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Watermark Removal

td_watermark_removal

Remove watermarks, logos, or overlaid text from images you have rights to modify, using standard or AI Pro models. Cleaned result files are saved to disk and their paths returned.

Instructions

Watermark Removal: remove watermarks from a design. Standard or AI Pro model. Best for: cleaning watermarks, logos, stamped branding or overlaid text off images you have the rights to modify, e.g. a residual mark on a licensed stock file or old branding on archive designs. Result files are saved to disk and their paths returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dpiNoOutput resolution in ppi (72-500). Omit to keep the image's own resolution.
waitNoWait for the job and save the outputs (default true). false returns the task_id right after submit.
imageYesSource image: a local file path or an http(s) URL. PNG, JPEG or WebP, up to 80 MB and 5000 px per side.
modelNoModel: standard (Standard, Recommended): Our standard watermark remover. Fast and reliable for most marks. ai_pro (AI Pro): Our AI model for tougher watermarks, logos and overlaid text. Costs more credits. Required: pass the mode the user named. If the user did not name one, omit it and the tool returns the modes to show them; never choose for the user.
output_dirNoFolder to save results in. Default: the folder of the input image (or the current directory for URL inputs). Files are never overwritten.
estimate_onlyNoOnly return the credit estimate; nothing is uploaded or charged.
review_settingsNoOmit it and the tool first asks whether to use the recommended settings or adjust them (unless the call already sets some). true: ask each setting one by one. false: run with the given or recommended settings without asking; pass it only after the user chose that.
timeout_secondsNoHow long to wait for the job before returning its task_id (default 240).
unlimited_bundleNoRequest the Unlimited bundle for this run (only has effect on Unlimited plans; the server decides).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=true, idempotentHint=false), so the bar is lower. The description usefully adds that results are written to disk and paths returned, and flags the rights-to-modify constraint, but does not expand on credit consumption or the point at which the model must be specified by the user.

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?

The purpose and target artifacts are front-loaded, and the text is compact with no filler. The "Best for" list is slightly dense but every clause carries usable scoping information.

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 nine-parameter tool with full schema coverage and no output schema, the description supplies the missing return-value context (files saved to disk, paths returned) and the rights caveat. It is adequate and largely complete; only the omission of credit/processing implications keeps it from the top.

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% and all nine parameters are thoroughly documented in the schema, including the model-selection rule and output_dir behavior. The description only echoes the "Standard or AI Pro model" distinction and adds no format, default, or syntax detail beyond the schema, 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?

The description names a specific verb and resource ("remove watermarks from a design") and scopes the target artifacts precisely (watermarks, logos, stamped branding, overlaid text). It does not, however, explicitly differentiate itself from closely related siblings such as td_background_removal or td_fabric_texture_removal, leaving that separation 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 Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Best for: cleaning watermarks... e.g. a residual mark on a licensed stock file or old branding on archive designs" gives clear, concrete usage context. It stops short of stating when NOT to use it or naming an alternative tool, so it is strong but not exhaustive.

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