get_logic_analysis_scaffold

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

With no annotations, the description carries full burden and describes the tool as 'read-only', implying no side effects. It lists what the scaffold provides but does not detail behavior like rate limits or dependencies. However, it is sufficiently transparent about its purpose and limitations.

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: two sentences, no superfluous words. The main purpose is front-loaded, and every sentence adds value.

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 zero parameters and a provided output schema, the description covers the essential aspects: what the tool returns and what it does not do. It could mention that the scaffold aids in generating reasoning steps, but overall it is complete enough for an AI agent.

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?

The tool has no parameters, so the description trivially adds value beyond schema. Schema description coverage is 100% since no parameters exist, and baseline is 4-5.

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 returns a read-only method scaffold for logic analysis reasoning, listing specific components like problem-type routing and structure templates. It explicitly distinguishes itself by stating what it does not do (solve or select answers), and the purpose aligns with its sibling scaffold tools.

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 when needing the scaffold for logic analysis reasoning, and clarifies its limitations by stating it does not solve questions or select answers. Although it doesn't explicitly mention when not to use or alternatives, the context is clear enough for an AI agent.

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