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numproof

numproof

by projecttron
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

diff_rows

Compare numeric rows across report versions, identifying changes and preserving provenance for audit.

Instructions

Compare two report versions by numeric row labels with provenance.

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": {
      "rows_before": "<rows_before>",
      "rows_after": "<rows_after>"
    },
    "name": "diff_rows"
  }
}

Input Schema

NameRequiredDescriptionDefault
rows_afterYes
rows_beforeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It mentions 'provenance' as a hint of what the output may include, but it does not explain whether the operation is read-only, what the output structure looks like, or how differences are presented. This is insufficient for a tool with no annotation support.

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 a single, front-loaded sentence that efficiently communicates the core purpose. Every word contributes value (compare, two report versions, numeric row labels, provenance), with no filler or redundant information.

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

Completeness2/5

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

The tool has no output schema, no annotations, and only minimal parameter descriptions. The description does not explain the return value, edge cases, or any operational context beyond 'compare'. For a diff tool, users would need to know the format of the diff result or any side effects, which are absent. The description is too sparse for the tool's complexity.

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

Parameters2/5

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

The input schema provides only array types for rows_before and rows_after (schema coverage 0%). The description adds that comparison is 'by numeric row labels', which gives a hint about the data structure, but it does not explain how these arrays should be formatted, what elements are expected, or how labels are used. The description does not sufficiently compensate for the lack of parameter documentation.

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 tool's purpose: comparing two report versions. It specifies the method ('by numeric row labels') and adds context ('with provenance'), distinguishing it from sibling tools like audit_rows or verify_claim. The verb 'compare' and resource 'report versions' make it unambiguous.

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

Usage Guidelines3/5

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

The description implies when to use the tool (when comparing two versions), but it does not provide explicit when-to-use guidance or mention alternatives/exclusions. Sibling tools exist, but the description does not contrast against them, leaving usage context partially implied.

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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