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

With no annotations provided, the description carries the full burden. It discloses the interpretive bias (Raëlian-canon-centred), what it returns (framework reading), and its behavior for arbitrary topics (closest wiki entry). It also states what it does not do (source-grounded data). This is strong transparency for a non-mutating lookup tool.

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?

Three sentences, each with a distinct purpose: core purpose, accepted inputs/behavior, and alternative tools. The description is front-loaded with the main action and maintains high information density without fluff.

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 a single parameter and no output schema, the description provides sufficient context for selection and use. It explains the interpretive nature, the input domain, and when to choose sibling tools. No critical information is missing for an agent to decide correctly.

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?

Although the schema has 100% coverage of the only parameter 'topic', the schema description is minimal. The tool description enriches semantics by enumerating specific framework topics (overview, hypothesis, terminology, timeline, sources, method) and explaining the fallback behavior for any other term. This goes beyond the schema's basic 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 states the tool's verb ('Return'), resource ('Wheel of Heaven interpretive framework's reading'), and scope ('of a topic'). It explicitly distinguishes from mainstream consensus and distinguishes itself from sibling tools like get_passage and compare_traditions, which provide fact-layer data.

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?

It provides explicit when-to-use guidance: use for the framework's interpretive reading. It also gives an explicit alternative: 'Use fact-layer tools (get_passage, compare_traditions) for source-grounded data without this framing.' This clearly differentiates from the listed siblings.

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