bubble_wu_estimate

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond that by stating that search estimates scale by dataset size and that expensive patterns are flagged. It does not describe return format or exact output, but for a computed estimate tool, this is reasonable given the annotation coverage.

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?

Two short sentences, with the primary purpose in the first sentence and a beneficial behavior in the second. Every word earns its place, with no redundancy or unnecessary detail.

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?

For a tool with only 3 parameters and no output schema, the description covers the core function well but omits what the estimate looks like (return format, units, etc.) and lacks explicit usage guidance. The scaling/flagging note adds some operational context, but the absence of output details and alternatives leaves modest completeness gaps.

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 coverage is 100%: all three parameters (dataType, operation, constraints) have meaningful descriptions. The description itself does not add parameter-specific details beyond what the schema provides, so it remains at the baseline for full schema coverage.

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 starts with a specific verb 'Estimates' and clearly identifies the resource ('Workload Units (WU) for a Bubble.io operation'). The additional detail about scaling and flagging expensive patterns further distinguishes this tool from all siblings, none of which estimate WU, making the purpose unambiguous.

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?

Usage is implied: this is the tool for estimating WU for a Bubble.io operation. However, there is no explicit statement of when to use it versus alternatives, nor any exclusion criteria. The mention of scaling by dataset size and flagging expensive patterns gives context but does not directly guide tool selection.

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