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cdp_list_column_validators

Retrieve column validation rules for a CDP tenant to ensure data quality and compliance in customer data management.

Instructions

List column validators for a tenant

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tenant_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states a read operation ('List'), implying it's non-destructive, but doesn't disclose behavioral traits like pagination, rate limits, authentication requirements, or error conditions. For a listing tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves in practice.

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 a single, efficient sentence with zero waste. It's front-loaded with the core action ('List column validators'), making it easy to scan. No extraneous information or redundancy is present, which is ideal for conciseness.

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?

Given the tool's low complexity (one optional parameter) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and 0% schema coverage, it should do more to explain the parameter's role and usage context. It's complete enough for basic understanding but lacks depth for reliable agent invocation.

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?

The description mentions 'for a tenant', which aligns with the 'tenant_id' parameter in the schema. However, schema description coverage is 0%, and the description doesn't add meaning beyond the parameter name—it doesn't explain what 'tenant' means, whether the ID is optional (it has a default of null), or what happens if omitted. With one parameter and low schema coverage, the description provides minimal compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'List column validators for a tenant' clearly states the verb ('List') and resource ('column validators'), but it's vague about scope and format. It doesn't specify whether this lists all validators globally or filtered ones, or what information is returned. Compared to siblings like 'cdp_get_column_validator' (singular retrieval), it distinguishes as a listing operation, but lacks specificity about the listing's nature.

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 description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication), when to prefer this over other listing tools (like 'cdp_list_audience_defs'), or any constraints. The agent must infer usage from the name alone, which is insufficient for effective tool selection.

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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