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Get one review item

get_review_item
Read-onlyIdempotent

Retrieve a complete review item with every evidence row quoted exactly, including row numbers and rule sources, to trace findings back to the original lab data.

Instructions

Return one review item from tidy_lab_files in full, with every evidence row quoted exactly as it is in its file.

Use it to show the person the lab, chain-of-custody and field-sheet lines behind a finding, with their row numbers, the rule and its source, and the judgement left to the scientist. Numbers come from tidy_lab_files for the same site.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYesSite id. Only the synthetic site 'FDS-01' is available.
numberYesReview item number from tidy_lab_files, starting at 1.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemYes
noteYes
siteYes
of_totalYesHow many review items the site has.
syntheticYes
source_linesYesEvery evidence row, as written in its file.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already communicate that the operation is read-only, idempotent, and non-destructive. The description adds meaningful behavioral detail beyond that: results quote evidence rows exactly, include row numbers and rule source, and leave judgement to the scientist. No contradiction 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.

Conciseness4/5

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

The description is compact and front-loaded with the core behavior. The second sentence adds useful context about what the review item containsolaris. The final sentence is slightly redundant but does reinforce the data source relationship.

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?

Given the output schema and strong annotations, the description is sufficient for an agent to understand what the tool returns and when to use it. It could go further by explicitly naming sibling tools or exclusions, but nothing critical is missing.

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%, so the description does not need to restate parameter meanings. It does add a small clarifying note that numbers come from tidy_lab_files for the same site, but most parameter semantics are already carried by the schema.

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 uses a specific verb and resource: 'Return one review item from tidy_lab_files in full'. It further specifies the key behavior, 'every evidence row quoted exactly as it is in its file', which clearly distinguishes this from a generic list or summary tool.

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

Usage Guidelines4/5

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

The description gives a clear use case: 'Use it to show the person the lab, chain-of-custody and field-sheet lines behind a finding'. It explains what context the returned item provides, though it does not explicitly name alternatives or state when not to use it.

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