cloglog

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

Annotations already declare readOnlyHint=true, and the description adds little beyond that: 'via maximum likelihood' names the fitting method but not what the call returns, caches, or how it handles failures. 'Validation: certified parity evidence' is too vague to inform agent behavior and reads as a quality claim rather than an operational disclosure.

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 main purpose sentence is short and front-loaded, which is good. However, the second sentence is cryptic and uninformative, so not every sentence earns its place; a 17-parameter tool needs a bit more orientation than this.

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 rich input schema and output schema cover invocation mechanics, and the read-only annotation covers safety. But the description omits any guidance on required inputs (data_path plus formula/x/y are not marked required) and on how this model relates to the many regression siblings, so it is only minimally complete.

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%, so the parameter descriptions already carry the semantic load, making 3 the baseline. The tool description itself says nothing about parameters and does not compensate with guidance such as 'supply either formula or x/y plus data_path'.

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 first sentence names a specific estimator ('Complementary log-log regression') and estimation principle ('via maximum likelihood'), so an agent can distinguish it from logit/probit at a glance. It stops short of 5 because it never explicitly contrasts itself with similarly named siblings such as clogit, and the 'Validation: certified parity evidence' sentence is not purpose-related.

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?

There is no statement of when to choose cloglog over logit, probit, clogit, or glm, and no exclusions or prerequisites are given. The only hint about usage is the 'detail' parameter's guidance about sub-step calls, which concerns output size, not tool selection.

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