Tesseract

Edit a picture

edit_image

Change a picture as instructed, optionally with reference pictures, with Tesseract (charged to the signed-in account). Returns download links, or 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": {
      "image": "<image>",
      "instructions": "<instructions>"
    },
    "name": "edit_image"
  }
}

Input Schema

Name	Required	Description
`count`	No
`image`	Yes	A picture: a public https:// URL, or a data:image/…;base64,… URI (up to 10 MB).
`model`	No	An edit model from list_models (default fal-ai/nano-banana-2/edit).
`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.
`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.
`instructions`	Yes	What to change — imperative and specific.
`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.
`reference_images`	No	Pictures of what should appear or be matched.

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

A3.8/5.0

Behavior4/5

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

Annotations already cover the safety profile (not read-only, open-world, non-idempotent), and the description adds cost behavior ("charged to the signed-in account") and the dual synchronous/asynchronous return shape (download links or a job_id). It stops short of saying when a job runs async versus returns links directly, which is the main behavioral ambiguity left.

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?

A single front-loaded sentence where every clause earns its place: action, input shape, provider, billing, and return contract. Nothing is padded or repeated from the schema.

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 9-parameter, nested-schema, no-output-schema tool, the description covers the two things an agent most needs beyond the schema: that it costs money and that it may return a job to poll. Missing only the async-versus-immediate condition and any comparison with generate_image.

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 89%, so the schema already documents the parameters thoroughly, including the consent and rights fields. The description only glosses "instructions" and "reference pictures", adding no syntax, limits, or meaning beyond the schema; 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 and resource ("Change a picture") plus scope ("as instructed, optionally with reference pictures"), so an agent can tell this is a prompted edit rather than a fresh generation. It doesn't name the sibling it contrasts with (generate_image), so differentiation is inferred 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?

Usage is only implied: having a source picture plus instructions is the implicit precondition for choosing this over generate_image. The one explicit routing statement is the return path ("or a job_id for check_job"), which helps follow-up polling but is not when-to-use guidance, and no exclusions or prerequisite conditions are given.

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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