extract_markdown

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

With no annotations at all, the description carries the behavioral burden and mostly meets it: it discloses that content is stripped (boilerplate, scripts, ads, navigation chrome) and that output is token-efficient Markdown. It does not cover failure modes, rate limits, or precedence when both url and raw_html are supplied.

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?

Three short sentences lead with the core definition and immediately provide the key transformation detail. The 80–95% token-reduction claim adds value for an LLM-context tool and no sentence is redundant.

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 plus a fully documented schema is adequate for basic invocation, but with no output schema and no annotations it leaves some gaps: the exact return format is only implied as Markdown, and there is no guidance on error cases or how distill_context is different. A small note on precedence/edge cases would round it out.

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 the schema already documents url, raw_html, and include_links. The description adds no parameter-level detail beyond restating that the tool scrapes URLs or parses raw HTML, so it stays at the baseline 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 opens with a concrete noun phrase, “Web-to-Markdown context compressor,” and specifies the exact action: scraping URLs or parsing raw HTML into Markdown. It is clear about the resource and output, though it does not explicitly differentiate itself from the sibling tool distill_context.

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 gives a clear use context: whenever a web URL or raw HTML needs to be compressed into token-efficient Markdown. It does not provide explicit exclusions or name alternatives like distill_context, but the input domain is specific enough to guide selection.

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