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cf_list_logpush_jobs

List configured Logpush jobs for a zone or account to review job status, dataset, and configuration details.

Instructions

List configured Logpush jobs at a given scope.

Args:
    scope: 'zone' or 'account'.
    scope_id: Cloudflare zone ID or account ID matching the scope.

Calls: GET /{zones|accounts}/{scope_id}/logpush/jobs.

Returns: envelope with `data = {jobs: [...], count: N, scope, scope_id}`.
Each job carries: id, dataset, destination_conf (redacted of secrets by
Cloudflare), enabled, frequency, last_complete, last_error, error_message.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeYes
scope_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It reveals that the tool uses a GET request (safe, non-destructive), specifies that destination_conf is redacted of secrets by Cloudflare, and details the response envelope structure. This conveys essential behavioral traits without contradictions.

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?

The description is highly concise with a clear structure: purpose sentence, args list, API call format, and return envelope with job fields. Every sentence adds value, and there is no extraneous text.

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 the moderate tool complexity (two parameters, list operation), the description fully covers purpose, parameter semantics, API endpoint, and response structure. The presence of an output schema (though not provided in the input) is supplemented by a detailed return description, making it complete for an agent to invoke correctly.

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

Parameters5/5

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

The input schema has 0% description coverage (no parameter descriptions), but the description compensates fully by defining each parameter. It explains that scope must be 'zone' or 'account' and that scope_id is the corresponding Cloudflare ID, adding critical semantics beyond the raw 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 starts with 'List configured Logpush jobs at a given scope,' which clearly states the action (list) and the resource (Logpush jobs). It distinguishes itself from sibling tools like cf_get_logpush_job, which retrieves a single job, by emphasizing the listing aspect.

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?

The description defines the required parameters (scope and scope_id) and their meanings, aiding correct usage. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., cf_get_logpush_job), and does not mention when not to use it.

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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