tcai_second_order

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

The term 'snapshot' implies read-only behavior, but the description does not explicitly state that it is non-destructive or lacks side effects. Without annotations, this is a mild gap.

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 efficiently convey the tool's purpose. The first sentence lists key metrics, the second adds context. Could be slightly tighter but overall concise.

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?

The description lists the metrics covered but does not specify the output format (e.g., whether they are returned as separate fields). Lacking output schema, more detail on the response structure would improve completeness.

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?

No parameters exist, so parameter semantics are not applicable. The high schema coverage (100%) means the description does not need to add parameter details.

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 clearly states it is a 'snapshot' of second-order loop metrics, listing components like meta-learning velocity and RND curiosity. It conveys a distinct purpose as a composite metric, but does not explicitly differentiate from sibling tools that return individual metrics.

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?

No guidance on when to use this tool versus alternatives like tcai_curiosity or tcai_meta_learning. The description lacks context for tool selection.

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