qte

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

Beyond the readOnlyHint annotation, the description discloses estimand assumptions, failure modes (large IPW weights, quantile crossing), and validation ('certified parity evidence'). The mention of 'method='ipw'' conflicts with the schema enum, but since it does not contradict the annotations, annotation_contradiction remains false.

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 dense but front-loaded with the core 'Quantile treatment effects' concept, then covers methods, assumptions, pre-conditions, failure modes, alternatives, and sample size. Almost every sentence carries information, though the 'Validation: certified parity evidence' clause is vague and the lack of structured formatting makes parsing harder.

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?

Since an output schema exists, the description need not explain return values. It thoroughly covers assumptions, prerequisites, failure modes, alternative tools, and a minimum-N guideline. The main gaps are the ambiguous validation statement and the inconsistent ipw reference, which slightly reduce completeness for a complex 13-parameter tool.

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 baseline is 3. The description adds meaningful semantics for the method parameter by explaining each of the four estimands, but it also references 'method='ipw'' and 'sp.trimming' which are not in the schema enum, muddying parameter mapping. The quantiles parameter is left with only a tautological schema description.

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 clearly identifies the tool as estimating quantile treatment effects and distinguishes the four internal methods ('firpo_qte', 'firpo_qtt', 'conditional_qr', 'distribution') by their estimands and assumptions. It lists alternative tools (sp.qdid, sp.rifreg, sp.cic, sp.metalearner) but does not explicitly differentiate them, preventing a top score.

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 pre-conditions (binary treatment, continuous outcome, controls covering confounders) and per-method assumptions, which implicitly tell an agent when the tool is appropriate. However, the Alternatives line names sibling tools without criteria for choosing them instead of qte, so routing decisions are left to inference.

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