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teradata-gcfr-mcp-server

by Pibbers

gcfr_error_log

Retrieve raw error log entries to investigate root causes, including calling API and step where errors occurred. Filter by date range or process name for targeted troubleshooting.

Instructions

Show raw error log entries for root cause investigation.

Includes the calling API and step where the error occurred. Sql_Text (CLOB) is excluded from output — ask separately if needed. date_from and date_to default to yesterday and today respectively. Optionally filter by process_name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
date_toNo
date_fromNo
process_nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently discloses that Sql_Text is excluded, what fields are included, and the default date range. It lacks details on pagination, ordering, or potential size of results, but for a read-only log retrieval tool the disclosed behavior is adequate.

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 four sentences with no filler. The main action is front-loaded, and each subsequent sentence adds a distinct piece of valuable information: included fields, excluded field, defaults, and filter option.

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

Completeness4/5

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

For a simple tool with three optional parameters and an output schema, the description covers the core purpose, key fields, a notable exclusion, and parameter behavior. It does not mention date formats or output ordering, but these are minor gaps given the output schema exists and the tool is straightforward.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate. It adds useful meaning: date_from/date_to default to yesterday/today and process_name is an optional filter. However, it does not specify the expected date format, whether the range is inclusive, or how process_name matching works.

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 clearly states the tool's function: 'Show raw error log entries for root cause investigation.' This identifies a specific verb and resource. However, it does not explicitly differentiate this tool from siblings like gcfr_execution_log, which could plausibly overlap in purpose.

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

Usage Guidelines4/5

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

The phrase 'for root cause investigation' provides a clear usage context. It also explains defaults and the optional filter (process_name). It does not, however, provide explicit exclusions or when to prefer a sibling tool over this one.

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