Call a target scraper

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds real behavioral context beyond that: a `run_js` in `params` returns a job id that must be polled, same as `scrape`. It does not cover error modes or how the job id maps to `check_scrape`/`read_scraped`, but the key async trait is disclosed.

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?

Four short sentences, front-loaded with the core action and the sibling distinction, then the workflow, then the async caveat. No filler; every sentence carries operational information.

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?

An output schema exists, so return values need not be explained, and the description still flags the job-id polling case. Endpoint sourcing, parameter sourcing, and the alternative tool are all covered, leaving nothing an agent needs before calling.

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 baseline is 3, and the description goes further by telling the agent not to guess `params` keys and to source them from `list_scrapers(endpoint)`. That discovery guidance is genuine added value for an open `additionalProperties: true` object.

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?

States a specific verb and resource — 'call a target-specific scrape endpoint with its own parameters' — and explicitly contrasts itself with the generic `scrape` sibling. An agent can distinguish this from `scrape`, `search`, or `extract` without opening any schema.

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?

Gives an explicit ordered workflow: look the endpoint up with `list_scrapers()`, read its parameters with `list_scrapers(endpoint)`, then call it here. It also names the alternative (`scrape` for arbitrary URLs) and the condition that selects it.

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