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KSDeshappriya

FindIt

findIt_scrap

Extract and process content from specified URLs for research and content analysis, with optional image extraction.

Instructions

Extracts and processes content from specified URLs, supporting in-depth content analysis and optional image extraction. Perfect for research and content gathering tasks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesList of URLs to extract content from.
extract_depthNoDepth of extraction - basic extracts main content, advanced attempts to get more detailed content.basic
include_imagesNoInclude a list of images extracted from the URLs in the response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations, the description carries the full burden and falls short: it says nothing about authentication, rate limits, failure behavior on unreachable URLs, whether JavaScript is rendered, or how batch URLs are handled. 'Processes' is left undefined, and the only behavioral hints (depth modes) merely restate the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences that are front-loaded with the core action, which is good. The second sentence, 'Perfect for research and content gathering tasks,' is unsupported marketing filler that consumes space without informing invocation.

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?

With no annotations and no output schema, the description should explain what a call returns (extracted text shape, image list) and how partially failed URLs are reported. It provides none of this, so an agent cannot predict results or handle errors from the definition 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 100%, so all three parameters are already documented in the schema, making 3 the baseline. The description's mention of 'in-depth content analysis' and 'optional image extraction' loosely parallels extract_depth and include_images but adds no syntax, defaults, or trade-off detail beyond the schema.

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 states a concrete verb and resource: 'Extracts and processes content from specified URLs,' with optional image extraction. An agent can tell it is a URL-scraping tool, though it never names or contrasts itself with the sibling findIt_google, leaving their division of labor 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 Guidelines2/5

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

The only guidance is the vague marketing line 'Perfect for research and content gathering tasks,' which does not say when to pick this over findIt_google, when not to use it, or what prerequisites (e.g., already having URLs) exist. No alternative is named.

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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