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Hug0x0

mcp-reunion

reunion_get_covid_emergency_stats

Retrieve daily COVID-19 emergency room attendance and SOS Médecins activity in La Réunion, broken down by age class. Returns per-day counts for ER visits, hospitalizations, and SOS Médecins acts.

Instructions

Daily COVID-19 emergency-room attendance and SOS Médecins activity in La Réunion, broken down by age class. Returns per-day counts for ER COVID visits, total ER visits, COVID-related hospitalizations from ER, and SOS Médecins COVID acts. Source: Santé publique France via data.regionreunion.com. Sorted most recent first. Combine with reunion_get_covid_hospital_stats for in-hospital indicators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fromNoInclusive lower bound on date, ISO format YYYY-MM-DD (e.g. "2021-01-01")
toNoInclusive upper bound on date, ISO format YYYY-MM-DD (e.g. "2022-12-31")
age_labelNoAge-bracket label as published by SpF, e.g. "0-14 ans", "15-44 ans", "45-64 ans", "65-74 ans", "75 ans et plus", "Tous âges"
limitNoMax rows to return (1-500, default 50)
Behavior4/5

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

With no annotations, the description carries full burden. It discloses data source (Santé publique France), sorting order (most recent first), and what is returned. Though it lacks details on rate limits or authentication, for a read-only data retrieval tool, this is adequate.

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 concise and front-loaded, stating the core function first, then listing data points, source, and sibling tool guidance. Every sentence is necessary and efficient.

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

Completeness5/5

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

For a simple data retrieval tool with no nested objects and full schema coverage, the description is complete. It specifies what columns are returned, mentions the source, and suggests complementary tools. No output schema exists, but the description covers return values adequately.

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 baseline is 3. The description adds context (age class breakdown, daily data) but does not explain parameters beyond what the schema already provides. It adds marginal value.

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 returns daily COVID-19 emergency-room attendance and SOS Médecins activity in La Réunion, broken down by age class, listing specific metrics. It also distinguishes from the sibling tool reunion_get_covid_hospital_stats.

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 mentions combining with reunion_get_covid_hospital_stats for in-hospital indicators, providing clear guidance on when to use this tool versus alternatives. It does not explicitly state when not to use it, but the context is sufficient.

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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