1,089 件 ・ 関連度順
概要と使いどころ
Persistent per-project memory for Claude Code. Auto-loads project context on session start, tracks sessions with git activity, and writes to native memory. Commands run deterministic Node.js scripts — behavior is consistent across model versions.
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。
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
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。
Turn a one-line objective into a step-by-step construction plan for multi-session, multi-agent engineering projects. Each step has a self-contained context brief so a fresh agent can execute it cold. Includes adversarial review gate, dependency graph, parallel step detection, anti-pattern catalog, and plan mutation protocol. TRIGGER when: user requests a plan, blueprint, or roadmap for a complex multi-PR task, or describes work that needs multiple sessions. DO NOT TRIGGER when: task is completable in a single PR or fewer than 3 tool calls, or user says "just do it".
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。
Capture architectural decisions made during Claude Code sessions as structured ADRs. Auto-detects decision moments, records context, alternatives considered, and rationale. Maintains an ADR log so future developers understand why the codebase is shaped the way it is.
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。
Patterns for controlling REPL sessions (Python, IPython, Node.js, Ruby, etc.) via terminalcp
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-stack security review — auditing vulnerabilities across infrastructure, smart contracts, CI/CD pipelines, and AI agent systems, plus auth/sessions/crypto and validating user input at API and infrastructure boundaries. Triggers on mentions of "vulnerability", "pentest", "OWASP", "access control", "injection", "CSRF", "JWT", "smart contract audit", "supply chain", "OIDC", or any review of security-sensitive code paths spanning more than one layer. For PII sanitization see [security](../security/SKILL.md).
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。
Give an AI agent its own real browser over MCP tool calls - launch, navigate, click, fill, screenshot, extract text, run JS - with a kernel-level real-device fingerprint and a persistent profile, so the session stays logged in between runs and pages see one coherent device instead of a headless build. No Playwright or SDK code to write. Use when an agent should operate a site itself, when a computer-use / browser-use setup needs a captured real fingerprint rather than a synthetic one, when agent sessions keep losing their login, or when comparing hosted agent-browser services. Also for 'MCP browser', 'browser MCP server', 'let my agent browse the web', 'agent browser control', 'browser-use MCP', 'computer use browser', 'Browserbase alternative', 'Steel browser alternative', 'headless browser detected'. Node (npx) or Python; Windows x64, macOS Intel + Apple Silicon, Linux x64 / arm64. SDK and REST reference is anti-detect-browser; account isolation is multi-account-isolation.
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。
Drive Chromium from standard Playwright APIs with a real-device fingerprint applied in the kernel, one persistent isolated profile per identity, and a per-profile proxy whose exit IP sets timezone and WebRTC - JavaScript (npm 'anti-detect-browser') or Python (PyPI 'antibrow'). Use when sessions must stay logged in across runs and stay separate, when a scraper or agent is blocked by an incoherent headless fingerprint, when checking ads or pricing from another region, when a page must be reached as a phone rather than a desktop, when automation mints a profile per task, when running several of your own accounts from one machine, or when testing how your own bot detection scores a real device. Also for 'antibrow', 'fingerprint browser', 'multi-account browser', '防关联', '多账号', '安卓模拟', 'Android profile', 'mobile fingerprint', 'temporary profile', 'CreepJS', 'residential proxy', 'browser-use', 'crawl4ai'. MCP control is browser-mcp-agent; isolation is multi-account-isolation.
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。
Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.
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。
Design, implement, or review security-sensitive dygo behavior across auth, sessions, Permissions, secrets, APIs, database writes, files, Jobs, and Studio. Use when security boundaries are a primary concern.
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。
Hardens code against vulnerabilities. Use when handling user input, authentication, data storage, or external integrations. Use when building any feature that accepts untrusted data, manages user sessions, or interacts with third-party services.
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。
When agent sessions generate millions of tokens of conversation history, compression becomes mandatory. The naive approach is aggressive compression to minimize tokens per request.
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。
Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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。
Review and merge student exercise PRs during TP sessions. Arguments: <repo-url> [--class <class-id>] [--timeslot <HH:MM-HH:MM>] [--dry-run]
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。
Auto-activate for Google ADK, LlmAgent, Runner, SQLSpecSessionService, google-genai, AgentRuntime, SpecTree, DynamicWorkflow, FunctionTool, or SSE agent chats. Not for offline ML training.
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。
Persistent vector memory for Claude Code via LanceDB. Use when: remembering across sessions, storing lessons, recalling past decisions, maintaining context continuity. Tools: memory_store, memory_recall, memory_update, memory_forget, memory_merge.
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。
Continuous learning framework — learn from work, organize knowledge, build feedback loops. Use when: recording lessons, organizing knowledge, or setting up learning systems that persist across sessions.
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。
Session handoff — compress current context into a structured prompt for seamless continuation in a new session. Use when: switching sessions, running low on context, or needing to hand off work.
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 this skill whenever a task involves running parallel work on a git repository without conflicts — e.g. "fix this bug while I keep working on my feature", "run Claude on two branches at once", "work on this task in isolation", "create a throwaway branch for this experiment", or anything where two agents or sessions might edit the same files. Also trigger when the user asks to use worktrees directly, or when an agent needs its own isolated checkout so it can work without disturbing the main branch. Even if the user just says "do this in parallel" or "don't mess up my current work", consider worktrees.
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。
Stores a persistent memory or learning with `bd remember` so it survives across sessions. Use when the user invokes `/bdr` or `$bdr`, or asks to remember, note, or persist an insight in a Beads workspace.
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。
Browser automation CLI for AI agents using agent-browser. Use for navigating websites, clicking/filling pages, screenshots, data extraction, web app testing, exploratory QA, dogfooding, Electron apps, Slack automation, Vercel Sandbox browser runs, AWS AgentCore cloud browsers, auth-heavy flows, and long autonomous browser sessions. Prefer over generic browser tools when a fresh/tool-managed Chrome session is fine. NOT for the user's real Chrome cookies/profile (see mk:chrome-profile); NOT for reusable Playwright specs (see mk:qa-manual).
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。
On explicit /homework invocation, analyze the current and linked previous sessions, extract mistakes (찐빠), and report them via omcustom-feedback with a confirmation gate. Auto-activation on session cleanup/session-end signals is OPT-IN (default OFF) — requires an explicit project/user directive. Use when explicitly auditing recent work for harness gaps.
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。
Persistent, adaptive vector memory for agents on a ruOS desktop — a Rust-native vector database with local semantic embeddings, HNSW retrieval, and graph relationships. Use to remember and recall across sessions with no database server or API key.
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。
Store and semantically search agent memory with ONNX vector embeddings on a ruOS desktop, using the Ruflo CLI. Use to persist patterns/decisions across sessions and recall them by meaning rather than exact key.
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。