arf_pca_preprocessed

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

Annotations already declare readOnlyHint=true, and nothing in the description contradicts that (it is a computation over an existing matrix). Beyond annotations it adds real behavioral context: preprocessing is not repeated on re-execution when only grouping or log transform changes. It stops short of describing return contents or component defaults.

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?

Front-loads the core purpose and the sibling distinction before the detail, which is the right ordering. Some sentences (the group_factors explanation) are dense and line-wrapped, but each carries information rather than 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?

Covers the workflow position, the alternative path, and the grouping mechanics thoroughly, which is the main complexity for this tool. However, with no output schema and no annotation coverage beyond readOnlyHint, an agent still lacks guidance on what components does, what top_features (default 10) controls, or what the call returns — meaningful gaps for a 5-parameter analysis tool.

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% and there are 5 parameters, so the description must compensate. It does well on grouping — group_levels is one factor, group_factors is a product of factor axes with a concrete example ([['control','ILG'],['0h','6h']] → 'control|0h') and a note that tokens resolve from both Class ID and sample name — but components and top_features are never mentioned, leaving two parameters undocumented anywhere.

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?

States a specific verb+resource (PCA on the matrix produced by arf_preprocess) and explicitly frames itself as the entry point of the preprocessed route. It also names the distinct sibling path (arf_parser) that re-filters raw spots, so an agent can tell the two apart without reading either schema.

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?

Gives the exact call order (arf_preprocess → this tool) and the condition that selects the alternative arf_parser (PCA that refilters raw spots). It also states when NOT to redo preprocessing — if only group_levels coloring or log transform changes, just re-run this tool.

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