spss_missing_values

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

With no annotations, the description carries the full transparency burden. It does disclose the core behavior: it issues MISSING VALUES, and an empty string clears missing values with NONE, plus the SPSS dependency. It does not state whether the original file is overwritten or what output_path controls, which matters for a mutating operation.

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 compact and front-loaded: it states the command, the parameter shape, concrete examples, the clearing behavior, and the external dependency in four short sentences 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 tool with a nested required parameter and an output schema present, the description covers the syntax and semantics needed to construct a valid missing_spec. The only notable omission is output_path semantics—whether the result is written to a new file or the input is modified—which prevents a perfect score.

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 0%, but the description richly defines the hardest parameter, missing_spec: it gives the object shape, valid syntax, and examples including the empty-string clearing case. It leaves file_path and output_path unexplained, but these are relatively conventional and the required complex parameter is fully covered.

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 names the exact SPSS operation ('MISSING VALUES') and the resource it acts on ('var (spec)'), and explains it as declaring user-missing values. It is clearly separable from siblings like spss_value_labels or spss_recode because it is framed around missing-value declarations.

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 intended use case is implied by the command and examples ('age': '99', 'LOWEST THRU 0; 99'), and the note about clearing with an empty string adds context. However, there is no explicit statement of when to choose this over alternative SPSS tools or any exclusions, so the guidance is implied rather than explicit.

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