extract_clean_markdown

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

With no annotations provided, the description carries the burden and does well by disclosing what is stripped (scripts, navbars, cookie banners, DOM bloat) and what is added (YAML frontmatter with title, description, canonical URL, timestamp, token metrics). It does not cover failure modes, dynamic-page handling, or rate limits, but the core transformation 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?

Two tightly written sentences front-load the action and output format, then list the cleaning behavior. Every clause adds relevant information with no repetition or 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 simple one-parameter extraction tool without an output schema, the description is complete enough: it explains the input, the transformation, the output format, and the intended downstream use. No critical context is missing for an agent to decide to call it.

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 coverage is 100%, and the single url parameter is already documented as accepting a full URL or domain. The description adds only the 'live web URL' framing and does not clarify the domain-input form or any URL normalization behavior beyond what the schema provides.

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 specific verb and resource: convert a live web URL into clean GitHub-Flavored Markdown. It also names the output format and frontmatter fields, making the tool's purpose immediately distinguishable from the domain-enrichment and audit siblings.

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 optimal LLM context ingestion' implies when the tool is useful, but there is no explicit when-to-use or when-not-to-use guidance. No sibling alternative is mentioned, so the agent must infer that this is the conversion tool rather than one of the analysis tools.

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