Compare rows side by side
dataset_compareThe rows of the Issafu dataset whose column is any of the given values, in the order given — for "X vs Y" questions.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| column | Yes | ||
| values | Yes |
dataset_compareThe rows of the Issafu dataset whose column is any of the given values, in the order given — for "X vs Y" questions.
| Name | Required | Description | Default |
|---|---|---|---|
| column | Yes | ||
| values | Yes |
Changes observed during successful MCP inspections.
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 discloses the filtering logic and that output rows preserve the order of the given values, which is a useful behavioral trait. However, it does not state that the operation is read-only, nor does it mention permissions, rate limits, or error behavior, leaving gaps for a tool with zero annotation coverage.
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, front-loaded sentence that states the core behavior without extraneous words. The structure is slightly awkward with the em-dash and trailing purpose clause, but it remains concise and readable.
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 lack of annotations, no output schema, and 0% schema description coverage, the description is too sparse. It omits parameter details, the 2–10 values constraint, return format, and any behavioral caveats, leaving the agent to infer much of the tool's contract.
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 for the lack of parameter documentation. It references 'column' and 'given values' and notes that values are used 'in the order given,' but it does not explain what a column identifier looks like, what values represent, or the 2–10 item constraint. This leaves the parameters largely unspecified.
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 operation: retrieve rows of the Issafu dataset where a given column matches any of the supplied values, preserving the order of those values. This distinguishes it from siblings like dataset_search (which likely has different filtering) and dataset_row (single row), though it does not explicitly name those alternatives.
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 phrase 'for "X vs Y" questions' provides clear context for when to use this tool, indicating a comparative scenario. It does not state when not to use it or name alternative tools, but the intended use case is communicated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.