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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context beyond this by including an 'ANTI-FABRICATION' note that the text is sourced from docs/reliability-theory.md and that the β-as-failure-mode interpretation is a practitioner framing to quote verbatim. This is useful sourcing and presentation guidance not present in the annotations.

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 a single dense paragraph that efficiently combines purpose, content details, usage triggers, and sourcing constraints. Every sentence earns its place, but the text could be improved with structured formatting (e.g., bullets) for easier scannability.

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?

For a 0-parameter informational tool with no output schema and robust annotations, the description is complete: it fully specifies the content scope ('textbook-tier distribution zoology', β table, alternative distributions, heuristics), provides explicit usage triggers, and includes important sourcing-specific instructions. An agent has everything needed to correctly select and invoke the 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?

The tool has zero parameters and an empty input schema. The description explicitly reinforces this with 'No inputs.' Since there are no parameters to document, the baseline of 4 applies per the rubric.

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 states the tool's action with a specific verb and resource: 'Return a textbook-tier distribution zoology for reliability work' and enumerates the exact topics (Weibull β table, alternative distributions, heuristics). It also provides explicit example user queries ('which distribution should I fit', 'what does Weibull β mean', 'when to use Lognormal') that distinguish it from sibling tools like explain_reliability_basics and interpret_weibull_shape.

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 clear usage context with the direct statement 'Use when a user asks...' and lists three concrete query examples. However, it does not explicitly state when not to use this tool or directly name alternative sibling tools, falling just short of the highest level of guidance.

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