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Zyte MCP Server

scrapy_cloud_get_job

Get one Scrapy Cloud job: state, close_reason, spider, tags, who scheduled and cancelled it, pending/running/finished times (ms), spider_args and job_settings (credential-like values masked) and 'scrapystats', Scrapy's counters such as item_scraped_count, downloader/response_status_count/, log_count/ERROR, retry/count, memusage/max and scrapy-zyte-api/*. A healthy finished job has close_reason 'finished'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobYesJob key in project/spider/job form, for example 123/1/4.

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the behavioral burden. It discloses useful specifics like masked credential-like values in spider_args, job_settings, and the meaning of close_reason 'finished', but does not cover permissions, error behavior, or the exact format of the response.

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?

It's a single, dense sentence that packs a lot of field-level detail without unnecessary repetition. Front-loaded with the core action and resource, though the list of fields makes it somewhat long.

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?

Given the absence of an output schema, the description provides substantial value by enumerating the returned fields, including scrapystats and masked settings. It still lacks details on error handling, rate limits, or authentication requirements, which would be needed for a fully complete picture of a network-dependent retrieval tool.

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%, so the schema already documents the single 'job' parameter with a regex pattern and example. The description adds no parameter-specific information, which is acceptable given the high schema coverage baseline.

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

Purpose4/5

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

States a specific verb+resource ('Get one Scrapy Cloud job') and enumerates the rich fields returned. It's clear the tool retrieves a single job, distinguishing it from list_jobs, but does not explicitly name siblings like scrapy_cloud_get_job_items or scrapy_cloud_get_job_log.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. It doesn't explain the difference between this and scrapy_cloud_get_job_items, scrapy_cloud_get_job_log, or scrapy_cloud_list_jobs, leaving the agent to infer usage from the name alone.

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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