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by trustxai

airbyte_list_jobs

Read-onlyIdempotent

List sync, reset, refresh, and clear jobs with filtering by connection, status, type, date range, and workspace. Monitor job activity and failures across Airbyte pipelines.

Instructions

List sync, reset, refresh, and clear jobs with rich filtering.

Jobs represent individual executions. Every time a connection runs (manually or on schedule), Airbyte creates a job that tracks status, duration, bytes synced, and rows synced.

When to Use: - Check recent sync activity for a specific connection. - Find failed or running jobs across workspaces. - Audit sync volume (bytes/rows) over a date range. - Monitor whether scheduled syncs are executing on time. - Check the status of a refresh or clear job.

When NOT to Use: - If you already have a job ID, use airbyte_get_job for full details. - To see pipeline definitions (schedule, streams), use airbyte_get_connection instead. - If refresh/clear jobs are not returned (older Airbyte versions), use airbyte_list_jobs_internal instead.

Filters: All filters are optional and combinable: - connection_id: restrict to one pipeline. - workspace_ids: restrict to specific workspaces. - job_type: "sync", "reset", "refresh", or "clear". Note: "refresh" and "clear" require Airbyte >= 0.63. When omitted, most versions default to sync+reset only. - status: pending, running, incomplete, failed, succeeded, or cancelled. - created_at_start / created_at_end: ISO-8601 date range (e.g. "2024-01-01T00:00:00Z"). - order_by: sort field, e.g. "createdAt|DESC" (default).

Returns: Paginated list of jobs. Each entry includes: - jobId, jobType, status, connectionId, startTime, duration, bytesSynced, rowsSynced.

Markdown format shows a heading per job with bullet fields.
JSON format returns the raw API response array.

Pagination: Use limit (1–100, default 20) and offset (default 0).

Examples: Recent failed jobs for a connection: params = { "connection_id": "a1b2c3d4-...", "status": "failed", "limit": 5 } All sync jobs in the last 7 days: params = { "job_type": "sync", "created_at_start": "2024-06-01T00:00:00Z" } Refresh jobs for a connection: params = { "connection_id": "a1b2c3d4-...", "job_type": "refresh" } Latest 3 jobs, newest first: params = { "limit": 3, "order_by": "createdAt|DESC" }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already indicate read-only, idempotent behavior. The description adds operational details like job tracking, version constraints for job types, and pagination behavior, which are not covered by annotations.

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?

Well-organized with clear sections, front-loaded summary, and no wasted text. Every sentence serves a purpose, from usage guidance to examples.

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 tool's complexity (multiple filters, pagination, version dependencies, response formats), the description is remarkably complete, covering all key aspects without relying solely on the output schema.

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?

Although the input schema has parameter descriptions, the tool description adds richer context for each filter (e.g., job_type version notes, created_at_start format), and provides usage examples, significantly enhancing meaning beyond the 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 it lists sync, reset, refresh, and clear jobs with rich filtering, and distinguishes from siblings like airbyte_get_job and airbyte_list_jobs_internal.

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?

Provides explicit 'When to Use' and 'When NOT to Use' sections with concrete scenarios and references to alternative tools, plus details on filters and pagination.

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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