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by markhilton

cja_validate_segment

Validate a segment definition for syntax and compatibility with a data view before creating or updating it.

Instructions

Validate a segment definition before creating or updating.

This tool checks if a segment definition is syntactically correct and compatible with the specified data view. Always use this before creating a new segment.

Args: definition: Segment definition to validate (required). dataview_id: Optional data view ID to validate against (uses configured default if not provided).

Returns: Dictionary with validation result and compatibility information.

Example queries: - "Validate this segment definition before I create it" - "Check if this filter definition is valid" - "Is this segment compatible with my data view?"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
definitionYes
dataview_idNo
Behavior3/5

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

The description discloses the tool checks syntax and compatibility, and returns a dictionary. However, with no annotations, it does not explicitly confirm it is read-only or describe error handling, which is a gap.

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 well-structured with Args, Returns, and Example queries. It is front-loaded with purpose. Minor redundancy like extra period after 'updating.' but overall concise.

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?

The description includes example queries and basic return info. But lacks output schema and detailed validation result format. For a validation tool, more specifics on success/failure indicators would improve completeness.

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?

Description adds meaning to both parameters: explains 'definition' is required segment definition and 'dataview_id' is optional with default. However, schema coverage is 0% and the nested 'definition' object is not described, limiting usefulness.

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 verb 'validate' and the resource 'segment definition'. It distinguishes this tool from siblings like 'cja_validate_calculated_metric' and 'cja_create_segment' by specifying it validates before creating or updating.

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 description explicitly says 'Always use this before creating a new segment' and mentions validation for updates. It provides clear context but lacks explicit when-not-to-use or alternatives.

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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