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

With no annotations, the description carries the full burden and does so well: it discloses that MONARK does not see, store, or verify caller data or models, does not validate that inputs are genuine nonconformity scores, and that results are not a probability of being right. These are non-obvious behavioral and trust properties that cannot be inferred from the schema.

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?

Four sentences, each load-bearing: the computation, the privacy/statelessness stance, the exchangeability precondition, and the misinterpretation warning. The guarantee-critical constraint is front-loaded and there is no filler.

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 values need no explanation, and the schema already documents the fail-closed nMin behavior. Combined with the description's coverage conditions and privacy disclosures, an agent has everything needed to call and correctly interpret this 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 nMin, alpha, and scores are already fully documented in the schema (including the fail-closed under_calib behavior). The description adds only the 'BYO / caller owns the score function' framing, which is context rather than new parameter semantics, so baseline 3 applies.

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 precise verb+resource: computes the split-conformal quantile at miscoverage alpha over caller-supplied nonconformity scores. That is unambiguous and an agent can tell it is a calibration/quantile computation, but the description never contrasts it with the sibling tools (attest, cascade, gate), so sibling differentiation is absent.

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?

Gives a clear applicability condition and an explicit exclusion: marginal 1-alpha coverage holds only for future points exchangeable with the supplied scores, and non-exchangeable data (distribution-shifted or time-ordered) voids it. It does not, however, say when to prefer this tool over the sibling tools, so full routing guidance is missing.

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