predict_semantic_closure

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

No annotations are provided, so the description carries the full burden of behavioral disclosure, and it discloses nothing. It does not state what a 'semantic closure' prediction returns, whether it is a classification or score, latency implications, or any side effects.

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 only three words, but this is under-specification rather than conciseness. It is front-loaded only in the trivial sense that there is nothing else to say.

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 an undocumented required parameter, no annotations, and no output schema, the description is completely inadequate. An agent cannot determine what the tool returns or when to invoke it.

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 description coverage is 0% and the sole required parameter, transcript_fragment, is never mentioned in the description. The parameter name is somewhat self-evident as a string input, but the description adds zero meaning about expected content, length, or format.

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 is a verbatim restatement of the tool name, 'predict semantic closure', with no added explanation of what 'semantic closure' means or what is actually predicted. It gives no way to distinguish this tool from siblings like analyze_turn_status or run_benchmark_turn_detection.

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?

There is no guidance on when to use this tool versus the sibling analysis/benchmark tools, nor any stated preconditions. The description provides no context that would route an agent here rather than to analyze_turn_status.

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