「setup memory」の検索結果

Build GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (v1.22.0+). Covers retriever selection (VectorRetriever, HybridRetriever, VectorCypherRetriever, HybridCypherRetriever, Text2CypherRetriever, ToolsRetriever), external vector DB retrievers (Weaviate, Pinecone, Qdrant), retrieval_query Cypher fragments, query_params, filters, GraphRAG pipeline wiring (GraphRAG + LLM + prompt), all LLM providers (OpenAI, Anthropic, Gemini/VertexAI, Bedrock, Cohere, Mistral, Ollama), embedder setup, index creation, token usage tracking, Cypher 25 SEARCH clause, and LangChain/LlamaIndex integration. Does NOT handle KG construction — use neo4j-document-import-skill. Does NOT handle plain vector search — use neo4j-vector-index-skill. Does NOT handle GDS analytics — use neo4j-gds-skill. Does NOT handle agent memory — use neo4j-agent-memory-skill.

日本語の概要は準備中です。原文の説明を表示しています。

First-run setup for the Mycelium plugin. Creates project-state directories (.claude/canvas, .claude/diamonds, .claude/memory, .claude/harness) and minimal starter files in the user's project. Optionally provisions opencode runtime support (a starter scaffold) when opencode is detected or requested. Idempotent — re-running on an initialized project is a no-op. Run this once after installing the Mycelium plugin and before invoking other skills.

日本語の概要は準備中です。原文の説明を表示しています。

Detects seven structural anti-patterns in Claude Projects that cause unpredictable output, ignored instructions, and degraded quality. Diagnoses Monolith, Orphan File, Echo Chamber, Phantom Conversation, Kitchen Sink, Misaligned Hierarchy, and Blurred Layers. Use when user says "what's wrong with my project," "Claude ignores my instructions," "diagnose my project," "why is output inconsistent," "review my project setup." Also trigger on symptom-phrased: "Claude doesn't follow my rules," "my instructions keep getting overridden," "my Project isn't behaving as designed." Use alongside rootnode-project-audit if available for deeper structural analysis. Activate whenever the user describes symptoms of unreliable, inconsistent, or degraded Claude Project output, even if they do not name a specific pattern. Do NOT use when the user's primary request is Memory-layer rebalancing (use rootnode-memory-optimization if available) or scoring a single prompt (use rootnode-prompt-validation if available).

日本語の概要は準備中です。原文の説明を表示しています。

Firmware development for the Waveshare ESP32-C6-Touch-LCD-1.47 board (ESP32-C6FH8, QFN32, 8 MB flash, SKU 31203 / 31201-M) — its 1.47" 172x320 JD9853 IPS panel, AXS5106L capacitive touch controller on I2C 0x63, QMI8658A IMU on I2C 0x6B, microSD/TF slot on the shared SPI2 bus, ETA6098 battery charger with VBAT sensing, USB-Serial-JTAG console, Wi-Fi 6/BLE/802.15.4 radio, and the ESP-IDF + PlatformIO setup around them. Use when working on this board: project setup, platformio.ini and sdkconfig, pin mapping and strapping pins, JD9853 bring-up, touch coordinates and calibration, LVGL memory budgeting, backlight PWM, TF card on the shared bus, battery voltage, flashing over Type-C, or debugging why something on the board does not work. This is NOT the non-touch ESP32-C6-LCD-1.47 (ST7789, 4 MB) — the two share a name and almost no pins.

日本語の概要は準備中です。原文の説明を表示しています。

Preventive hygiene audit of your own Claude Code configuration — memory files, project context (CLAUDE.md), rules, permissions, skills — a deterministic scan of sizes / broken links / stale entries / excessive permissions / junk + interpretation + targeted fixes by agreement. Keeps the setup from rotting before it breaks. Triggers — "check the system", "system health", "workflow hygiene", "what to clean up", "audit memory", "optimize the system".

日本語の概要は準備中です。原文の説明を表示しています。

Bootstrap full agent infrastructure for an existing, already-coded project without modifying a single line of source code. Surveys the repo, infers conventions from manifests, README, git history, and source samples, then generates the missing AGENTS.md, docs/architecture.md, docs/product-soul.md, ADR backfill, and seeded docs/memory/ files. Asks the user only about gaps the repo cannot reveal. Load when the user asks to "retroactive project setup", "backfill agent infrastructure", "bootstrap agents for this existing repo", "onboard agents to a legacy codebase", "set up agents without touching code", or "fill in missing agent context for this project".

日本語の概要は準備中です。原文の説明を表示しています。

Build, update, and query a persistent project knowledge graph from skills, memory, docs, and code structure — stdlib Python only, no external tools. Dual-mode: skill-library (agent-loom) or application (any consumer repo). Load when the user asks for a knowledge graph, project map, skill relationships, query the graph, update the graph, or trace how components connect. Auto-runs on memory-handoff and project-setup bootstrap. Also triggers on "build the graph", "what connects to X", "map this project".

日本語の概要は準備中です。原文の説明を表示しています。

画像の内容を質問したり、説明文を作ったりするために、LLaVAの導入と利用を支援します。画像を見ながら続ける対話や、画像付き文書の理解にも使えるスキルです。

• 写真の説明文を作りたいとき
• 画像内の物や場面について質問したいとき
• 画像について話せるチャットの試作

Bring what Claude Code or Codex already remembers or has configured for this user into Muse Code — their memory notes and their MCP servers — whenever the user mentions things Claude Code or Codex remembers or knows about them, an MCP tool or server they had there that is missing here, or asks to migrate, import, or copy that setup; call read_skill for bundled:migrate before reading any foreign file. Rules and skills are already covered by /rules import and `muse skills import --from claude|codex`; point there. Do NOT use for session transcripts (resume-claude or resume-codex for Claude Code/Codex continuation, including recovery of unfinished work with or without a handle; import for explicit /import requests or continuation from other agents or unnamed artifacts), for Muse settings unrelated to migration (manage-settings), or when Claude Code or Codex is only mentioned in passing.

日本語の概要は準備中です。原文の説明を表示しています。

Initialize a new MemPalace — guided setup for your AI memory palace with ChromaDB backend.

日本語の概要は準備中です。原文の説明を表示しています。

Recall protocol for MemPalace — search the palace before answering about past work, people, projects, or prior decisions. Apply when the user asks what was decided, what happened before, who someone is, what was discussed last time, or anything that may already be filed in their memory palace; or when mempalace-recall is invoked. Complements the mempalace setup skill and requires the mempalace-mcp server.

日本語の概要は準備中です。原文の説明を表示しています。

Add keyless GBrain memory to an existing agent, or connect a hosted brain while preserving identity and configuration

日本語の概要は準備中です。原文の説明を表示しています。

Top-level workflow skill for USD performance diagnosis and optimization. Use for slow loading, high memory, low FPS, or 'optimize my scene' requests; delegates auth/runtime setup to Phase 0 owners.

日本語の概要は準備中です。原文の説明を表示しています。

Show users how Continuous Claude works - the opinionated setup with hooks, memory, and coordination

日本語の概要は準備中です。原文の説明を表示しています。

Top-level workflow skill for USD performance diagnosis and optimization. Handles slow loading, high memory, low FPS, and broad scene-optimization requests; delegates auth/runtime setup to Phase 0 owners.

日本語の概要は準備中です。原文の説明を表示しています。

Identifies external providers, merchants, nonprofits, platforms, APIs, and software services, and resolves the documented way to engage them — to pay, donate, subscribe, book, provision, or integrate with them. MUST be used BEFORE web search, model memory, or any other directory/vendor-lookup skill for ANY request that requires selecting, finding, or engaging an external provider or organization — whether a specific one is named ("pay my Twilio bill"), implied ("donate to the Red Cross"), or only a category is stated ("set up a mailing client", "I need a database", "find me a CRM"). Directory supplies verified recipients and their documented payment or engagement path. Results are ranked by agent-readiness (how reliably an agent can complete the interaction), relevance and popularity. Do not treat this as a search-only tool. Examples: "setup a database", "find hosting", "pay X", "use Twilio", "donate $50 to the Red Cross", "book a table at Y", "subscribe to a CRM".

日本語の概要は準備中です。原文の説明を表示しています。

Automates pre-development workflow for large-scale complex tasks. Use when the user mentions "rewrite", "migrate", "overhaul", "refactor entire project", "transform", "rebuild in [language]", "spec-driven", or describes any large-scale project transformation that requires planning before coding. Also triggers on Chinese keywords: "改造", "重写", "迁移", "重构", "大规模", "规范驱动". Performs full project analysis, task decomposition, documentation generation, project-level instruction and native memory surface resolution, progress tracking setup, and then executes the plan within the same session.

日本語の概要は準備中です。原文の説明を表示しています。

Manages project directory setup and artifact organization. Use when starting a new project, resuming an existing one, or when a PLAN.md needs to be associated with a project directory. Creates the project folder structure (specs/, scripts/, notebooks/, manifests/, agent_memory/) and resolves project naming.

日本語の概要は準備中です。原文の説明を表示しています。

Optimize Flutter widget rebuilds, memory usage, rendering, and scrolling performance. Use when diagnosing jank, reducing rebuilds, or improving list performance—not performance tests, monitoring setup, or API optimization.

日本語の概要は準備中です。原文の説明を表示しています。

Use when you need to set up Java application profiling to detect and measure performance issues — including trusted preinstalled async-profiler v4.x setup, problem-driven profiling (CPU, memory, threading, GC, I/O), interactive profiling scripts, JFR integration with Java 25 (JEP 518, JEP 520), or collecting profiling data with flamegraphs and JFR recordings. This should trigger for requests such as Improve the code with profiling; Apply Profiling; Refactor the code with profiling; Add profiling support; Collect JFR or async-profiler data for Java performance. Part of Plinth Toolkit

日本語の概要は準備中です。原文の説明を表示しています。

Cross-agent self-inspection of your AI-agent stack. Audits skills, MCP servers, hooks, plugins, commands, credentials, and memory files across Claude Code, Codex, OpenClaw, and NanoClaw. Produces a structured inventory and narrative briefing with cross-ecosystem risk analysis. Use when the user asks to audit their own setup, check what they have installed, review their agent stack security posture, or understand cross-tool interactions. Use when a user has accumulated skills/plugins/MCP servers over time and wants visibility into their attack surface. Use after installing new skills or plugins. Do NOT use for vetting external code before install (that is repo-forensics). Do NOT use for incident response during active attacks. Do NOT use for fixing or patching vulnerabilities (forensify is read-only).

日本語の概要は準備中です。原文の説明を表示しています。

Test native, React Native, hybrid, and Flutter mobile apps with Appium 3.x, Detox, Maestro, and Patrol. Covers device farm setup (BrowserStack, Sauce Labs), gesture simulation, deep link and cold-start testing, push notifications, biometric (Face ID) auth, offline/poor-network simulation, and iOS/Android permission dialog handling. Use when: "mobile test," "Appium," "Detox," "Maestro," "Patrol," "Flutter test," "iOS test," "Android test," "device farm," "deep link," "biometric," "Face ID," "permission dialog," "React Native test." Not for: device/browser matrix strategy in the abstract — use cross-browser-testing; app startup/memory/battery profiling depth — use performance-testing; mobile screenshot diffing — use visual-testing. Related: ci-cd-integration, cross-browser-testing, performance-testing, test-data-management, test-reliability.

日本語の概要は準備中です。原文の説明を表示しています。

Neo4j Graph Data Science (GDS) embedded plugin via Python client or Cypher — covers graphdatascience client 2.x, GraphDataScience, gds.graph.project.native, gds.graph.project.cypher, snake_case endpoints, graph catalog operations, stream/stats/mutate/write modes, memory estimation, PageRank, Louvain, WCC, FastRP, KNN, Node Similarity, ML pipelines, and cleanup. Use for Aura Pro, self-managed, local, or offline Neo4j DBMS with the GDS plugin installed. Does NOT cover Aura Graph Analytics GDS Sessions, AuraGraphDataScience, GdsSessions, gds.graph.project.remote, or AuraDB Cypher API projection/session management — use neo4j-aura-graph-analytics-skill. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT cover driver setup — use neo4j-driver-python-skill or other driver skill.

日本語の概要は準備中です。原文の説明を表示しています。

Product-only Red Team audit of the FMT/IWE platform: source, manifests, setup/update paths, CI and release provenance, agent permissions and memory, hooks, runtime, roles, schedulers, Day Open/Close, and regression claims. Use before merging or publishing a release, after changes to updater/runtime/security behavior, or when verifying a reported platform defect. Excludes real consumer workspaces and personal customizations; use repository-owned code and synthetic disposable fixtures only.

日本語の概要は準備中です。原文の説明を表示しています。