Get one Physical AI platform, deployment, guide or reference

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

Annotations already cover safety (readOnly, idempotent, non-destructive, openWorld), yet the description adds genuinely non-obvious behaviour: unpublished specs or KPIs come back as null with status 'unpublished' and must be reported as unknown rather than estimated. That is an interpretation rule the agent could not infer from schema or annotations, and it directly prevents fabrication.

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, front-loaded with the verb+resource, then the handling rule. The long parenthetical enumerating per-type contents is dense but each item distinguishes record kinds; a bulleted structure would read more easily, but nothing is 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?

An output schema exists so return shape need not be described, yet the description still conveys enough about each record type and the unpublished-value convention for an agent to call the tool and report results correctly. Three params, one required, one enum — nothing essential is missing.

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 parameters are already documented, but the description still adds value by tying `type` to differing payload shapes and by clarifying that `slug` is optional only for taxonomy/methodology. It does not add anything about `locale`, which the schema already handles with a stated default.

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 opening clause 'Read one record by type and slug' states a specific verb and resource, and the sentence then enumerates exactly which record kinds exist (platform sheet, case study, guide, source, taxonomy/methodology) with what each contains. It is clearly the single-record counterpart to the list/search siblings in the toolset.

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?

'Use this after search_physical_ai, with the type and slug it returned' gives an explicit prerequisite and the exact inputs to carry over, and it names the alternative (search) it follows. It also states the one exception to slug requirements (taxonomy and methodology need none), so the agent knows both the normal path and the edge case.

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