neuroskill-bci – skill Khác cho agent AI
Sử dụng trạng thái nhận thức và tâm trạng BCI trực tiếp từ NeuroSkill.
Cài skill neuroskill-bci bằng một lệnh
Chọn công cụ bạn đang dùng, copy lệnh và dán vào terminal. Skill sẽ nằm trong thư mục skills của công cụ đó và sẵn sàng dùng ở phiên làm việc tiếp theo.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/neuroskill-bci-4f7ee.tgz | tar xz -C ~/.claude/skills
Gọi trong Claude Code: /neuroskill-bci – rồi mô tả công việc bạn muốn làm.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/neuroskill-bci-4f7ee.tgz | tar xz -C ~/.codex/skills
Gọi trong Codex: $neuroskill-bci – rồi mô tả công việc bạn muốn làm.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/neuroskill-bci-4f7ee.tgz | tar xz -C ~/.hermes/skills
Gọi trong Hermes Agent: /neuroskill-bci – rồi mô tả công việc bạn muốn làm.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/neuroskill-bci-4f7ee.tgz | tar xz -C ~/.deepcode/skills
Gọi trong DeepSeek: /neuroskill-bci – rồi mô tả công việc bạn muốn làm.
Nội dung SKILL.md
Nội dung SKILL.md gốc bằng tiếng Anh.
NeuroSkill BCI Integration
Connect Hermes to a running [NeuroSkill](https://neuroskill.com/) instance to read
real-time brain and body metrics from a BCI wearable. Use this to give
cognitively-aware responses, suggest interventions, and track mental performance
over time.
> ⚠️ Research Use Only — NeuroSkill is an open-source research tool. It is
> NOT a medical device and has NOT been cleared by the FDA, CE, or any regulatory
> body. Never use these metrics for clinical diagnosis or treatment.
See references/metrics.md for the full metric reference, references/protocols.md
for intervention protocols, and references/api.md for the WebSocket/HTTP API.
---
Prerequisites
- Node.js 20+ installed (
node --version) - NeuroSkill desktop app running with a connected BCI device
- BCI hardware: Muse 2, Muse S, or OpenBCI (4-channel EEG + PPG + IMU via BLE)
npx neuroskill statusreturns data without errors
Verify Setup
node --version # Must be 20+
npx neuroskill status # Full system snapshot
npx neuroskill status --json # Machine-parseable JSONIf npx neuroskill status returns an error, tell the user:
- Make sure the NeuroSkill desktop app is open
- Ensure the BCI device is powered on and connected via Bluetooth
- Check signal quality — green indicators in NeuroSkill (≥0.7 per electrode)
- If
command not found, install Node.js 20+
---
CLI Reference: npx neuroskill <command>
All commands support --json (raw JSON, pipe-safe) and --full (human summary + JSON).
| Command | Description |
|---------|-------------|
| status | Full system snapshot: device, scores, bands, ratios, sleep, history |
| session [N] | Single session breakdown with first/second half trends (0=most recent) |
| sessions | List all recorded sessions across all days |
| search | ANN similarity search for neurally similar historical moments |
| compare | A/B session comparison with metric deltas and trend analysis |
| sleep [N] | Sleep stage classification (Wake/N1/N2/N3/REM) with analysis |
| label "text" | Create a timestamped annotation at the current moment |
| search-labels "query" | Semantic vector search over past labels |
| interactive "query" | Cross-modal 4-layer graph search (text → EXG → labels) |
| listen | Real-time event streaming (default 5s, set --seconds N) |
| umap | 3D UMAP projection of session embeddings |
| calibrate | Open calibration window and start a profile |
| timer | Launch focus timer (Pomodoro/Deep Work/Short Focus presets) |
| notify "title" "body" | Send an OS notification via the NeuroSkill app |
| raw '{json}' | Raw JSON passthrough to the server |
Global Flags
| Flag | Description |
|------|-------------|
| --json | Raw JSON output (no ANSI, pipe-safe) |
| --full | Human summary + colorized JSON |
| --port <N> | Override server port (default: auto-discover, usually 8375) |
| --ws | Force WebSocket transport |
| --http | Force HTTP transport |
| --k <N> | Nearest neighbors count (search, search-labels) |
| --seconds <N> | Duration for listen (default: 5) |
| --trends | Show per-session metric trends (sessions) |
| --dot | Graphviz DOT output (interactive) |
---
1. Checking Current State
Get Live Metrics
npx neuroskill status --jsonAlways use --json for reliable parsing. The default output is colorized
human-readable text.
Key Fields in the Response
The scores object contains all live metrics (0–1 scale unless noted):
{
"scores": {
"focus": 0.70, // β / (α + θ) — sustained attention
"relaxation": 0.40, // α / (β + θ) — calm wakefulness
"engagement": 0.60, // active mental investment
"meditation": 0.52, // alpha + stillness + HRV coherence
"mood": 0.55, // composite from FAA, TAR, BAR
"cognitive_load": 0.33, // frontal θ / temporal α · f(FAA, TBR)
"drowsiness": 0.10, // TAR + TBR + falling spectral centroid
"hr": 68.2, // heart rate in bpm (from PPG)
"snr": 14.3, // signal-to-noise ratio in dB
"stillness": 0.88, // 0–1; 1 = perfectly still
"faa": 0.042, // Frontal Alpha Asymmetry (+ = approach)
"tar": 0.56, // Theta/Alpha Ratio
"bar": 0.53, // Beta/Alpha Ratio
"tbr": 1.06, // Theta/Beta Ratio (ADHD proxy)
"apf": 10.1, // Alpha Peak Frequency in Hz
"coherence": 0.614, // inter-hemispheric coherence
"bands": {
"rel_delta": 0.28, "rel_theta": 0.18,
"rel_alpha": 0.32, "rel_beta": 0.17, "rel_gamma": 0.05
}
}
}Also includes: device (state, battery, firmware), signal_quality (per-electrode 0–1),
session (duration, epochs), embeddings, labels, sleep summary, and history.
Interpreting the Output
Parse the JSON and translate metrics into natural language. Never report raw
numbers alone — always give them meaning:
DO:
> "Your focus is solid right now at 0.70 — that's flow state territory. Heart
> rate is steady at 68 bpm and your FAA is positive, which suggests good
> approach motivation. Great time to tackle something complex."
DON'T:
> "Focus: 0.70, Relaxation: 0.40, HR: 68"
Key interpretation thresholds (see references/metrics.md for the full guide):
- Focus > 0.70 → flow state territory, protect it
- Focus < 0.40 → suggest a break or protocol
- Drowsiness > 0.60 → fatigue warning, micro-sleep risk
- Relaxation < 0.30 → stress intervention needed
- Cognitive Load > 0.70 sustained → mind dump or break
- TBR > 1.5 → theta-dominant, reduced executive control
- FAA < 0 → withdrawal/negative affect — consider FAA rebalancing
- SNR < 3 dB → unreliable signal, suggest electrode repositioning
---
2. Session Analysis
Single Session Breakdown
npx neuroskill session --json # most recent session
npx neuroskill session 1 --json # previous session
npx neuroskill session 0 --json | jq '{focus: .metrics.focus, trend: .trends.focus}'Returns full metrics with first-half vs second-half trends ("up", "down", "flat").
Use this to describe how a session evolved:
> "Your focus started at 0.64 and climbed to 0.76 by the end — a clear upward trend.
> Cognitive load dropped from 0.38 to 0.28, suggesting the task became more automatic
> as you settled in."
List All Sessions
npx neuroskill sessions --json
npx neuroskill sessions --trends # show per-session metric trends---
3. Historical Search
Neural Similarity Search
npx neuroskill search --json # auto: last session, k=5
npx neuroskill search --k 10 --json # 10 nearest neighbors
npx neuroskill search --start <UTC> --end <UTC> --jsonFinds moments in history that are neurally similar using HNSW approximate
nearest-neighbor search over 128-D ZUNA embeddings. Returns distance statistics,
temporal distribution (hour of day), and top matching days.
Use this when the user asks:
- "When was I last in a state like this?"
- "Find my best focus sessions"
- "When do I usually crash in the afternoon?"
Semantic Label Search
npx neuroskill search-labels "deep focus" --k 10 --json
npx neuroskill search-labels "stress" --json | jq '[.results[].EXG_metrics.tbr]'Searches label text using vector embeddings (Xenova/bge-small-en-v1.5). Returns
matching labels with their associated EXG metrics at the time of labeling.
Cross-Modal Graph Search
npx neuroskill interactive "deep focus" --json
npx neuroskill interactive "deep focus" --dot | dot -Tsvg > graph.svg4-layer graph: query → text labels → EXG points → nearby labels. Use --k-text,
--k-EXG, --reach <minutes> to tune.
---
4. Session Comparison
npx neuroskill compare --json # auto: last 2 sessions
npx neuroskill compare --a-start <UTC> --a-end <UTC> --b-start <UTC> --b-end <UTC> --jsonReturns metric deltas with absolute change, percentage change, and direction for
~50 metrics. Also includes insights.improved[] and insights.declined[] arrays,
sleep staging for both sessions, and a UMAP job ID.
Interpret comparisons with context — mention trends, not just deltas:
> "Yesterday you had two strong focus blocks (10am and 2pm). Today you've had one
> starting around 11am that's still going. Your overall engagement is higher today
> but there have been more stress spikes — your stress index jumped 15% and
> FAA dipped negative more often."
# Sort metrics by improvement percentage
npx neuroskill compare --json | jq '.insights.deltas | to_entries | sort_by(.value.pct) | reverse'---
5. Sleep Data
npx neuroskill sleep --json # last 24 hours
npx neuroskill sleep 0 --json # most recent sleep session
npx neuroskill sleep --start <UTC> --end <UT… (nội dung đầy đủ có trong gói tải về)
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