mcp-csv-analyst

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions grouping and aggregation but lacks details on permissions, file format requirements, error handling, or output format. For a tool that processes files and performs computations, this leaves significant gaps in understanding its behavior.

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 a single, efficient sentence with zero waste. It front-loads the core functionality and uses clear, direct language without unnecessary elaboration, making it easy to parse quickly.

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 complexity of file processing and aggregation, no annotations, and no output schema, the description is incomplete. It doesn't explain the return values, error conditions, or behavioral traits like whether it modifies the original file. For a tool with 4 required parameters and computational operations, more context is needed.

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 all parameters thoroughly. The description adds minimal value beyond the schema by implying the relationship between group_column and agg_column, but doesn't provide additional syntax, format details, or examples. Baseline 3 is appropriate when the schema does the heavy lifting.

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 with specific verbs ('group rows' and 'compute an aggregate') and identifies the resource (CSV rows). It distinguishes from siblings like csv_aggregate or csv_filter by focusing on grouping with aggregation, but doesn't explicitly differentiate from csv_aggregate which might have similar functionality.

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?

No guidance is provided on when to use this tool versus alternatives like csv_aggregate or csv_filter. The description implies usage for grouping and aggregation tasks but offers no explicit context, prerequisites, or exclusions for selecting this tool over siblings.

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