CockroachDB MCP Server

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

No annotations are provided, so the description carries the full burden. It mentions that the tool 'bulk import data' and returns a 'success message or an error message', but does not disclose critical behavioral traits such as whether it overwrites existing data, requires specific permissions, handles errors gracefully, or has rate limits. For a mutation tool with zero annotation coverage, 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 well-structured and appropriately sized, with a concise opening sentence stating the purpose, followed by organized sections for Args, Returns, and Example. Every sentence adds value without redundancy, and the example illustrates usage clearly, making it easy to understand at a glance.

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 (data import with multiple parameters) and lack of annotations or output schema, the description is moderately complete. It covers parameters well and includes an example, but lacks details on behavioral aspects (e.g., data overwrite policy, error handling) and does not explain the return value beyond 'success or error message'. For a mutation tool, this leaves room for improvement in contextual understanding.

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 0%, so the description must compensate. It provides clear semantics for all 5 parameters in the 'Args' section, explaining each parameter's purpose (e.g., 'URL to the data file', 'CSV delimiter') and default values. This adds substantial meaning beyond the bare schema, though it could include more details like URL format examples or delimiter constraints.

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 ('bulk import data into a table') and resources ('from a file'), distinguishing it from sibling tools like create_table or execute_query by focusing on data ingestion rather than schema manipulation or query execution. It specifies supported file formats (CSV/Avro) and storage sources (S3, Azure Blob, etc.), making the scope explicit.

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 for importing data from external files into tables, but does not explicitly state when to use this tool versus alternatives (e.g., manual inserts or other import methods). It mentions supported formats and storage types, providing some context, but lacks guidance on prerequisites, limitations, or comparisons with sibling tools like execute_query for data manipulation.

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