get_high_severity_smells

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

With no annotations, the description carries the full burden. It discloses one behavioral trait: if commitHash is absent, the latest result is used. This is valuable but does not cover other aspects such as read-only nature, authentication requirements, or output format.

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 that directly state the purpose and the key behavioral note. No wasted words, and the main action is front-loaded.

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 presence of multiple sibling tools (e.g., get_smells_by_file, get_pyexamine_result_by_commit), the description does not clarify when to use this tool versus those. The lack of an output schema and annotations further increases the burden, but the description only covers the basic retrieval behavior and one fallback rule.

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 schema already provides descriptions for all parameters (100% coverage). The description adds meaning by explaining the commitHash fallback behavior, which goes beyond the schema's simple 'commit hash 필터'. This enhancement justifies a score above the baseline of 3.

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 retrieves a list of high severity smells, using the verb '조회한다' (retrieve) and the resource 'high severity smell 목록' (high severity smell list). The mention of commitHash fallback adds specificity. However, it does not explicitly differentiate from siblings like get_smells_by_file or get_code_analysis_results.

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 for retrieving high severity smells, and the note about commitHash absence using the latest result gives some contextual guidance. However, there is no explicit mention of when to prefer this tool over alternatives, nor any exclusions.

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