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suniljavadi

Data Engineering MCP Server

by suniljavadi

analyze_job_failure

Prepare deterministic evidence for a failed ETL run using job name and run ID to identify root causes.

Instructions

Prepare deterministic evidence for a failed ETL run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
run_idYes
job_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries full behavioral burden. It hints at determinism but does not disclose whether the tool is read-only, whether it executes anything, what side effects it has, or how 'evidence' is produced.

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?

A single, front-loaded sentence with no wasted words. It is concise and readable, though 'deterministic evidence' is somewhat jargon-heavy and could be clarified without losing brevity.

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

Completeness3/5

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

With an output schema present, return values are likely covered. However, the absence of usage guidance, behavioral details, and parameter explanation leaves meaningful gaps for an agent trying to decide when and how to invoke this tool correctly.

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 does not explain job_name or run_id. It adds only the context that the run is a failed ETL run, which helps interpret run_id, but leaves parameter formats and semantics mostly to inference from the property titles.

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?

The description states a specific action ('Prepare deterministic evidence') and a clear resource ('a failed ETL run'). It differentiates from siblings like get_job_status and get_job_logs by focusing on failure evidence, though it could be more explicit about what 'evidence' includes.

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

Usage Guidelines2/5

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

The phrase 'for a failed ETL run' implies a context, but the description gives no guidance on when to choose this over get_job_logs, get_job_status, or get_job_history. No alternatives or exclusions are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.