メニュー
Detect and classify candlestick patterns from ingested OHLCV data
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | market-pattern |
| description | Detect and classify candlestick patterns from ingested OHLCV data |
| argument-hint | <symbol> [--period 1D] |
| allowed-tools | mcp__claude-flow__memory_search mcp__claude-flow__memory_list mcp__claude-flow__memory_store mcp__claude-flow__agentdb_pattern-store mcp__claude-flow__agentdb_pattern-search mcp__claude-flow__ruvllm_hnsw_route Bash |
Scan ingested OHLCV data for known candlestick patterns, classify them by type and reliability, and store for future reference.
When you need to identify candlestick patterns (doji, hammer, engulfing, head-shoulders, etc.) in market data. Requires data to be ingested first via market-ingest.
mcp__claude-flow__memory_search (or memory_list) on the market-data namespace to retrieve normalized OHLCV data for the symbol and period. The memory_* tool family routes by namespace; the agentdb_hierarchical-* family does NOT (it routes by tier), so use memory_* for namespaced reads.mcp__claude-flow__agentdb_pattern-store with type: 'market-pattern'. Don't pass a namespace arg — ReasoningBank routes it; on bridge unavailability the fallback writes to the reserved pattern namespace with controller: 'memory-store-fallback' (see ruflo-agentdb ADR-0001).mcp__claude-flow__memory_store --namespace market-patterns — this DOES respect the market-patterns namespace because memory_* is namespace-routed.npx @claude-flow/cli@latest memory search --query "bullish reversal patterns" --namespace market-patterns
npx @claude-flow/cli@latest memory store --key "pattern-AAPL-2026-05-04-doji" --value '{...}' --namespace market-patterns
One-command drift detection. Composes audit-list + oia-audit + audit-trend into a single primitive — finds the most recent audit in `metaharness-audit` namespace, runs a fresh audit against the current repo, diffs them via ADR-152 §3.1 similarity, and alerts when structural distance crosses `--threshold`. Iter 53 of ADR-150 deep integration.
ADR-152 — weighted similarity between two harness fingerprints (genome + score JSON). Returns overall score in [0,1] plus per-component breakdown (cosine over 9 numerics, categorical agreement over 4 enums, jaccard over agent_topology). Unblocks ADR-151 §3.2 Recommender, §3.3 Drift Detection, §3.5 Plugin Compat. Pure-TS, no `@metaharness/*` dep — preserves ADR-150's four architectural constraints.
Composite Phase-2 audit worker (ADR-150). Bundles harness oia-manifest + threat-model + mcp-scan into one timestamped audit record stored in the `metaharness-audit` memory namespace. Designed for cron-scheduled drift detection.
7-section repo readiness report from `metaharness genome <path>`. Returns repo_type / agent_topology / risk_score / mcp_surface / test_confidence / publish_readiness. Pure-read; degrades gracefully (ADR-150).
Static security scan of a harness's declared MCP surface via `harness mcp-scan <path>`. Reads `.mcp/servers.json` + `.harness/claims.json`. Pure-read, no dispatch. Exits 1 on findings at or above `--fail-on` severity.
Scaffold a custom AI agent harness via `metaharness new <name> --template <id> --host <id>`. Defaults to DRY-RUN (no writes) unless --confirm is passed. Refuses to write to the calling repo root or anywhere inside it. Honors ADR-150 architectural constraint + ruflo's "destructive-action confirmation" pattern.