AI NetCafé

Two tables → what differs (the VLOOKUP job, no amounts needed)

diff_tables

Read-onlyIdempotent

Matches rows across two CSVs on a key column and reports three things: keys only in A, keys only in B, and keys in both whose other columns disagree — naming the exact column and both values. Unlike reconcile_ledger this needs no amount column, so it also fits name lists, inventory counts, permission tables, and any "these two exports should match" check.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "key": "<key>"
    },
    "name": "diff_tables"
  }
}

Input Schema

Name	Required	Description
`key`	Yes	Column that identifies a row, e.g. id.
`url_a`	No	Link to the first CSV.
`url_b`	No	Link to the second CSV.
`text_a`	No	Or the first CSV content directly.
`text_b`	No	Or the second CSV content directly.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedAug 17, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds behavioral context beyond these by explaining the exact matching semantics and that it reports which column differs and both values. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core purpose, then followed by usage guidance. Every sentence earns its place, with no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has an output schema, so return values are already specified. The description provides all necessary operational context: the matching algorithm, output categories, and appropriate use cases. It is fully complete for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with each parameter clearly described (e.g., 'Column that identifies a row', 'Link to the first CSV'). The tool description does not need to add parameter-level detail since the schema already does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Matches rows across two CSVs on a key column' and specifies the exact three outputs (keys only in A, only in B, and mismatches with column names and values). It also distinguishes itself from the sibling reconcile_ledger by explicitly noting it needs no amount column.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Unlike reconcile_ledger this needs no amount column' and lists appropriate use cases ('name lists, inventory counts, permission tables, and any "these two exports should match" check'). This provides clear when-to-use guidance and names an alternative.

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

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