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mfbaig35r
by mfbaig35r

units_propose

Preview the rows a table would process before writing them, and warn when a missing or ambiguous base document could produce incorrect results.

Instructions

Show the rows a table would run over, without writing them.

Grouped tables assemble a family from a base document plus everything issued under it. Reports dependents whose base is absent or ambiguous: 00a warns that a family missing an amendment produces a confidently wrong row and nothing else detects it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYesTable number as the corpus defines it, e.g. '01' or '13'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It explicitly discloses a key behavior: the tool does not write rows ('without writing them'), and it describes a specific warning mechanism (00a for ambiguous families). This is transparent about its side-effect-free nature and a notable edge-case behavior, though it does not mention permissions, performance, or return format (output schema exists).

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

Conciseness4/5

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

The description is two sentences. The first is a clear, front-loaded summary. The second provides useful context about grouped tables and the warning, which earns its place. It is not verbose, though the second sentence is long and could be split for readability, but overall it is efficient.

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

Completeness4/5

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

For a single-parameter preview tool with an output schema, the description covers the essential behavior (dry-run, no writes) and a specific warning condition. It does not mention prerequisites or side effects beyond non-writing, but given the simplicity and existing output schema, it is reasonably complete.

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?

The schema already fully documents the 'table' parameter (100% coverage), including the format and examples. The description adds no extra semantic detail about the parameter itself; the grouped-table context is about the tool's behavior, not the parameter. Baseline 3 is appropriate when schema is sufficient.

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

Purpose4/5

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

The description clearly states a specific verb-resource pair: 'Show the rows a table would run over, without writing them.' This distinguishes it from writing tools, but it does not explicitly name sibling tools (e.g., run_table or units_assemble) or state why it is preferred for previewing. The grouped-table explanation adds context but does not name alternatives.

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 usage (preview before writing) and explains the behavior for grouped tables and the 00a warning, but it does not explicitly state when to use this tool over siblings, nor does it list exclusions. The context is present but not framed as guidance.

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