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BachStudio Teradata MCP Server

dba_resusageSummary

Summarize Teradata system usage metrics by weekday and hour, filtering by workload type, complexity, user, or application ID.

Instructions

Get the Teradata system usage summary metrics by weekday and hour for each workload type and query complexity bucket.

Arguments: dimensions - list of dimensions to aggregate the resource usage summary. All dimensions are: ["LogDate", "hourOfDay", "dayOfWeek", "workloadType", "workloadComplexity", "UserName", "AppId"] user_name - user name date - Date to analyze, formatted as YYYY-MM-DD dayOfWeek - day of the week to analyze hourOfDay - hour of day to analyze workloadType - workload type to analyze, example: 'LOAD', 'ETL/ELT', 'EXPORT', 'QUERY', 'ADMIN', 'OTHER' workloadComplexity - workload complexity to analyze, example: 'Ingest & Prep', 'Answers', 'System/Procedural' AppId - Application ID to analyze, example: 'TPTLOAD%', 'TPTUPD%', 'FASTLOAD%', 'MULTLOAD%', 'EXECUTOR%', 'JDBC%'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dimensionsNo
user_nameNo
dateNo
dayOfWeekNo
hourOfDayNo
workloadTypeNo
workloadComplexityNo
AppIdNo
Behavior2/5

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

With no annotations, the description must disclose behavior. It states 'Get...summary metrics' but does not specify the actual metrics (e.g., CPU, IO), whether the operation is read-only, performance implications, or return format. The user is left uninformed about what data is returned or how aggregation works.

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 front-loaded with the purpose in one sentence, followed by a bullet list of arguments with examples. While the list is somewhat lengthy, it is well-structured and each parameter is explained concisely. No redundant sentences, but the purpose could be slightly tighter.

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?

Given 8 parameters, no output schema, and no annotations, the description is incomplete. It does not describe the output format, the effect of combining multiple parameters, or how to interpret the summary metrics. Essential context for an agent to generate correct queries is missing.

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?

Despite 0% schema coverage, the description adds significant meaning: list of possible values for 'dimensions', example values for workloadType, workloadComplexity, and AppId (including wildcard patterns). This helps an agent understand which parameters to use and with what values, going beyond the schema titles.

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 the tool retrieves 'Teradata system usage summary metrics' aggregated by 'weekday and hour for each workload type and query complexity bucket'. This distinguishes it from siblings like dba_featureUsage (features) and dba_flowControl (flow control) by specifying the exact resource and aggregation dimensions.

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?

No explicit guidance on when to use this tool versus alternatives. The description lists parameters that can be used to filter, but does not advise on scenarios (e.g., 'use for historical analysis') or exclude use cases. Sibling tools like dba_sessionInfo or dba_userDelay are not mentioned, leaving the agent to infer usage context.

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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