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codeiva11
by codeiva11

solve_captcha

Automate CAPTCHA solving and form completion for web automation and testing. Handles JavaScript widgets, image text, and interactive verification with intelligent field mapping and human-like input.

Instructions

Automate form completion and interactive widget verification on web pages. Supports JavaScript-based challenge widgets, image text transcription, and intelligent form field mapping for QA and automated browsing workflows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoText recognition language code: eng, hin, or eng+hineng
typeNoWidget type: js_widget (JavaScript-based embedded challenge widget), text (text transcription verification), image (image-based input), auto (detect automatically).auto
iframeNoTarget a specific iframe by index
submitNoSubmit the form after filling all fields
aiMatchNoMatch form fields by semantic similarity even if names differ
timeoutNo
formDataNoKey-value pairs of form fields to fill (field names matched automatically to page inputs)
humanLikeNoType with variable keystroke delays
maxRetriesNoMaximum refresh attempts before giving up
allowedCharsNoCharacter set allowed in the answer
analyzeFirstNoInspect page structure before filling fields
formSelectorNoCSS selector for the form element (auto-detected if not provided)
inputSelectorNoCSS selector for the answer input field
expectedLengthNoExpected character length of the answer
iframeSelectorNoTarget a specific iframe by CSS selector
widgetSelectorNoAlias for captchaSelector
captchaSelectorNoCSS selector targeting the verification element, canvas, image, or interactive widget container
refreshSelectorNoCSS selector for the reload/refresh button
preferTextFallbackNoReturn text-only guidance instead of an image when the model cannot process images

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv3.2.13

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It states that the tool automates form completion and widget verification, but it doesn't disclose side effects like form submission, page interaction, retries, or the risk of triggering anti-bot protections. Key behavioral parameters such as submit, maxRetries, and humanLike are left to the schema rather than explained in the description.

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 description is short and structured as two sentences without filler. It loses a point because 'interactive widget verification' is vague euphemism for captcha solving and the first sentence could more directly state the tool's unique purpose.

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

Completeness2/5

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

This is a complex tool with 19 parameters, no annotations, and no output schema, so the description must carry substantial context. It provides an overview of capabilities but omits return behavior, failure modes, and how it composes with the other browser automation siblings. An agent would need to infer important invocation context from the schema alone.

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 high (95%), so the baseline is 3. The description adds no parameter-level detail, but nearly every parameter already has a clear schema description, including the enum for type and selectors for captcha-specific targeting.

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 clearly identifies the tool's verb (automate) and resources (form completion, interactive widget verification on web pages), and lists concrete supported capabilities like JavaScript challenge widgets and image text transcription. However, it doesn't explicitly differentiate itself from sibling tools like type or click, relying on the tool name and higher-level scope to set it apart.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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

There is no guidance about when to use this tool versus alternatives such as type, click, or execute_js. The mention of 'for QA and automated browsing workflows' provides a general audience but not conditions, exclusions, or alternative tool routing.

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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