conformal

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

The description says 'Kwargs pass through to the target function,' implying that additional/unlisted arguments are accepted, while the annotations set openWorldHint=false, indicating a closed-world parameter set. This is a direct contradiction, so the description fails behavioral transparency despite providing useful failure-mode context.

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 opening sentence is strong and front-loaded, and the enumerations are valuable. However, the final failure-mode passage is a long run-on that ends with '...' without completing the miscalibrated-nuisance sentence, making the structure feel unfinished rather than intentionally concise.

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?

Given the tool's complexity, the description covers assumptions, preconditions, and failure modes, and the schema-plus-output-schema combination covers parameters and return structure. It is nearly complete, but it relies on an external guide for kwargs and leaves the failure-mode list truncated, preventing a 5.

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%, so the baseline is 3. The description adds meaningful semantics beyond the schema for the central parameter `kind`, listing estimator families and linking assumptions/failure modes to specific choices. Other parameters like `detail` and `as_handle` are already well documented in the schema, so no further description is needed.

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 states a specific role ('Unified conformal causal inference dispatcher') and enumerates the estimator kinds it can select, so an agent can tell what the tool computes. It does not explicitly differentiate itself from sibling tools such as conformal_ite, conformal_fair_ite, or conformal_synth beyond the word 'unified.'

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 gives explicit when-to-use guidance for estimator variants: e.g., covariate shift should use kind='weighted' with estimated density ratios, and small calibration sets should be addressed by increasing calibration sample or alpha. It does not discuss when to use this dispatcher versus the conformal-specific sibling tools, but it covers the internal kind-selection decision well.

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