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List extraction jobs

jobs
Read-only

List extraction jobs with optional filters. Filter by job ID, URL, status (pending, running, completed, failed), output format, or date range. Results are paginated; use 'page' and 'page_size' to navigate large result sets. Requires a Geonode API key, sent as the X-Api-Key header.

Input Schema

NameRequiredDescriptionDefault
urlNo
pageNo
job_idNo
outputNo
api_keyNo
end_dateNo
page_sizeNo
job_statusNo
start_dateNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already establish readOnly=true, destructive=false, openWorld=false, so safety is covered. The description adds genuinely non-derivable context: an API key is required and must be sent as the X-Api-Key header, and results are paginated. It stops short of describing sort order or what a result row contains.

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?

Four short sentences, front-loaded with purpose then filters, pagination, and auth — no filler. The one redundancy is restating 'page' and 'page_size' by name when they are already visible in the schema.

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 9-parameter, no-output-schema, read-only listing tool, the definition covers filters, pagination, and authentication — the three things an agent needs to call it correctly. What is missing (default page_size=100, ordering, and correct enum values) is small in volume but the enum error is consequential.

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

Parameters2/5

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

Schema coverage is 0%, so the description must carry parameter meaning — and it does map most parameters (job_id, url, job_status, output, start_date/end_date, page, page_size). However, it documents the status vocabulary as "pending, running, completed, failed," which conflicts with the schema enum (queued, processing, completed, failed, cancelled); an agent following the description would send invalid values. api_key is described only as a header, not as a parameter.

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?

Clear verb + resource: "List extraction jobs with optional filters." The tool's read/listing nature and supported filter dimensions are unambiguous. It does not, however, distinguish itself from near-name siblings like `job`, `search_jobs`, or `map_jobs`, so an agent must infer that this is the general listing endpoint.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: filters and pagination guidance ('use page and page_size to navigate large result sets') tell the agent how to shape a call, but there is no explicit when-to-use-this-vs-`job`/`search_jobs` and no stated exclusions. The auth prerequisite is the only hard precondition given.

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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