url_to_markdown
Fetch a URL and return its main text content as clean, readable plain text/markdown-ish output. Strips scripts, styles, and HTML tags.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL to fetch |
Fetch a URL and return its main text content as clean, readable plain text/markdown-ish output. Strips scripts, styles, and HTML tags.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL to fetch |
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 does disclose that scripts, styles, and HTML tags are removed, which is useful. It does not mention redirects, JavaScript rendering, timeout/error behavior, or whether the output can be parsed as markdown vs plain text, leaving some important edge cases undisclosed.
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 with no filler. The first sentence front-loads the core action and expected output; the second adds a specific, valuable detail about content stripping. Every sentence contributes, and the structure is easy to scan.
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 has one required parameter, no annotations, and no output schema, so the description must cover the core contract. It states the input, the output format, and the transformation behavior. It lacks edge-case information such as failure handling and redirects, but for a simple fetch-and-extract tool this is sufficient for an agent to call 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?
Schema description coverage is 100% — the url parameter is already described as 'The URL to fetch.' The description's 'Fetch a URL' phrase echoes the schema without adding new meaning. With full schema coverage, a baseline of 3 is appropriate; the description does not compensate with extra parameter details.
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 a specific action (fetch), a specific resource (URL), and the precise output (main text content as plain text/markdown). It also notes the stripping of scripts, styles, and HTML tags. Among the many sibling diagnostic tools, this is the only one focused on content extraction, so it is easy to distinguish.
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 when to use the tool: whenever an agent needs the readable text content of a webpage. However, it provides no explicit alternatives, exclusions, or conditions such as 'use this when you need page text' or 'not for checking site health.' The context is clear enough but left entirely to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools audit overlapping site signals (seo_audit vs structured_data_extract vs tech_stack_fingerprint; page_performance_check vs pagespeed_insights; ssl_cert_check vs ssl_labs_grade; broken_link_check vs sitemap_url_validator), so an agent could initially pick the wrong one. Descriptions usually clarify the distinction, but the boundaries are not always obvious.
Most names follow a snake_case target+operation pattern (ssl_cert_check, email_deliverability_check), but check_open_ports and check_robots_sitemap reverse the order, and the action suffixes vary widely (check, audit, validate, lookup, extract, grade, report, insights). Still readable, but not a single predictable convention.
At 29 tools, the server is above the 25-tool threshold and feels like an undifferentiated grab bag of single-purpose audits rather than a tightly scoped toolkit. Many checks could be consolidated (e.g. the separate SSL and performance tools, or domain_report versus its component checks).
For a web/domain/email/security diagnostics toolbelt, the coverage is unusually broad: DNS, TLS, email, SEO, structured data, vulnerabilities, ports, redirects, and more are all represented. Minor gaps exist (no generic HTTP request/debug tool, no zone-transfer or full WHOIS history), but agents can accomplish most diagnostic workflows without hitting dead ends.