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

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose an important behavior: it never sends raw unredacted private transcripts, and it clarifies that input must be structured. It does not describe side effects, persistence, or lifecycle consequences, but the privacy-oriented behavioral constraint adds meaningful transparency beyond the bare function.

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 extremely concise: a clear opening purpose sentence, a brief statement of accepted content, and a focused privacy constraint. Every sentence carries distinct information without filler or repetition, and the most important purpose is front-loaded.

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 tool with three required parameters and an open-ended nested event_data object, the description provides just enough context to make a reasonable invocation: use experience_id from an ongoing episode, provide an event_type, and include structured actions or observations. The output schema presumably covers return values, but the description lacks examples or a controlled vocabulary for event_type, which leaves some ambiguity for correct use.

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%, and the schema only provides parameter names and types. The description compensates partially by mapping event_data to 'structured actions, observations, and state changes' and by tying experience_id to an ongoing episode. It leaves event_type values and the exact structure of event_data unspecified, so an agent still has to infer some semantics from the tool name and context.

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 and object: 'Record an observable event in an ongoing experience episode.' This clearly separates it from sibling tools like start_experience, submit_outcome, and report_transfer, and the 'ongoing' qualifier reinforces that it is not for initiating an episode. It also adds what the event consists of: structured actions, observations, and state changes.

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 useful context for when to use it: during an ongoing experience episode and for structured events rather than raw transcripts. However, it does not explicitly mention alternative tools or state when not to use it, such as when starting an episode or submitting a final outcome. The usage guidance is implied rather than explicit.

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