scrape_docs

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

The description discloses key behaviors: file creation (SKILL.md, reference files), auto-detection of llms.txt for speed, and fallback to HTML scraping. However, it lacks details on overwrite behavior, idempotency, or side effects, which are important for a file-creating tool.

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?

The description is concise with three front-loaded sentences. Each sentence adds distinct value: core purpose, config support, and processing optimization. No wasted words.

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?

Despite having an output schema, the description omits parameter semantics and behavioral details like overwrite behavior. Given the tool's complexity (6 parameters, file creation), the description is insufficient for complete agent understanding.

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?

With 0% schema description coverage, the description fails to explain any of the 6 parameters. While parameter names like 'dry_run' and 'skip_scrape' are somewhat self-explanatory, the description adds no clarification, especially for 'merge_mode' and 'enhance_local'. This is a critical gap.

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 the tool scrapes documentation and builds an LLM skill, mentioning file creation and processing modes. However, it does not explicitly differentiate from sibling scraping tools like scrape_generic or scrape_codebase, leaving room for ambiguity.

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 does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention when not to use it. Usage is implied from the purpose but not clearly delineated.

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