Fetch a public webpage and convert it into clean, token-efficient LLM Markdown with metadata and token count for reliable downstream processing.
Fetch any public webpage and convert it into clean, token-efficient LLM Markdown with metadata and token count ($0.005 USDC on Base).
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public http/https URL to convert to Markdown | |
| maxChars | No | Maximum Markdown characters (500-50000, default 15000) |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It usefully discloses the price ($0.005 USDC on Base) and that the response includes metadata and a token count, but it omits payment mechanics, failure behavior on non-public/inaccessible URLs, and rate limits for a paid operation.
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?
A single sentence that front-loads the core action and folds in the output shape and cost. No filler.
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 two-parameter tool with a fully described schema and no output schema, the description covers the transformation, expected return elements (metadata, token count), and cost. Only payment flow and error conditions remain unstated.
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%, so both url and maxChars are already documented with format, range, and default. The description adds nothing about parameters, so baseline 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?
States a specific verb+resource: fetch a public webpage and convert it to clean Markdown. The output characteristics (token-efficient LLM Markdown, metadata, token count) are named, and no sibling tool overlaps with this scraping/conversion function.
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?
'Fetch any public webpage' implies the scope of use, but there is no explicit when-to-use, when-not-to-use, or alternative guidance. The public-only constraint is stated but framed as capability rather than a restriction on when to call it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.