save_smell_analysis

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

With no annotations, the description does disclose meaningful behavior: the backend workflow via /analyze, persistence of findings, and the constraint that projectPath must be a container-side path. However, it omits side-effect details such as whether results are overwritten, idempotency, authentication, or response/return behavior.

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 three tightly written sentences: purpose, backend mechanism, and a key parameter warning. Every sentence contributes useful information with no filler.

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 10-parameter tool with no output schema and no annotations, the description gives a useful high-level flow but leaves out what the tool returns after saving, how to link results to subsequent getters, and any prerequisites. It is adequate but has clear gaps.

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 90%, so the schema already documents most parameters. The description only reinforces the projectPath container-path guidance, which duplicates the schema's own parameter description, adding no new semantic value beyond it.

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 a specific action: request smell analysis execution from the CodeVi backend and save results. It also adds distinctive detail by mentioning the backend calls advanced-pyexamine-service /analyze and stores findings, which separates it from pure getter or metric-analysis 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?

No guidance is given on when to use this tool versus siblings like analyze_python_smells or run_metric_analysis. The description only mentions a projectPath requirement, not decision criteria or exclusions.

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