Tesseract

Make pictures

generate_image

Make pictures from words with Tesseract, charged to the signed-in account (its plan's free media first, then its allowance or balance). Waits up to about 40 seconds and returns download links (valid for an hour); if it takes longer, returns a job_id for check_job.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "prompt": "<prompt>"
    },
    "name": "generate_image"
  }
}

Input Schema

Name	Required	Description
`count`	No	How many pictures (default 1).
`model`	No	A picture model from list_models (default fal-ai/nano-banana-2).
`params`	No	The model's own fields (fal.ai's names), e.g. {"aspect_ratio": "16:9", "seed": 7}. A field the model's price does not cover is refused, never sent.
`prompt`	Yes	What to make — be descriptive.
`max_usd`	No	The most this may cost, in US dollars: a dearer job is not started.
`rights_ok`	No	With a source video of someone else's: true only when the person says the video and its sound belong to their makers, and the result is for their own use unless they hold the rights.
`aspect_ratio`	No	The shape, e.g. "16:9", "1:1", "9:16", for models that take one.
`likeness_consent`	No	Only when the person asked for it themselves, about who is shown: "self" (them), "consented" (an adult who agreed to it) or "made-up" (a made-up person) — and only when nobody shown is under 18 or a public figure, and there is no nudity or sexual content. Needed by the effects that put a person in, talking or lip-synced people, headshots and try-ons.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedNov 10, 2026

addedInput schema / properties / likeness_consent

Added value: +{
+  "description": "Only when the person asked for it themselves, about who is shown: \"self\" (them), \"consented\" (an adult who agreed to it) or \"made-up\" (a made-up person) — and only when nobody shown is under 18 or a public figure, and there is no nudity or sexual content. Needed by the effects that put a person in, talking or lip-synced people, headshots and try-ons.",
+  "enum": [
+    "self",
+    "consented",
+    "made-up"
+  ],
+  "type": "string"
+}

addedInput schema / properties / rights_ok

Added value: +{
+  "description": "With a source video of someone else's: true only when the person says the video and its sound belong to their makers, and the result is for their own use unless they hold the rights.",
+  "type": "boolean"
+}

First observedNov 7, 2026

TDQS

A3.9/5.0

Behavior5/5

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

It discloses cost behavior (charged to the signed-in account, plan free media first, then allowance or balance), a latency ceiling (~40 seconds), the return payload (download links valid one hour), and the async escape hatch (job_id). None of that is inferable from the annotations, which only mark it as non-readonly, open-world, non-idempotent.

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 clauses, front-loaded with the capability and immediately followed by cost and latency/return behavior; no filler sentences. The parenthetical billing clause is dense but each element (free media, allowance, balance) carries distinct meaning.

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?

With no output schema, the description correctly supplies return shape (links with a one-hour TTL, or a job_id) and the cost ceiling behavior is covered by max_usd in the schema. What's missing is relative guidance against edit_image for an 8-parameter, nested-object tool where the choice between generating and editing is the main decision an agent faces.

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 coverage is 100%, so all eight parameters, including the nested params object and the likeness_consent enum, are already documented in the schema. The description adds no parameter-level meaning beyond the billing context already credited under transparency, so the baseline 3 applies.

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?

"Make pictures from words with Tesseract" gives a specific verb (make), resource (pictures), and input modality (words), which implicitly separates it from edit_image and the video siblings. It never names an alternative explicitly, so differentiation is inferential rather than stated.

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 only routing guidance is the fallback: if generation exceeds ~40 seconds, call check_job with the returned job_id. There is no statement of when to choose this over edit_image or apply_effect, and no prerequisites beyond the billing note.

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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