claudetools/.claude/skills/unifi-wifi/SKILL.md

name, description

name

description

unifi-wifi

Analyze and tune UniFi WiFi for performance + stability, especially in dense/congested environments. Audits AP/radio config and the neighbor-interference map from the UOS controller, flags issues (2.4GHz over-provisioning, channel width, min-RSSI/sticky clients, channel plan), and recommends prioritized changes. Works for any UniFi site on the UOS (172.16.3.29); Cascades is the hard case. Triggers: unifi wifi tuning, RF/airtime/channel analysis, 2.4GHz congestion, AP channel plan, sticky clients, wireless performance.

UniFi WiFi tuning (UOS sites)

Data-driven WiFi tuning for UniFi sites on the UOS Server (172.16.3.29). Goal: solid performance + stability for connected devices in congested environments by analyzing what the controller knows and making prioritized, validated changes. Built for any site; Cascades (77 APs, ~550 clients, brutal 2.4GHz) is the reference hard case.

First, load context

• references/data-access.md — what data the UOS exposes and how to read it (the two planes: Mongo config/interference now, live Network API later).
• references/methodology.md — the prioritized tuning playbook (synthesized from a multi-model pass + live recon). Read before recommending any change.

What it does (current = Plane 1, read-only)

1. Audit a site — config + interference, no live plane needed:

   bash .claude/skills/unifi-wifi/scripts/audit-site.sh <site-name|site_id>
   bash .claude/skills/unifi-wifi/scripts/audit-site.sh cascades
   

   Outputs 2.4/5/6 config summary, the per-channel neighbor-density (interference) map, and flagged issues (2.4 over-provisioning, 40/80/160MHz width, off-1/6/11 channels, min-RSSI off, high power).
2. Interpret the flags against methodology.md (fix order: prune 2.4 -> shrink cells/power -> min data rates -> manual 1/6/11 plan -> min-RSSI + roaming -> steer to 6GHz).
3. Recommend a prioritized, per-zone change plan. Roll out per zone, not site-wide at once.

Ad-hoc Mongo queries: .claude/scripts/uos-mongo.sh (recipes in data-access.md). Access is the vaulted dedicated key infrastructure/uos-server-ssh-key (works from any fleet machine).

The two data planes (know which you're using)

• Plane 1 — Mongo ace (available now, read-only via SSH): radio config (radio_table), the rogue neighbor-interference map, channelplan, AP/client inventory. Enough for the full config audit + channel/interference plan — covers the 2.4GHz "first problem".
• Plane 2 — live Network API (stat/device, stat/sta; NOT yet wired): live channel utilization (cu_total), per-client RSSI/SNR/retries, AP satisfaction. Needed to validate changes (before/after) and find the worst APs by live airtime. Wiring it needs a dedicated read-only UniFi admin or integration API key on .29, vaulted as infrastructure/uos-server-network-api. See data-access.md "Plane 2".

Applying changes — IMPORTANT boundary

This skill is audit + advisory today. Writing config to the controller is not wired and is high-stakes (a bad channel/power/disable push degrades a live facility). When change-application is added it MUST: go through the controller API with an authed account; change one zone at a time; capture live cu_total/satisfaction before and after each change; and never run nightly/auto channel optimization in ultra-dense sites (pin a manual plan). Until then, hand the recommended plan to a tech to apply in the UniFi UI, or get explicit go before any write path is built.

Roadmap

• Phase 1 (done): config + interference audit, flags, methodology. Read-only.
• Phase 2: wire the live Network API (Plane 2) for cu_total/satisfaction/per-client RF → before/after validation + "worst APs by airtime" ranking.
• Phase 3: assisted change application (per-zone, API-driven, with live before/after gating).

Notes

• The methodology is independent-model guidance + config-plane recon — validate against live stats before trusting any single recommendation, and roll out per zone.
• Multi-site: pass any site name/id; uos-mongo.sh --sites lists them. Cascades = 685f39068e65331c46ef6dd2.