Data Analytics MCP Toolkit

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

With no annotations provided, the description carries the full burden. It discloses that the tool returns a 'data_id and schema summary' and that this ID is used in subsequent tools, which adds useful context about output and workflow. However, it lacks details on behavioral traits like error handling, rate limits, authentication needs, or what happens with invalid data, leaving gaps for a tool with mutation implications (data ingestion).

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 appropriately sized and front-loaded: the first sentence states the core purpose, and the second adds crucial usage context. Every sentence earns its place with no wasted words, making it efficient and easy to parse.

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 no annotations, no output schema, and 4 parameters with 0% schema coverage, the description is incomplete. It covers purpose and basic usage but lacks details on parameters, error cases, or behavioral nuances. For a data ingestion tool with potential complexity, this leaves significant gaps, though it meets a minimum viable level by explaining the workflow.

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 mentions 'CSV or JSON (inline string or URL)' which partially explains the 'source' parameter, but doesn't address 'format', 'session_id', or 'delimiter'. With 4 parameters and low coverage, the description adds minimal meaning beyond the schema, failing to fully clarify parameter roles or usage.

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: 'Ingest data from CSV or JSON (inline string or URL).' It specifies the verb ('ingest') and resource ('data'), and mentions the input formats. However, it doesn't explicitly differentiate from siblings like 'run_analytics' or 'train_test_split' which might also involve data handling, though the focus on ingestion is clear.

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 provides clear context for usage: 'Use the returned data_id in subsequent tools (clean_data, plot_*, train_*, etc.).' This indicates this tool is a prerequisite for other operations, giving good guidance on when to use it. However, it doesn't explicitly state when NOT to use it or name alternatives among siblings, such as if other tools might handle data loading differently.

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