Read a lead's score

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

Annotations already cover readOnly/idempotent/non-destructive/openWorld=false, but the description adds material behavioral context beyond them: the model admits insufficient data by returning a null score and low confidence rather than fabricating a value, notes data sensitivity 'redacted', and lists required scopes. This exceeds what the structured fields convey.

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 core value proposition is front-loaded in the first sentence, and the operational block (endpoint, scopes, idempotency, workspace override) is compact. The 'Does not require idempotency' line is somewhat redundant with idempotentHint=true, a minor waste.

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?

An output schema exists, so return structure needn't be explained, and the description covers scopes, workspace overriding, and the null/low-confidence edge case. It is essentially complete for a single-lead read; only explicit alternative-tool guidance is missing.

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 67%; workspaceId and workspaceSlug are already documented in the schema, and the description only restates their override role. leadId is required but has no textual meaning in either place, so the description does not fully compensate for the gap. Baseline 3 is appropriate.

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?

States a specific verb+resource: a predictive booking-likelihood score (0-100) for one lead, derived from a trained bucket-rate model, plus its return components (confidence tier, top features). This is highly distinctive; no sibling analytics or leads tool returns a per-lead model score, so an agent can identify it immediately.

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?

It gives usage context for the workspace override ('Use workspaceId or workspaceSlug to override the default workspace configured by environment'), which is helpful. However, it never states when to use this tool versus adjacent options such as luca_leads_explain or the other analytics tools, leaving that to inference.

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