tcai_capability_model

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

No annotations are provided, so the description carries the full burden. It states the tool queries or lists, but does not disclose behavioral traits such as idempotency, side effects, or any state requirements. For a read-like operation, minimal disclosure is insufficient.

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 two sentences, front-loaded with the tool's identity and followed by its two use cases. Every word serves a purpose; no redundancy or irrelevant detail.

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?

Given the tool's simplicity (1 optional parameter, no output schema), the description adequately covers its dual mode. However, it lacks details on return format or possible errors, leaving minor gaps. The high schema coverage offsets the need for extensive description.

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% for the single parameter 'action', which is described as 'Action label to query expected valence for'. The description adds value by implying that omitting the action parameter results in listing the capability table, a semantic nuance not captured in the schema.

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 the tool's purpose: 'Agency capability model... Query expected outcome of an action, or list the learned capability table.' It uses specific verbs ('query', 'list') and identifies the resource (expected-valence map), distinguishing it from sibling tools focused on sensors, simulation, or other tcai functions.

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 implies usage for obtaining expected valence for an action or listing the table, but it does not provide explicit guidance on when to use this tool versus alternatives like get_acm_score or other query tools. No when-not-to-use or contextual prerequisites are mentioned.

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