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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower; the description adds real value by disclosing the return content (full markdown teaching text) and an output-side obligation (required citation), which annotations do not convey.

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?

Two short sentences, zero waste, with the scope constraint ('ONE module') front-loaded before the exclusion clause.

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?

No output schema exists, so the description carries return-value burden and does so reasonably (markdown teaching text, citation required). Minor gaps remain: what the required citation looks like and error behavior for an unmatched slug.

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 0% for the single slug parameter, but the description conveys its semantic role by emphasizing 'ONE module' (identifying a single record) and implicitly ruling out bulk selection. It adds no format or slug-value guidance beyond the schema's pattern.

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 specific verb (Read) and resource (ONE module's full teaching text in markdown) and immediately scopes it against bulk usage. An agent can distinguish it from list_modules and search_teaching without opening any schema.

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 exclusion 'Not for bulk corpus assembly' implies bulk work belongs elsewhere, but no sibling (e.g., search_teaching, list_modules) is named as the alternative, so routing remains partly inferential.

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