bubble_record_validator

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=true, establishing a safe read-only operation. The description adds behavioral detail about sampling and the specific checks performed (empty/null fields, fully empty records), which is valuable context beyond the annotation values.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that conveys the core purpose and method with no filler words. Every part contributes to understanding the tool.

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

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

The tool is simple (2 params, no output schema), but annotations provide safety context. The description covers the function adequately. However, it doesn't mention what the tool returns or how results are reported, which could be useful given the lack of an output schema.

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

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

Schema description coverage is 100%: both dataType and sample_size have meaningful descriptions. The tool description reinforces their semantic roles ('given data type', 'sampling') but doesn't add significant new meaning beyond what the schema already provides.

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

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

The description uses a specific verb 'validates' with a clear resource 'records of a given Bubble data type' and describes the method 'by sampling and checking for empty or null fields and fully empty records.' This distinguishes it from sibling tools like bubble_tdd_validate or bubble_health_check.

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

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

The description provides no explicit guidance on when to use this tool versus alternatives. It doesn't mention typical use cases, prerequisites, or mention sibling tools. The context is implied but not stated.

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