pinkpixel-dev-web-scout-mcp

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool 'returns a well-structured list of findings' and defaults maxResults to 10, but lacks details on rate limits, authentication needs, error handling, or what 'well-structured' entails. For a search tool with no annotation coverage, this leaves significant gaps in understanding its operational behavior.

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

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

The description is appropriately sized with two sentences that efficiently cover the tool's function and parameters. It is front-loaded with the core purpose, though the second sentence could be slightly more streamlined by avoiding repetition of 'Input'.

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

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

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and parameters but lacks details on output format, error cases, and behavioral traits. Without annotations or an output schema, more context on what 'well-structured list' means would improve completeness.

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

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

Schema description coverage is 100%, with both parameters (query and maxResults) fully documented in the schema. The description adds minimal value beyond the schema: it reiterates that query is for 'keywords, question, or topic' and notes the default for maxResults, which is already in the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Initiates a web search query using the DuckDuckGo search engine and returns a well-structured list of findings.' This specifies the verb ('initiates a web search'), resource ('web search query'), and engine ('DuckDuckGo'), distinguishing it from the sibling tool UrlContentExtractor. However, it doesn't explicitly contrast with the sibling beyond mentioning the engine.

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

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

The description provides no guidance on when to use this tool versus alternatives like UrlContentExtractor. It mentions the query input and maxResults default but offers no context about appropriate use cases, prerequisites, or exclusions. Usage is implied through parameter descriptions but not explicitly stated.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool fetches and extracts content but lacks details on potential issues like rate limits, authentication needs, error handling, or what 'extracts content' entails (e.g., text, HTML, metadata). This leaves significant gaps in understanding its behavior.

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

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

The description is appropriately sized and front-loaded, with the core purpose stated first. Both sentences are relevant, but the second sentence could be slightly more concise by combining the single and multiple URL explanations without repetition.

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

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

Given the lack of annotations and output schema, the description is incomplete for a tool that performs web content extraction. It doesn't explain what 'extracts content' means in terms of output format, potential limitations (e.g., JavaScript-rendered content), or error scenarios, leaving the agent with insufficient context for reliable use.

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

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

The schema description coverage is 100%, so the schema already fully documents the 'url' parameter as a string or array of URIs. The description adds minimal value by restating this in plain language without providing additional context, such as URL format constraints or performance implications of array inputs, aligning with the baseline score for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('fetches and extracts content') and resource ('from a given webpage URL'), making it easy to understand what it does. However, it doesn't explicitly differentiate from its sibling tool DuckDuckGoWebSearch, which likely serves a different search-oriented purpose rather than direct content extraction.

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

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

The description provides no guidance on when to use this tool versus alternatives, such as DuckDuckGoWebSearch. It mentions the ability to handle single or multiple URLs but doesn't clarify scenarios where one might prefer this over other tools or when it's inappropriate to use.

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