Menü
Persist and recall state between skill invocations. Store analysis results, trade setups, session context, and carry them across conversations.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Basierend auf der SOC-Berufsklassifikation
Entry-point live-market scan. Returns current quote, H1/H4 regime, session state, and watch levels for a default watchlist (gold, US30, US500, US100, EURUSD, GBPUSD, BTCUSD, ETHUSD) — or any custom list. Uses the free yfinance path by default, MT5 if available. USE FOR - scan markets, what's moving, market overview, current prices, what's on the watchlist, show me the markets.
Entry-point ranked-setup feed. Runs the full pair-analyze pipeline against a watchlist and returns the top N highest-grade trade setups right now, sorted by confidence × R:R, with one-line rationale and a copy-pasteable trade plan. USE FOR - what should I trade, recommend trades, best setups, top picks, ranked opportunities, where's the edge.
Entry-point skill discovery. Given a keyword or task description, returns the shortest list of Tradecraft skills that match, with direct invocation recipes. No keyword = show the 5 main entry points. USE FOR - find skill, which skill, how do I, search skills, list skills, what can this do, find command.
Entry-point strategy selector. Lists the available trading strategies with a one-line when-to-use for each, plus a deep-dive drill-down by name. Routes to the right specialist skill (ICT/SMC, breakout, scalping, swing, trend-following, mean-reversion). USE FOR - which strategy, what strategies, strategy selector, strategy list, how should I trade, pick a strategy, ICT or SMC, breakout or trend.
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
Agentic storage architecture — persistent memory for AI agents using MCP, immutable versioning, sandboxing, and intent validation. Covers the stateless problem in LLM agents, RAG limitations (read-only), MCP protocol (JSON-RPC, resources, tools), storage safety layers, and agent file system design. Source: IBM Technology (Martin Keen), March 2026. Use this skill for "agentic storage", "agent memory", "persistent agent state", "MCP storage", "agent file system", "agent hard drive", "stateless agent problem", "agent work product", "immutable versioning", "agent sandboxing", "intent validation", "agent safety layers", "agent context window limits", "storage for AI agents", "agent persistence", "autonomous agent storage", "agent audit trail". Works with mcp-integration, trading-brain, agents, trade-psychology-coach.
| name | context-memory |
| description | Persist and recall state between skill invocations. Store analysis results, trade setups, session context, and carry them across conversations. |
| kind | meta |
| category | platform/routing |
| status | active |
| tags | ["context","memory","platform","routing"] |
| related_skills | ["skill-pipeline","smart-skill-router","workflow-builder"] |
You are a persistent state manager for multi-skill workflows. You save, retrieve, and inject context between skill calls.
{
"session": {
"date": "YYYY-MM-DD",
"account_size": null,
"risk_per_trade": null,
"active_pairs": [],
"current_regime": null
},
"analysis": {
"last_pair": null,
"last_fen": null,
"macro_bias": null,
"key_levels": {},
"active_setups": []
},
"trades": {
"open": [],
"pending": [],
"today_pnl": 0,
"today_trades": 0
},
"skills_run": []
}
/context-memory save key=value
/context-memory save account_size=10000
/context-memory save current_regime=trending_bullish
/context-memory save active_pairs=[EURUSD,XAUUSD,GBPUSD]
/context-memory load
/context-memory load account_size
/context-memory load analysis
/context-memory inject → /trading-brain
(automatically prefixes stored context before running the skill)
/context-memory clear session
/context-memory clear all
/context-memory summary
When chaining skills, automatically capture these outputs:
/market-regime-classifier → save current_regime/risk-and-portfolio → save position_size, max_risk/trading-brain → save active_setups, key_levels/trade-journal-analytics → save today_pnl, today_tradesWrite memory state to: ~/.claude/session_context.json
Read it at the start of each session for continuity.
When user says "remember that...", "use what you know about...", "apply previous analysis to...", activate this skill to retrieve and inject the relevant stored context.