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Change the text in an image

replace_text

Change or remove text in a photo or screenshot and keep the same font, colour and background. Give each line to change as { from, to }: "from" is the text as it appears in the image, "to" the new text (empty to remove it). Up to 20 lines per image; 1 credit per image. The image is scanned first; if a "from" is not found, nothing is charged and the error lists the lines that were read. IDs, certificates, receipts, invoices and bank documents are refused. Waits up to 50 seconds; if still editing, call get_edit.

Input Schema

NameRequiredDescriptionDefault
hintNoOptional: where the text is when it appears more than once, e.g. "the line at the bottom".
localeNoLanguage of the person asking (for our statistics only). Default en.
image_urlNoPublic https URL of the image (PNG or JPG).
image_base64NoThe image as base64, with or without a data: prefix. Use when there is no URL.
replacementsYes
wait_secondsNoHow long to wait for the result before returning, 0 to 50 seconds.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Adds substantially beyond the annotations: 1 credit per image, no charge when a 'from' is not found, refusal of official documents, 20-line cap, 50-second wait and async fallback. The unbilled-failure and refusal policies are exactly the behavioral facts annotations can't express.

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 purpose, then payload format, then limits, then billing/failure semantics, then timeout fallback. Every sentence carries an operational fact; nothing is filler.

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?

Covers cost, limits, refusal policy, error content and timeout behavior for a mutation tool with no output schema. Only the shape of a successful response (what IDs or result fields come back) is left unspecified, which is minor since get_edit is named for follow-up.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 83%, so baseline is 3, but the description adds real meaning: 'from' is the text as it literally appears, 'to' empty means delete, and the 20-line limit is restated as an operational constraint. It doesn't explain hint, locale, or the image_url/image_base64 choice, leaving some parameters to the schema.

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 concrete verb and resource ('Change or remove text in a photo or screenshot') plus the quality constraint (same font, colour, background), which immediately separates it from scan_text (read-only) and get_edit (status check). An agent can route on this sentence alone.

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?

Gives explicit preconditions and exclusions: documents like IDs, certificates, receipts are refused, and if the edit is still running 'call get_edit'. It also explains the scan-first validation path. It does not explicitly contrast with scan_text, so it falls just short of full when/when-not coverage.

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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