, poll, return) on a named resource, and the compression of that into a single 'subscribe' convenience call distinguishes it from the sibling falai_submit_request, which presumably only submits. An agent can tell what it gets without opening the 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 the agent to falai_get_request_status / falai_get_request_result when the wait budget is exhausted, which is clear contextual guidance. However, it never states when to prefer this tool over falai_submit_request or when to avoid the blocking convenience path entirely, so one comparison is left 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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