572 件 ・ 関連度順
概要と使いどころ
Build stateful AI agents using the Cloudflare Agents SDK. Load when creating agents with persistent state, scheduling, RPC, MCP servers, email handling, or streaming chat. Covers Agent class, AIChatAgent, state management, and Code Mode for reduced token usage.
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。
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
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。
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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。
Maintain host-independent persistent runtime state, its reusable directory parser, encrypted records and generated keys, portal and portal-free OAuth sessions, refresh/OIDC replay history, local identity epochs, restart E2E tests, and embedding lifecycle contracts.
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。
Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware: breaks down per-person contributions with praise and growth areas.
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 and operate a complete, brand-neutral Reddit intelligence system with approved read-only monitoring, grouped keyword rules, evidence-backed AI scoring, a persistent opportunity bank, dashboard review, urgent-alert and weekly-digest previews, content briefs, and human-only response drafts. Use for "reddit intelligence", "reddit monitor", "reddit listener", "watch subreddits", "find reddit opportunities", "content ideas from reddit", "community listening", or setting up this workflow for a client or brand.
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-use is an open-source Python framework for letting AI agents interact with websites through a real browser. It supports local execution, optional cloud browsers, custom tools, and a CLI for persistent browser 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。
Browserless turns Chrome, Firefox, and WebKit into a remote browser service you can self-host or consume as a managed platform. It gives automation stacks a stable WebSocket and REST surface for screenshots, PDFs, scraping, persistent sessions, and debugging without hand-managing browser fleets.
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。
Convert a book or long document into a reusable AI mentor with source-grounded lessons, guided practice, citations, and persistent learning records.
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。
5-phase repeatable structure for autonomous agent sessions: context-load, tiered work-selection, coordination claim, execute, and persist-learning. Prevents duplicate work across concurrent sessions and ensures every run produces durable artifacts. Runtime-agnostic — Claude Code, gptme, Codex, or any persistent-workspace agent.
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 Agent QA's CLI and MCP server to author, validate, run, debug, and triage natural-language web and mobile regression tests with persistent test memory and reviewable run evidence.
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。
Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.
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。
host chinese call of cthulhu and similar investigative tabletop rpg sessions as kp/keeper. use when the user asks to start, continue, simulate, or play a coc scenario, wants chatgpt to be kp, asks for preset investigator cards, npc teammates, dice checks, horror investigation pacing, solo/co-op tabletop roleplaying, or persistent pre-session prep/project folders for a campaign. ask only the minimum setup questions: whether the user wants a custom investigator persona and how many npc teammates; otherwise handle scenario selection, character card creation, npc teammates, dice, pacing, narration, and campaign notes automatically.
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。
Guided project onboarding for new codebases. Helps agents understand project structure, build systems, test commands, and development workflows by creating persistent knowledge memories.
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。
Manus-style file-based planning for complex tasks. Use task_plan.md, findings.md, and progress.md to maintain persistent context. Use for multi-step tasks, research, or work spanning many tool calls.
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。
Entity and relation tracking skill using MCP memory server patterns and local knowledge graph storage. Build persistent knowledge graphs of entities, relationships, and observations across agent sessions. Covers the MCP memory server (@modelcontextprotocol/server-memory), local JSON-based graphs, and entity-relation querying patterns for long-running agents.
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。
Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
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Process unhandled Slack messages as Claudicle with persistent memory. Loads user models and soul state, posts terminal-styled thinking messages, generates cognitive-step responses, updates memory based on mentalQuery decisions. Requires Session Bridge listener running.
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Diagnoses and fixes Claude behavioral issues in system prompts and Projects using tested countermeasure templates. Use when "Claude is too verbose," "keeps hedging," "agrees with everything," "claims it did something it didn't," "won't use a tool," "fix Claude's output," "tune Claude's behavior," "Claude ignores my preferences," "adds unsolicited disclaimers," "uses too many lists." Covers ten tendencies: agreeableness (output-content + persistent-preference), hedging, verbosity, list overuse, fabricated precision, over-exploration, tool miscalibration (over- and under-triggering), LaTeX defaulting, editorial drift, self-referential fabrication. Also use when auditing a system prompt for behavioral calibration or recalibrating a pre-4.7 prompt, and when users describe recurring output problems without naming a tendency. Do NOT use for scoring a prompt's overall quality — 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。
Run the memex session-init ritual at the start of a fresh session: load the bias-log, read the persistent-self trail in order, run the verification scoreboard, and surface the next slice from the docs. Use at the very start of any session that operates on the memex repo, when reconstructing context before doing work, or when an interrupted session needs to re-orient. NOT the `memex init` CLI command (which initializes the store/db) — this is the reconstruct-context ritual.
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-session shared memory for agents. Use at session start to load the persistent bias-log via `mcp__memex__recent_observations`, mid-session to search prior context with `mcp__memex__search`, and immediately when a bias surfaces to log a new `observation` via `mcp__memex__add`. The six-layer reconstruction trail (raw → embedded → indexed → graphed → curated → reflexive) means memex stores facts AND the agent's own reasoning patterns across sessions. Prefer querying memex before re-deriving prior architectural decisions; re-derivation is itself evidence that the trail is incomplete.
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。
Organize, extract, prune, and verify Claude Code persistent memory files. Covers MEMORY.md as a concise index, topic extraction to dedicated files, staleness detection, accuracy verification against project state, the dual 200-line / 25KB load cap, and reachability of topic files from the index. Use when MEMORY.md is approaching either load cap, after a session produces durable insights worth preserving, when a topic section has grown beyond 10-15 lines and should be extracted, when project state has changed and memory entries may be stale, or before and after rewriting the index so that no topic file loses its only pointer.
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Use for Desktop Commander MCP capabilities — persistent shells and REPLs, long-running processes, filesystem beyond the workspace, structured files (.xlsx, .docx, .pdf, images) and large local data files such as CSVs, ripgrep search at scale, SSH, or cross-turn state.
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。
SurrealFS virtual filesystem for AI agents. Rust core + Python agent (Pydantic AI). Persistent file operations backed by SurrealDB. Part of the surreal-skills collection.
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。