Fetch any URL and extract its readable text with boilerplate removed, so you can read an article found through search in full depth.
Fetch a URL and extract its readable text (boilerplate stripped), for reading an article found via search in more depth.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL to fetch. | |
| max_length | No | Max characters to return (default 4000). |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It discloses that the tool fetches a URL and returns boilerplate-stripped readable text, which is good. However, it does not mention potential failure modes, handling of non-HTML content, external network side effects, or any constraints—leaving some behavioral gaps.
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, tightly worded sentence conveys the action, the output format, the key behavioral detail (boilerplate stripping), and the intended use case. 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?
For a two-parameter tool with fully documented parameters and no output schema, the description is largely sufficient: it explains the output (readable text), the processing (boilerplate stripped), and the workflow context. It only lacks explicit alternative routing and edge-case behavior.
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 parameters are already documented. The description adds no parameter-level meaning beyond what the schema provides, so the baseline 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 description uses a specific verb-resource pair ('Fetch a URL and extract its readable text') and states that it strips boilerplate. This clearly distinguishes it from the sibling search tools, which find content rather than fetch and read a specific 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?
The phrase 'for reading an article found via search in more depth' gives a clear contextual trigger: use this after search, when a result needs deeper reading. It does not explicitly name the alternatives or state when not to use it, but the intended workflow is inferable from the sibling names and the stated purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.