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Generate Alt Text

generate_alt_text
Destructive

Generate AI-powered alt text from an image URL to make web content accessible. Returns synchronized results and can overwrite existing descriptions.

Instructions

Generate AI-powered alt text for an image URL. Returns the result synchronously (may take a few seconds). Uses account credits; additional languages and image conversion can increase the total. Can overwrite existing alt text when requested.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic URL of the image
langNoComma-separated language codes (e.g. 'en', 'en,fr,es')
tagsNoTags for organization
asset_idNoCustom asset ID (default: auto-generated hash)
keywordsNoKeywords to incorporate
metadataNoCustom metadata (string key-value pairs)
max_charsNoMaximum character length for the alt text
overwriteNoOverwrite existing alt text if image was previously processed
gpt_promptNoCustom prompt template. Use {{AltText}} as a placeholder for the generated alt text.
negative_keywordsNoKeywords to avoid

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.4

TDQS

A3.9/5.0
Behavior4/5

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

It discloses non-obvious behavior beyond the annotations: synchronous result with a few seconds latency, account-credit usage, cost increase for languages/conversion, and conditional overwrite of existing alt text. This complements the destructiveHint/readOnlyHint annotations without contradicting them.

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?

Three short sentences with no filler; the primary action is front-loaded and each subsequent sentence adds a distinct piece of behavioral or billing context. Very efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 10-parameter, no-output-schema tool, the description covers the important high-level behaviors (latency, cost, overwrite), but it does not describe the shape or content of the returned result beyond 'the result.' It also introduces 'image conversion' without tying it to a listed parameter, leaving some ambiguity.

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 the descriptions of all 10 parameters already carry most meaning. The tool description adds only a couple of value-added links (language selection affects credits; overwrite only happens when requested), which is useful but not a major contribution beyond 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 specific verb and resource ('Generate AI-powered alt text for an image URL'), and the URL input distinguishes it from the sibling generate_alt_text_from_file. The purpose is unambiguous and not a restatement of the name.

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 description gives useful context for deciding to call it—synchronous latency, credit consumption, and optional overwrite—but it never explicitly states when to choose this tool over generate_alt_text_from_file or mentions alternatives. The URL qualifier implies the intended input, so usage is inferable but not spelled out.

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