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

Annotations already cover read-only and non-destructive behavior. The description adds useful behavioral context: this returns a fixed set of 13 authored pages, not arbitrary content, and describes the structured composition of each answer. This goes beyond the annotations without contradicting them.

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 sentences with no filler, front-loaded with the core behavior and followed by concrete enumerations. The slug list is useful and compact.

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?

With a single simple parameter, annotations, and an output schema, the description covers the essential calling context. The only minor gap is that not all 13 known slugs are enumerated, but the query-map reference and examples are sufficient for safe usage.

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 100%, so the baseline is 3. The description adds beyond the schema by enumerating known slug examples, which helps the agent recognize valid inputs even though no enum is provided. This is meaningful extra value for the slug parameter.

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 uses a precise verb ('Returns') and names the exact resource ('one authored /answers page') plus the content structure (question, short answer, problem frame, citations). This clearly distinguishes it from sibling tools like search_library or get_wage_jurisdiction.

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 implies usage through the list of known slugs and the single required 'slug' parameter, so the intended context is inferable. However, it does not explicitly name alternatives or state when not to use this tool, leaving selection guidance largely implicit.

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