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andronaft

health-os

stage_lab_panel

Stage extracted lab panel rows as PENDING, alert on critical values, then display the table and wait for approval before saving.

Instructions

Stage an extracted lab panel (PENDING). rows: a list of {raw_name, value, unit, ref_min, ref_max}. Critical values are alerted immediately. Afterwards — show the table to the user and wait for an explicit approve_staged_source.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYes
facilityNo
panel_dateYes
panel_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, idempotentHint=false and openWorldHint=true. The description adds genuinely useful behavioral context beyond that: the PENDING state, immediate alerting of critical values, and the requirement of explicit human approval before downstream approval. It stops short of specifying idempotency or re-staging behavior, which matters given idempotentHint=false.

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?

Three tight sentences, front-loaded with the action and state, followed by the row shape and the required follow-up. No filler, though the trailing dash construction is slightly informal.

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?

An output schema exists, so return values need not be explained. The description covers purpose, the staged/PENDING lifecycle, critical-value behavior, and the mandatory approval follow-up, leaving only minor gaps around the non-rows parameters.

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 0%, so the description must carry the parameter burden. It documents the rows item shape ({raw_name, value, unit, ref_min, ref_max}) well, but leaves facility, panel_type, and even the required panel_date format/expectations unaddressed, so it only partially compensates.

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?

States a specific verb (Stage) and resource (extracted lab panel) plus the resulting state (PENDING), and it clearly positions itself before approve_staged_source. It does not name a sibling to avoid, but the two-step relationship is explicit enough to distinguish it from the read/report siblings.

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?

Gives clear usage context: stage now, then show the table to the user and wait for an explicit approve_staged_source. This tells the agent when the tool fits in the workflow and what must follow, though it doesn't state exclusions for panels already staged or alternative staging paths.

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