altair_reduce_dimensions_pca

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

No annotations are provided, so the description must fully disclose behavioral traits. While it mentions the variance threshold, it omits important details such as whether the tool is destructive (modifies original data), prerequisites (e.g., numeric data), performance implications, or edge cases (e.g., insufficient variance). 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 concise (two sentences) with no redundant information. It front-loads the core functionality. However, the second sentence about action number adds minimal value and could be integrated.

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 complexity (PCA with a parameter), no output schema, and no annotations, the description is incomplete. It fails to specify what the output is (e.g., reduced dataset), prerequisites (numeric data, no missing values), or limitations. This leaves the agent with insufficient information to correctly invoke and interpret results.

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 description coverage is 67% (2 of 3 parameters described). The description adds context by linking varianceThreshold to the target variance objective, but does not provide syntax or constraints beyond the schema. For a low-coverage schema, the description partially compensates but remains insufficient for all 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 verb 'reduce', the resource 'dimensionality', and the method 'PCA'. It specifies the behavior of keeping enough components to reach a target variance threshold, making the tool's purpose unambiguous and distinct from siblings like clustering or normalization.

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 does not explicitly state when to use PCA vs other dimensionality reduction methods or when not to use it. It mentions 'Covers action 43 (PCA)' but provides no guidance on alternatives or context. Usage is implied but not clearly delineated.

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