select_reasoning_protocol

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

With no annotations, the description carries the full burden of disclosing behavioral traits. It only states the tool is 'model-agnostic' but does not explain what that means for behavior, how selection is made (e.g., based on prompt content or complexity), whether it modifies anything, or any side effects. The description is too sparse to provide meaningful behavioral transparency.

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 concise, consisting of a single sentence with a clear list of options. It front-loads the core purpose. However, it could be restructured to include more essential details without losing conciseness, such as the role of the 'complexity' parameter.

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 task complexity (selecting from multiple reasoning protocols) and the existence of an output schema (not detailed here), the description is incomplete. It does not explain how the selection works, what the output looks like, or how parameters influence the result. An agent would lack sufficient context to use the tool effectively.

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%, so the description must compensate for parameter information. It fails to explain the 'complexity' parameter at all, even though it has a default value and likely influences the selection. The description only mentions 'prompt' implicitly but does not elaborate on its role. No value is added beyond the raw 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 identifies the action ('Select') and the resource ('a model-agnostic reasoning protocol stack for a prompt'), and it lists the specific protocol options, making the tool's purpose unambiguous. It distinguishes itself from sibling tools which are primarily analytical, decision-making, or memory-related, not protocol selection.

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 is provided on when to use this tool versus alternative reasoning or planning tools from the sibling list. The description does not specify context, prerequisites, or when to avoid using this tool. For example, it does not differentiate between when to use 'direct' vs 'ReAct' or how to choose among them.

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