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acquire

Crawl any storefront page once to get a complete structured payload with products, facets, screenshots, performance metrics, trust signals, analytics, and more — enabling full offline audit.

Instructions

Acquire a complete structured payload from a storefront page in a single crawl. Returns products, facets, sort options, desktop + mobile screenshots, performance metrics, aggregated trust signals, analytics tracking summary, data quality fill rates, navigation structure, and automatically sampled PDP details — all in one call. Use this as the primary entry point for any storefront audit. The payload is designed for offline analysis: call acquire once, then analyze against the returned data with no further live site calls. Always scrapes with Puppeteer first (free, bundled, captures analytics and network events). Falls back to Firecrawl automatically only when Puppeteer is blocked (0 products + FCP=0) and FIRECRAWL_API_KEY is set — Firecrawl costs money per call and is reserved for WAF-protected sites. A warnings[] array flags data quality issues automatically (LOW_CARD_CONFIDENCE, MOBILE_RENDER_FAILED, FCP_ZERO, ECOMMERCE_TRACKING_GAP, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull http/https URL of the category or listing page to acquire.
pdp_sampleNoNumber of PDPs to automatically sample and include in pdpSamples[] (default 2, max 5, set 0 to skip). Picks one mid-range and one premium product by price.
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so thoroughly. It discloses the scraping engine order (Puppeteer first, Firecrawl fallback), cost implications, offline-analysis design, and the warnings[] array with specific quality flag examples. This exceeds expectations.

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

Conciseness4/5

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

The description is dense yet front-loaded with a clear summary, then usage guidance, fallback details, and warnings. Each sentence earns its place, but the length and single-paragraph structure make it slightly less scannable than ideal; a 5 would require tighter organization.

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

Completeness4/5

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

For a tool with no output schema, the description lists the major data categories returned (products, screenshots, metrics, trust signals, etc.) and mentions warnings[] for quality issues. It does not specify the exact payload format, but given the breadth of the tool, the description is largely complete; minor absence of return-type detail prevents a 5.

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 coverage is 100% and both parameters have detailed descriptions. The tool description does not add meaningful parameter-specific semantics beyond referencing 'automatically sampled PDP details', which the schema already covers. Baseline 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 uses a specific verb ('Acquire') and resource ('complete structured payload from a storefront page'), immediately clarifying the tool's core function. It further distinguishes itself from sibling tools by declaring itself 'the primary entry point for any storefront audit'.

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

Usage Guidelines5/5

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

The description explicitly tells when to use this tool ('Use this as the primary entry point'), when not to rely on alternatives ('designed for offline analysis'), and provides conditional guidance for the Firecrawl fallback ('only when Puppeteer is blocked... and FIRECRAWL_API_KEY is set'), including that Firecrawl is reserved for WAF-protected sites.

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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