wifi-dead-zoneUse when Wi-Fi is slow or drops in specific rooms, when placing a router or mesh node in a new home, when deciding if you need a mesh system or just a better router spot, when your 5 GHz doesn't reach the bedroom, or when picking clean channels among neighbors — builds a floor plan of your home as a simple model (rooms, walls, materials), estimates per-room signal with real RF physics (log-distance path loss + per-material wall attenuation), renders an ASCII heatmap, grid-searches 676 candidate spots for the optimal router placement, tells you exactly where to put mesh nodes (and where NOT to), calibrates against your actual phone measurements, and recommends non-overlapping channels given your neighbors' networks.
Install via ClawdBot CLI:
clawdbot install voronindenis5/wifi-dead-zoneGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://clawhub.ai/user/voronindenis5Audited Sep 29, 2026 · audit v1.0
Generated Sep 29, 2026
A remote worker struggles with dropped video calls in a spare-bedroom office. They map their apartment in the home JSON, run the plan command, and discover a load-bearing concrete wall is the primary culprit. The tool recommends a new router position that lifts the weakest room by almost one RSSI grade without buying any hardware.
A family moving into a new house wants usable Wi-Fi everywhere before furniture arrives. Using floor plan coordinates and wall materials, they run the grid-search to find the optimal router spot and identify which rooms will likely need mesh nodes. This avoids buying unnecessary hardware and ensures good coverage from day one.
A homeowner is about to spend $300 on a mesh kit but is unsure if it will help. They model their current setup, see that moving the router would fix most dead zones, and get explicit mesh-node placement advice for the two remaining weak rooms. The analysis saves money and avoids the common mistake of putting a node inside the dead room.
An apartment dweller experiences intermittent slowdowns despite strong signal, caused by neighbors crowding 2.4 GHz and 5 GHz channels. They run the channels command with a neighbor scan list to get non-overlapping recommendations, then reconfigure the router for a cleaner channel. This resolves congestion without new equipment.
An independent IT consultant uses the skill to produce per-room Wi-Fi heatmaps and placement plans for clients during home visits or remote consultations. The calibrated model and honest error bars lend credibility, and the clear advice list helps clients understand why their current setup fails. It becomes a repeatable, low-cost diagnostic offering.
Offer the core floor-plan modeling and heatmap for free to attract homeowners, then charge a one-time or subscription fee for advanced features like mesh placement optimization, multi-floor support, and historical surveys. The open-source script is wrapped in a polished mobile/web UI for non-technical users.
Internet service providers embed the skill into their support apps or technician tablets to remotely diagnose customer Wi-Fi complaints and recommend router relocation or mesh add-ons. This reduces truck rolls and improves customer satisfaction while creating upsell opportunities for managed Wi-Fi hardware.
Connect homeowners with vetted installers who use the skill to plan and verify router and mesh placement during smart-home setup appointments. The platform takes a commission on each job and can upsell premium calibration visits using phone-based surveys.
💬 Integration Tip
Collect 2–3 real RSSI measurements in the worst rooms and use the compare command to calibrate wall materials before trusting the model; also verify neighbors' channels with a Wi-Fi analyzer app for accurate channel advice.
Scored Sep 29, 2026
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