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airbyte_get_attempt_logs

Read-onlyIdempotent

Retrieve structured log entries for a specific job attempt, useful when debugging a failing attempt without fetching all attempts.

Instructions

Get logs for a specific attempt of a job.

Uses the internal Configuration API (POST /v1/attempt/get_for_job) to fetch structured log entries for exactly one attempt. More efficient than airbyte_get_job_logs when you know which attempt failed.

Always returns JSON — structured logs are best consumed as-is.

When to Use: - A job had multiple attempts and you want logs for a specific one (e.g. the failing attempt). - You already identified the failing attempt number from airbyte_get_job_details.

When NOT to Use: - If you want logs for all attempts, use airbyte_get_job_logs. - On Airbyte Cloud (internal API not available).

Returns: JSON with attempt metadata and structured log entries, truncated to the last tail_lines entries.

Examples: params = { "job_id": 12345, "attempt_number": 0 } params = { "job_id": 12345, "attempt_number": 2, "tail_lines": 500 }

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 cover safety (readOnlyHint, idempotentHint). Description adds useful behavioral details: uses internal API, returns JSON, truncates to tail_lines entries. No annotation contradiction.

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 sections, bullet points, and examples. Every sentence adds value; no wasted words. Front-loaded with purpose and endpoint info.

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, description covers all necessary aspects: purpose, usage conditions, parameter behavior, and example usage. Complete for a read-only log retrieval tool.

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 provides descriptions for all parameters, so baseline is 3. Description adds value with examples and explanation of tail_lines default and truncation behavior, raising score to 4.

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?

Clear verb 'Get' with specific resource 'logs for a specific attempt of a job'. Differentiates from sibling airbyte_get_job_logs by specifying efficiency and single-attempt focus.

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?

Explicitly states when to use (know which attempt failed) and when not (all attempts → airbyte_get_job_logs, not on Airbyte Cloud). Provides clear context for decision-making.

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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