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Show your current knowledge state — what you know, what's decaying, study stats
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Connect a notification channel (Slack, Gmail, etc.) so Cognition can send you learning exercises throughout the day — even when your laptop is off.
Schedule learning exercises for the next 24 hours via Slack/Gmail. Runs at the end of every session so exercises arrive even when Claude Code is closed. The API decides WHEN and WHAT technique — you build the exercise and schedule delivery.
Send screen observations to the Cognition API as learning events. Transforms Screenpipe data into API event format.
Launch the Cognition GUI app. Opens the Electron window and connects Claude Code to it via WebSocket. Use this after /cognition:start or whenever you need the GUI.
Generate and deliver a learning exercise based on what the user is forgetting. Orchestrates different learning techniques.
Test if the user's confidence matches their actual knowledge. Use when calibration ECE is high or strategy is "overconfident".
| name | status |
| description | Show your current knowledge state — what you know, what's decaying, study stats |
TOKEN=$(cat ~/.cognition/token)
# Learner state (all concepts + recall probabilities)
curl -s -H "x-api-key: $TOKEN" \
"https://cognition-api.fly.dev/v1/learner-state?user_id=USER_ID"
# Recommendations (what needs attention)
curl -s -H "x-api-key: $TOKEN" \
"https://cognition-api.fly.dev/v1/recommendations?user_id=USER_ID&limit=10"
# Strategy signature (learner type)
curl -s -H "x-api-key: $TOKEN" \
"https://cognition-api.fly.dev/v1/strategy/signature?user_id=USER_ID"
# Calibration (confidence accuracy)
curl -s -H "x-api-key: $TOKEN" \
"https://cognition-api.fly.dev/v1/calibration/snapshot?user_id=USER_ID"
# Assessment report (mastery evidence)
curl -s -H "x-api-key: $TOKEN" \
"https://cognition-api.fly.dev/v1/assessment/report?user_id=USER_ID"
╔══════════════════════════════════════════════════╗
║ COGNITION STATUS ║
╠══════════════════════════════════════════════════╣
║ ║
║ Concepts tracked: 47 ║
║ Average recall: 74% ║
║ At risk (< 60%): 5 concepts ║
║ Strong (> 85%): 28 concepts ║
║ ║
║ LEARNING STYLE: stable_retriever ║
║ CALIBRATION: well-calibrated (ECE: 0.08) ║
║ ║
║ ── NEEDS REVIEW ────────────────────────────── ║
║ ⚠ React useEffect cleanup 43% 1.5d left ║
║ ⚠ SQL JOIN types 52% 3.0d left ║
║ △ Git rebase workflow 61% 5.0d left ║
║ △ Python decorators 64% 6.2d left ║
║ △ CSS Grid vs Flexbox 67% 7.1d left ║
║ ║
║ ── STRONGEST CONCEPTS ──────────────────────── ║
║ ✓ Python list comprehensions 92% ║
║ ✓ HTTP status codes 87% ║
║ ✓ JavaScript promises 86% ║
║ ║
║ ── TODAY'S STUDY ───────────────────────────── ║
║ Reviews completed: 8 ║
║ Accuracy: 87% ║
║ Concepts strengthened: 6 ║
║ ║
╚══════════════════════════════════════════════════╝
Fill in actual data from the API responses. Adjust the layout to fit the data.
If concepts are at risk, offer: "Want me to start a quick review? The most urgent concept is [X]."