Get an Agentic AI Knowledge Unit

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

Annotations already mark this as readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds the key behavioral detail that a locale parameter changes the response from a full entry to a single-locale body, which informs the agent's expectations. It does not mention error cases, but the simplicity of the read operation makes this acceptable.

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 tight two sentences, front-loading the primary action and adding the essential workflow instruction. Every clause adds value, with no redundancy or filler.

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 simple single-retrieval tool with complete schema coverage, an output schema, and informative annotations, this description covers the purpose, usage, and behavioral nuance. The workflow relationship to search/list is included, making the tool self-contained for an agent to select 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?

The input schema already provides complete descriptions for both `slug` and `locale`, including an example and enum values, so the parameter semantics are fully covered. The description only reiterates the locale behavior without adding new usage details, matching the baseline for high schema coverage.

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 states 'Get one knowledge unit by slug' with a specific verb and resource, and clarifies the return behavior ('full entry' vs 'single-locale body'), distinguishing it from list-like siblings. The second sentence explicitly ties it to the search/list workflow, reinforcing its specific role.

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?

Explicitly directs the agent to use this tool after `search` or `list_knowledge` has provided a slug, establishing the prerequisite and workflow. This clearly differentiates when to invoke this tool versus its list/search counterparts, and implies not to use it for pattern/architecture retrieval.

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