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Deraiven
by Deraiven

zadig_workflow_task_job_log

Retrieve a specific job log from a Zadig workflow task. Filter by keyword or tail lines to diagnose pipeline failures.

Instructions

Get one Zadig workflow task job log. Supports tail_lines and keyword filtering.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordNo
task_idYes
job_nameYes
tail_linesNo
include_rawNo
project_keyNo
workflow_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It only states that tail_lines and keyword filtering are supported; it does not describe how logs are returned, pagination/truncation behavior, raw-output semantics, or error/availability traits. This is a meaningful gap for a log-fetch tool.

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?

The description is a single front-loaded sentence with no wasted words: it states the action and resource first, then signals supported capabilities. It is concise and easy to parse, though slightly lean for the paramater set it supports.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With seven parameters and no annotations, the description offers too little context to fully equip an agent. It gives no usage scenario, no relationship among required parameters, and no explanation of optional fields; the output schema may cover return values, but the operational context is still thin.

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 description coverage is 0%, and the description only names tail_lines and keyword without explaining their effect beyond what their property titles already imply. It does not clarify the relationship between workflow_name, task_id, and job_name, or the role of optional fields like include_raw and project_key.

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 uses a specific verb and resource: it gets one Zadig workflow task job log, which clearly separates it from task list/detail and other workflow tools. Even without a title, the purpose is unambiguous.

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 intended use is implied by the noun phrase 'job log' — an agent can infer this is for retrieving logs rather than task summaries or lists. However, it does not explicitly contrast with siblings like zadig_workflow_task_list or zadig_workflow_task_detail, nor 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.