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Scrape a URL (quality-gated)

scrape_url

Scrape a public web page into clean markdown, with automatic quality checks and retries for stronger crawling when needed.

Instructions

Scrape a public web page into clean markdown in one call: runs a crawler, waits, scores the result (completeness, bot-wall detection), and automatically retries with stronger settings when quality is low. Costs Apify credits per run. For arbitrary actors or fire-and-forget runs use run_actor instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic http(s) URL to scrape
max_pagesNoHow many pages to crawl starting from the URL (same site)
max_tokensNoToken budget for the returned page content
quality_retryNoRe-run with residential proxies / a browser crawler when quality is low

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pagesYes
run_idYes
qualityYes
attemptsYes
truncatedYes
dataset_idYes
Behavior5/5

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

The description significantly enriches the sparse annotations. It discloses cost ('Costs Apify credits per run'), the multi-step behavior ('runs a crawler, waits, scores the result... automatically retries with stronger settings'), and quality criteria ('completeness, bot-wall detection'). This contextualizes the non-read-only and open-world hints beyond what annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences: the first states the core function and mechanism, the second covers cost and the sibling alternative. Every clause adds value without redundancy or fluff, making it well-structured and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite the tool's moderate complexity (4 params, output schema, annotations), the description covers the purpose, workflow, retry logic, cost, and a key alternative. The output schema exists to define return values, so the description doesn't need to explain them. It is complete for an agent to select and invoke the tool appropriately.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already explains all four parameters clearly. The description adds useful pipeline context (e.g., 'automatically retries with stronger settings' clarifies quality_retry) but does not individually elaborate on parameter syntax or defaults beyond schema, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's specific functionality: 'Scrape a public web page into clean markdown in one call.' It distinguishes from sibling tools by explicitly naming run_actor as the alternative for 'arbitrary actors or fire-and-forget runs.' This is a specific verb+resource+result with clear differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use guidance, noting it is for quality-gated scraping with automatic retries. It also gives an alternative: 'For arbitrary actors or fire-and-forget runs use run_actor instead.' While it doesn't address all siblings, the key distinction from the closest alternative is clear.

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

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