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ZenRows
by ZenRows

crawl_results

Read-only

List the URLs kept by a crawl in order, track content status, and use next_cursor to resume partial runs and fetch newly kept pages.

Instructions

List the URLs a crawl kept, in the order it kept them, following the API's pages up to limit.

Each result has url and, when the crawl has output_format, content_status (pending, fetched, failed) and, once fetched, content_url: pass it to crawl_content as content.

While the crawl runs the list is partial (partial=true): call again later with the returned next_cursor to get only the URLs kept since. A stopped crawl can still add URLs from pages fetched before the stop for up to 10 minutes, so next_cursor stays set during that window: call again later. next_cursor is null once the crawl ended and every URL was read.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return in this call (default 100, max 10000)
cursorNonext_cursor from a previous crawl_results call, to continue from there
crawl_idYesCrawl id returned by crawl_create (c_…)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.7.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already establish read-only/safe, but the description adds substantial behavior beyond them: partial=true during a run, the 10-minute post-stop window where next_cursor stays set, the exact condition for next_cursor becoming null, and the content_status lifecycle (pending/fetched/failed). This is rich, non-obvious disclosure.

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?

Three tight paragraphs, each front-loaded with the point (what it lists, what a result contains, pagination lifecycle) and no filler. Slightly longer than strictly necessary but every sentence carries distinct information.

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?

With no output schema, the description fully carries the burden: it names the returned fields (url, content_status, content_url) and their meaning, plus the cursor lifecycle an agent must handle to call this correctly across runs.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds real semantics the schema lacks: next_cursor returns only URLs kept since the last read (incremental pagination) rather than a plain continuation. Limit behavior is left to the schema, which already documents it fully.

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?

States a specific verb (list), resource (URLs a crawl kept), and ordering/scope constraint (in the order it kept them, paginated up to limit). This clearly separates it from crawl_get (status), crawl_content (fetch body), and crawl_list (enumerate crawls).

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?

Gives explicit operational context: call again with next_cursor while partial=true, and wait up to 10 minutes after a stop. It also routes the agent onward ('pass it to crawl_content as content'). It stops short of explicitly contrasting when to prefer crawl_get or crawl_wait instead, so it is strong context rather than full when/when-not guidance.

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