Get an Agentic AI Knowledge Unit

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds value beyond those annotations by disclosing the locale-dependent return behavior: full entry vs. single-locale body. No contradiction with 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?

Two sentences, zero filler. The first sentence front-loads the core purpose and locale behavior; the second delivers actionable usage timing. Every word earns its place.

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 low-complexity, read-only tool with an output schema, annotations, and fully documented parameters, the description covers purpose, behavior, and usage timing. A minor gap is not explicitly routing to alternative get_* sibling tools, but the 'knowledge unit' resource scope makes that differentiation implicit.

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 the schema already documents both parameters. The description adds genuine meaning by explaining the behavioral consequence of locale ('full entry, or a single-locale body'), which goes beyond the schema's 'Language of the returned body' phrasing.

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 specific verb+resource structure: 'Get one knowledge unit by slug.' It clearly distinguishes from sibling list/search tools by emphasizing single-item retrieval by slug, and the phrase 'Use this once search or list_knowledge has given you a slug' positions it precisely against its discovery-oriented siblings.

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 an explicit precondition for use: after `search` or `list_knowledge` yields a slug. This is clear context that prevents an agent from calling it prematurely. It does not explicitly enumerate exclusions (e.g., that get_pattern/get_article are for other resource types), but the knowledge-unit scope makes those alternatives obvious.

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