dataset_info

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

With no annotations provided, the description carries the full burden, and it does well: it discloses that the tool reads local files, returns structural/statistical summaries, and explains path resolution semantics (relative paths resolve against datasets/ or MCP_DATASETS_DIR; absolute paths are allowed). It does not discuss failure modes or read-only guarantees, but none of those are essential for this simple analysis tool.

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 compact and well structured: one front-loaded sentence establishes purpose and outputs, followed by a single bullet that clarifies the parameter. Every sentence adds value and there is no redundant or promotional content.

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 low-complexity, single-parameter tool, the description covers purpose, behavior, return scope, and path semantics. An output schema exists, so detailed return formatting is not required. Minor omissions like error behavior or file-size limits are not critical for this tool's typical use.

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%, but the description fully compensates for the single 'path' parameter by explaining what it is, how relative paths are resolved, and that absolute paths are also accepted. This is more than sufficient for an agent to provide a correct value.

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 states a specific action ('analyze local dataset'), the supported formats (CSV/JSON), and the concrete outputs (structure, row count, per-column statistics). It also gives the intended use case (quick pre-processing reconnaissance for competitions), which clearly distinguishes it from the sibling tools that involve search, PDF extraction, or project scaffolding.

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 explicitly frames when to use the tool: 'for quick familiarity before competition data processing'. While it does not name alternative tools or state exclusion conditions, the sibling set is dissimilar enough that no explicit negative guidance is necessary.

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