get_method_guide

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. It describes what the tool returns (a detailed guide) but doesn't cover critical aspects like whether it's a read-only operation, if it requires authentication, rate limits, error handling, or the format of the output (e.g., text, structured data). For a tool with no annotation coverage, this is a significant 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?

The description is a single, efficient sentence in Korean that front-loads the core purpose. It wastes no words, though it could be slightly more structured by explicitly stating it's a retrieval tool. Every part of the sentence contributes to understanding the tool's function.

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 moderate complexity (2 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the purpose and parameters indirectly, but lacks details on output format, behavioral traits, and usage context. Without annotations or an output schema, the agent is left guessing about the return value and operational constraints.

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 input schema has 100% description coverage, with clear parameter descriptions and an enum for 'aspect'. The description adds minimal value beyond the schema by listing the aspects (assumptions, procedure, interpretation, reporting) in Korean, which aligns with the enum but doesn't provide additional semantics like examples of method names beyond the schema's examples. Baseline 3 is appropriate when the schema does the heavy lifting.

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: to retrieve a detailed guide for a specific statistical method, covering aspects like assumptions, procedure, interpretation, and reporting. It uses specific verbs ('get', 'retrieve' implied) and resources ('statistical method guide'), but doesn't explicitly differentiate from siblings like 'bayesian_guide', 'causal_design_guide', or 'sem_guide', which appear to be more specialized guides.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'compare_methods' for method selection, 'check_assumptions' for assumption validation, or 'suggest_method' for recommendations, leaving the agent with no context for choosing among them.

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