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weather-risk-skill

Assess weather conditions and assign operational risk levels for flight planning.

DeepseekModel Curated skill Quality Good · 48 v1.0.0

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https://deepseekmodel.com/api/download.php?id=froot1-aeroops-ai-agents-skills-weather-risk-skill-skill-md&format=skill
Download .skill Standard format with system_prompt and model_config, ready for any agent framework
The actual content of the system_prompt field in the .skill file.
name weather-risk-skill description Assess weather conditions and assign operational risk levels for flight planning. Weather Risk Skill This skill evaluates the meteorological data supplied for a flight (e.g., METAR, TAF, free‑text weather notes) and translates it into a risk classification (LOW, MEDIUM, HIGH) that can be used by the AeroOps AI workflow. Input Expected weather_text : Raw weather report string (METAR/TAF or free‑form description). Optional: scheduled_time (ISO‑8601) to consider time‑dependent phenomena (e.g., forecasts). Risk Assessment Rules Condition Risk Level HIGH • Visibility < 1000 m OR < 3 SM in IFR conditions • Wind shear, thunderstorms, severe turbulence, or lightning in the vicinity • Significant icing conditions (temperature ≤ 0 °C with visible moisture) • Runway surface contamination (snow/ice) with reduced braking performance MEDIUM • Moderate turbulence, light rain/sleet, visibility 1000‑3000 m • Winds > 30 kt or cross‑winds exceeding runway limits • Cloud ceiling 500‑1500 ft (IFR) but no severe weather LOW • VMC/clear weather, visibility > 5 km, light winds (< 15 kt) • No significant hazards reported Output Produced weather_risk_level : LOW , MEDIUM or HIGH . weather_summary : Human‑readable narrative explaining the assessment. Usage in Agent The AeroOps AI agent can call this skill to obtain weather_risk_level and embed the summary in the final briefing, or to trigger a Human‑in‑the‑Loop review when risk is HIGH. Implementation notes The skill should be pure logic; no external API calls. Accept both structured METAR strings and free‑form text using simple keyword detection. Return JSON‑compatible fields as shown in the output section.
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Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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