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Calculator source table

get_tool_data
Read-onlyIdempotent

The source table one Open Factory calculator runs on, with every input's provenance: copper-wire-price-sheet, genset-tco, interconnection-cost, lead-time-schedule, pjm-capacity-bill, quote-check, tariff-exposure-calculator, transformer-sizing-cost. The calculation itself runs in the browser at the tool URL in this version.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolYesTool slug.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and a closed-world hint, so safety is covered. The description adds genuinely non-obvious behavioral context: the actual calculation happens client-side at the tool URL, so this tool yields source data rather than computed results — an important expectation-setting detail agents cannot get from the annotations.

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

Conciseness3/5

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

The lead sentence is reasonably front-loaded, but listing all eight enum slugs in the prose is pure duplication of the input schema and bloats the text. The second sentence about browser execution is useful but awkwardly worded and tacked on.

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

Completeness3/5

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

For a single-parameter read tool with full annotations and a fully-described enum schema, the definition is mostly adequate, and 'with every input's provenance' signals the shape of the return payload despite the absent output schema. However, it never clarifies what the returned table actually contains field-by-field or whether it can be empty for a given slug.

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 coverage is 100% and the single 'tool' parameter has an enum plus a description ('Tool slug.'), so the schema already carries the semantics. The description restates all eight slug values verbatim, adding no format, default, or error-behavior detail beyond the schema — baseline 3.

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

Purpose3/5

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

The description identifies the resource ('the source table one Open Factory calculator runs on, with every input's provenance') and the sibling set of calculators it applies to, but it never uses a retrieval verb and 'source table' is domain jargon. An agent can infer this returns underlying input data for a named calculator, but the phrasing is indirect rather than a clear verb+resource statement.

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

Usage Guidelines2/5

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

No when-to-use guidance is given, nor any exclusions or alternatives among the many sibling get_* tools. The trailing note about the calculation running in the browser hints at scope, but it is a caveat rather than routing guidance.

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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