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

Annotations already declare readOnly/openWorld=false/destructive=false, and the description adds genuine behavioral detail beyond them: properties are scaled before PCA, the Morgan space uses radius-2 bits, constant properties are silently dropped, and the returned statistics (SD, variance share, loadings) are enumerated. It does not say how missing values or how many components are handled, which is a modest remaining 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?

A single front-loaded sentence with a colon-delimited enumeration of outputs; dense but every clause carries information. The output enumeration is somewhat redundant given a dedicated output schema exists.

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 four-parameter read-only analysis tool with a full output schema, the description covers the algorithm, the input spaces, preprocessing (scaling, constant-property exclusion) and the shape of results. An agent has enough to call it correctly; only edge-case behavior (missing values, component count limits) is unaddressed.

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 100%, so the schema already documents 'molecules' (one SMILES or molfile per entry) and the 'space' enum. The description adds only marginal semantics, clarifying that 'descriptors' means a scaled property table and that the Morgan bits are radius-2 (ECFP4), which largely restates the enum descriptions.

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 operation (principal component analysis) on a specific resource (a list of small molecules), and names the exact algorithm ('computed as R's prcomp computes them') plus the two spaces it can run over. This clearly separates it from siblings like cluster_molecules or compare_molecules, though it never names an alternative explicitly.

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?

Usage is only implied: the description tells you the tool produces PC scores, so an agent can infer it is for dimensionality reduction/visualization of a molecule set, but there is no statement of when to prefer it over cluster_molecules, compare_molecules, or assess_small_molecule, and no guidance on choosing between the descriptors and morgan spaces (that lives only in the schema enum descriptions).

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