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thermostat

Adjust temperatures, diagnose comfort issues, calculate energy savings, and automate schedules through voice commands or smart home integration.

DeepseekModel Curated skill Quality Good · 64 v1.0.0

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https://deepseekmodel.com/api/download.php?id=clawic-skills-skills-thermostat-skill-md&format=skill
Download .skill Standard format with system_prompt and model_config, ready for any agent framework
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name Thermostat slug thermostat version 1.0.0 description Adjust temperatures, diagnose comfort issues, calculate energy savings, and automate schedules through voice commands or smart home integration. homepage https://clawic.com/skills/thermostat metadata {"clawdbot":{"emoji":"🌡️","displayName":"Thermostat"}} What the Agent Can Do User Request Agent Action "Make it warmer/cooler" Adjust setpoint ±2-3°F or to specific temp "Why is my bedroom cold?" Diagnose: sensor location, vent issues, zone problems "Set up a schedule" Gather wake/leave/return/sleep times → configure "Am I wasting money?" Calculate setback savings, identify inefficiencies "I'm going on vacation" Set freeze protection (55°F) or vacancy mode "Something's wrong with my heat" Troubleshoot: cycles, error codes, aux heat issues Before Adjusting Temperature Gather context: Current temp and setpoint Heating or cooling mode? Smart thermostat or basic? Any specific room complaints? Smart thermostats: Adjust via voice, app command, or API integration. Basic thermostats: Guide user to physical adjustment, suggest smart plug workarounds if relevant. Diagnosing Comfort Problems When user says "it's too hot/cold": Check location mismatch — Thermostat in hallway but complaint is bedroom? Sensor measures wrong place. Solution: remote sensors or door management. Check system behavior — Running constantly? Short cycling (<5 min)? Not turning on? Each has different diagnosis path. See troubleshooting.md . Check settings — Wrong mode? Hold preventing schedule? Eco mode active unexpectedly? Energy Calculations When user asks about savings: Setback rule of thumb: 1°F setback for 8 hours = ~1% savings. Scenario Estimated savings 10°F night setback (8h) 5-15% 10°F work setback (8h) 5-15% Both combined 10-25% Heat pump exception: Deep setbacks may trigger expensive aux heat. Recommend 3-5°F max for heat pumps. Myth to debunk: "Costs more to reheat" is false except heat pumps in extreme cold. Vacation/Away Configuration Short away (hours): Set 62°F heat / 82°F cool. Extended vacation: Minimum 55°F (pipe freeze protection) Maximum 85°F (humidity/mold prevention) Enable leak sensor alerts if available Remind user: Set return date or use geofencing to avoid coming home to extreme temps. Load Detailed Reference Situation Reference Mode explanations, holds, fan settings basics.md System not responding, error codes, HVAC issues troubleshooting.md Cost calculations, efficiency tips, renter workarounds efficiency.md HomeKit, Alexa, Google, Home Assistant, Matter integration.md Vacation settings, freeze protection, humidity away.md
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The downloaded .skill package contains the following fields.
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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