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pmankineni

mcp-sac-tools

by pmankineni

sac_validate_import

Validate staged data in an import job and review rejected rows to ensure data quality before finalizing the import.

Instructions

Validate the staged data in an import job. Returns validation result including any rejected rows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYesThe job ID
modelIdYesThe model/provider ID
dataTypeNo
dimensionNameNo
Behavior3/5

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

With no annotations provided, the description partially discloses behavior: it returns validation results including rejected rows. However, it does not state whether the tool is read-only or has side effects, which is a gap given the lack of annotations.

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 two sentences, concise, and front-loaded with the core purpose. No unnecessary words.

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?

The description covers the main purpose and return value. It lacks explicit mention that the tool does not modify data (important for a validation tool), but given the straightforward nature, it is mostly complete.

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 50%, with jobId and modelId documented but dataType and dimensionName lacking descriptions. The tool description does not add any parameter-level detail beyond what is in the schema.

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 action 'validate' and the resource 'staged data in an import job', and specifies the return value includes validation result and rejected rows. It distinguishes from sibling tools like sac_run_import and sac_import_status.

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 description implies the tool is used after staging data, but does not explicitly state when to use it versus alternatives, nor does it provide when-not-to-use guidance or prerequisites.

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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