preprocess_data

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

Annotations indicate the tool is not read-only (readOnlyHint=false), but the description does not explain behavioral traits beyond listing processing steps. It fails to disclose that the tool modifies the dataset or produces new objects, what side effects occur, or how results are stored. The description adds minimal value beyond the annotation.

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 short and to the point, with a clear opening statement and a simple 'Args' list. It front-loads the purpose and is free of fluff. A slightly more structured format (e.g., bullet points) could improve readability but it remains efficient.

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 (30+ parameters) and the presence of an output schema (not shown), the description should indicate what the preprocessing produces (e.g., modified dataset, new files, or in-memory updates). It fails to describe the outcome or how to interpret results, leaving the agent with incomplete context.

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?

The input schema is rich with 30+ parameters, each having a description. Schema description coverage is effectively high (despite context signal claiming 0%). The tool description only mentions 'params' and says they have sensible defaults, adding no new semantic information. Baseline score is 3 for high schema coverage.

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 tool's purpose: 'Preprocess spatial transcriptomics data (QC, normalization, HVGs, PCA, clustering, spatial neighbors).' It uses a specific verb ('preprocess') and resource ('spatial transcriptomics data') and lists the main steps. This distinguishes it from sibling tools that perform analysis (e.g., analyze_cell_communication) or loading (load_data).

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 implies usage as a preprocessing step after data loading but before analysis. However, it does not explicitly state when to use it, when not to, or mention alternatives. Given the sibling set includes no other preprocessing tools, the context is clear but the description lacks explicit guidance.

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