MicroScrape

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

The description discloses key behaviors: it returns only the first element matching each selector, trims text content, and costs $0.010 USDC per call via x402. This adds meaningful context beyond the schema, though it does not specify behavior when no element matches.

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 extremely concise: one sentence for the core behavior and one for pricing. Every word adds value, and the key information is front-loaded.

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?

The description covers the essential behavior and cost, and the output schema exists to detail returns. It lacks explicit notes on edge cases (e.g., missing selectors, redirects), but these are not critical for correct invocation. Overall, it is well-rounded.

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 already provides full descriptions for both parameters, including an example for the fields object and max 25 fields limit. The description adds no additional parameter-level detail beyond the schema, so a baseline score of 3 is appropriate.

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 title and description clearly identify the tool as extracting structured field values from a webpage using CSS selectors. It distinguishes itself from sibling tools (links, metadata, full scrapes) by focusing on specific field extraction with custom selectors.

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 clear context: it takes a map of field names to CSS selectors and returns trimmed text for first matches. However, it does not explicitly mention alternative tools or when to prefer this over links_url/metadata_url/scrape_url, so it lacks explicit exclusion guidance.

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, the description adds valuable behavioral context: it discloses the cost per call and the exact return content (every link and anchor text). It does not cover error handling or authentication, but the core behavior is clear.

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 a single sentence with front-loaded action and essential information. No wasted words, and the pricing note is concise.

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?

For a simple single-parameter tool with an output schema, this description is complete: it states the return value, the resource (links), and the cost. The agent has enough to select and invoke it correctly.

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 input schema already fully describes the 'url' parameter with 100% coverage. The description adds no additional parameter-level details, so it stays at the baseline of 3.

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 what the tool does: 'Returns every internal and external link with its anchor text.' This is a specific verb and resource, distinguishing it from sibling tools like scrape_url or metadata_url.

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?

No explicit guidance on when to use this tool versus alternatives. The mention of pricing and an API reference does not help an agent decide between this and sibling tools.

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, the description must carry the transparency burden. It discloses the cost per call and the scope limitation (no full-page content), which is useful. Yet it omits other behaviors such as error handling, authentication requirements, or rate limits, which are relevant for a paid API call.

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 two short sentences, front-loaded with the key selling points (cost, metadata-only scope), and contains no filler. Every word earns its place.

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?

The tool is simple (one parameter, no nested objects) and has an output schema, which covers return structure. The description covers purpose, cost, and scope, leaving only minor gaps such as explicit usage exclusions or error behavior, which are not critical for this low-complexity tool.

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 input schema provides full coverage (100%) of the single `url` parameter with a clear description. The tool description adds no additional parameter-specific semantics beyond what the schema already states, so the default baseline of 3 applies.

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 title explicitly lists the extracted data (title, description, Open Graph tags, favicon), and the description adds 'metadata-only extraction' and 'no full-page content,' clearly distinguishing it from the full-page scraping sibling. This is a specific verb+resource+scope definition.

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 implies usage for cheap metadata-only needs via 'Cheap metadata-only extraction' and highlights the cost, which helps decide between this and more expensive full-page tools. However, it does not explicitly name alternative tools or state when not to use it, so it stops short of full guidance.

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?

No annotations are provided, so the description carries the full burden. It adds useful context like the $0.005 USDC cost and the 'public URL' constraint, but it does not disclose behavior around redirects, failures, JavaScript rendering, rate limits, or auth requirements. Basic transparency but not comprehensive.

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?

Two sentences, front-loaded with the primary purpose, followed by pricing info. No redundant phrases; every word earns its place.

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?

The tool is simple (one parameter, output schema present) and the description covers core purpose, URL type, and cost. Minor gaps exist around error handling and edge cases, but given the tool's simplicity, the description is sufficiently complete.

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% and the single 'url' parameter is already clearly described. The description adds 'public' and 'clean Markdown' framing but no new syntax or format details beyond what the schema provides. Baseline 3 is appropriate.

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 states a clear verb ('Fetches'), a specific resource ('a public HTTP/HTTPS URL'), and the output ('primary content as clean Markdown'). It implicitly distinguishes from sibling tools (extract_fields, links_url, metadata_url) by focusing on full-page content conversion to Markdown.

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 makes it clear this is for fetching public URLs and getting clean Markdown, which implies its use case. It does not explicitly say when not to use it or mention alternatives (e.g., extract_fields for structured data), but the context is strong enough for basic selection.

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