generate_review_template_boj

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 discloses that the tool analyzes code and problem text, may require platform clarification, and includes specific output components. However, it does not explain how it obtains the user's code, side effects, failure modes, or whether it fetches external data, leaving behavioral ambiguity.

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 core purpose and followed by a necessary warning. Every sentence adds value; no redundant content or excessive 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?

For a generation tool with no output schema, the description provides a solid overview of expected outputs (markdown template, analysis, related problems, prompt) and critical platform guidance. It lacks details on prerequisites like whether code submission is required, but is otherwise sufficiently complete for the tool's complexity.

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%, so the baseline is 3. The description adds meaningful context beyond the schema by warning about platform ambiguity for problem_id and clarifying that user_notes is an optional memo. This helps the agent understand the practical implications of the parameters.

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 analyzes the user's submitted code and problem text to generate a personalized review guide for BOJ problems. It includes a specific verb ('제공합니다'), target resource ('백준(BOJ) 문제'), and output components, distinguishing it from platform-specific siblings like generate_review_template_programmers.

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?

Provides explicit platform-disambiguation guidance: if only a problem number is given, determine the platform from context or ask the user whether it is BOJ or Programmers. This helps the agent select the correct platform-specific tool, but it does not explicitly contrast with other BOJ tools like analyze_code_submission_boj or generate_hint_boj.

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