CatchAll (by NewsCatcher)

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pull_results

Retrieve clustered, validated web results from a submitted job. Get partial output while job is active, then full results when completed, iterating pages as needed.

Instructions

Retrieve the results of a job.

Can be called before completion for partial results, or after completion for the full set. Returns clustered, validated, and enriched web results. While job status is active, call this repeatedly (typically page=1) to refresh partial output. When job reaches completed, iterate all pages. If job fails, call once more to capture any partial output.

Input Schema

TableJSON Schema

Name	Required	Description
`page`	No	Page number for pagination (default: 1). Use total_pages from the response to iterate through all results.
`job_id`	Yes	The job ID returned from submit_query
`api_key`	No	CatchAll API key. Optional if provided via x-api-key header or CATCHALL_API_KEY env var.
`page_size`	No	Number of records returned per page (default: 100, max: 1000).

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jul 28, 2026

TDQS

A4.7/5.0

Behavior4/5

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

With no annotations, the description covers behavioral traits: results are clustered, validated, enriched; behavior during different job statuses; and pagination. Missing details on authentication or response format, but adequate.

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?

Five sentences, front-loaded with main purpose, then usage scenarios. No wasted words; every sentence provides essential 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?

Given output schema exists and schema covers all parameters, the description fully explains return values (clustered, validated, enriched) and pagination behavior. No missing context.

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 baseline is 3. The description adds value by explaining pagination context (use total_pages) and api_key alternatives, going beyond schema.

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 retrieves job results, specifying it can be used for partial or full results. It distinguishes from sibling tools like pull_job_csv by focusing on general job results rather than CSV output.

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?

Explicit guidance on when to call: before completion for partial results, after completion for full results, repeatedly while active, and on failure. Provides clear context for pagination and iteration.

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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