'agent memory' 검색 결과

Error pattern tracking for AI agents. Detects corrections, escalates recurring mistakes, learns mitigations. The 'something's off' detector from the AI Brain series.

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Structured memory system for OpenClaw agents. Context death resilience (checkpoint/recover), structured storage, Obsidian-compatible markdown, local semantic search, and session transcript repair.

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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.

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Deliberate system-improvement loop — audit your own Claude Code setup (rules / memory / skills / MCP / agents / registry), evaluate incoming tools via /vet, adopt the worthwhile ones with discipline (backup → verify), and record every decision. Use when bringing in a tool/idea/collection to improve the setup, or when doing a tooling-improvement pass. Triggers — "upgrade the workflow", "audit our setup", "let's improve the tooling", "evaluate this for us", when handed a post/repo/reel with a tool.

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Comprehensive Mastra framework guide for building agents, workflows, tools, memory, workspaces, and storage with current APIs. Use for documentation lookup, API verification, TypeScript setup, common errors, migrations, and `mastra api` CLI tasks: inspect or call resources on local, Mastra platform, Trace Intelligence, or remote servers.

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Generate production-ready manga pages, chapter pages, covers, and panel sequences with strict recurring-character consistency. Use this when the user asks for a manga page, manga scene, chapter page, comic page, storyboard page, or character-consistent page generation. Before generating any page, inspect `img-memory`, create missing character sprites/reference sheets, make those images visible to image generation, then generate the final manga page.

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Use when claiming 'done', suggesting a commit, push, or PR — runs the evidence gate so completion claims come from fresh output in this message, not memory or earlier runs.

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Before stating any specific fact about an LLM provider's product — models, pricing, limits, context windows, SDK/API — for OpenAI, Gemini, Claude & others, verify against official docs, not memory.

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Use after an incident or outage is resolved — blame-free facilitation, root cause, corrective actions, memory write-back — even for a near-miss. Consumes the incident-commander skeleton.

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Construa, depure e otimize aplicativos com Claude API / SDK Anthropic. Aplicativos construídos com esta skill devem incluir cache de prompt. Também lida com migração de código Claude API existente entre versões de modelo (4.5 → 4.6, 4.6 → 4.7, substituições de modelo descontinuado). TRIGGER quando: código importa `anthropic`/`@anthropic-ai/sdk`; usuário solicita Claude API, SDK Anthropic ou Managed Agents; usuário adiciona/modifica/afina um recurso Claude (cache, thinking, compaction, tool use, batch, files, citations, memory) ou modelo (Opus/Sonnet/Haiku) em um arquivo; dúvidas sobre prompt caching / cache hit rate em um projeto SDK Anthropic. SKIP: arquivo importa `openai`/SDK de outro provedor, nome de arquivo como `*-openai.py`/`*-generic.py`, código agnóstico de provedor, programação geral/ML.

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Use when logging, scoring, and triaging a learner's persistent weak areas to drive intervention selection.

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Manus-style file-based planning for multi-step work. Keep task_plan.md, findings.md, progress.md in your run workspace so the filesystem is your working memory. Use for any research/build with 5+ tool calls. Adapted for OpenMark sub-agents from Ahmad's planning-with-files v3.0.0.

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Pull version-current Convex docs for the version this project uses — pin the installed version, fetch page-as-markdown or check node_modules types, freshness hierarchy — instead of writing a possibly-stale API from memory.

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Educational single-threaded TypeScript vanity address generator for Solana using @solana/web3.js with async iteration, event-loop yielding, streaming generator API, and best-effort memory zeroization.

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Secure Solana wallet generation using official Solana Labs libraries — Ed25519 keypairs, memory zeroization, vanity address generation, offline-only operation, and multi-language implementations (Rust, TypeScript, Bash).

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Defense-in-depth security across Rust, TypeScript, and Bash for the Pump SDK — cryptographic key handling, memory zeroization, secure file I/O, input validation, privilege management, dependency auditing, and a 60+ item security checklist.

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Onboard a new machine as a receive-only follower on a multi-machine agent network: it reads the shared vault, canon, skills and memory, runs nothing heavy locally (no RAG, reindex or GPU), and never receives executable hooks from the hub. Checklist-driven, with a verify step at each stage. Triggers: "/follower-onboard <machine>".

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Session stores conversation history for a specific session, allowing agents to maintain context without requiring explicit manual memory management.

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Metakognitive Injektoren und Selbstgesprächs-Strategien (Self-Talk, Metacognitive Auditing, Evaluator Hooks, Pre-Flight Checklists, State Persistence & Personas). Integriert Aktive Informationssuche (Systemgedächtnis Gardener & USMC), Rehearsal (Aktives Abrufen & Wiedergeben), Baddeleys Arbeitsgedächtnis (State + Hooks), Miyake Exekutivfunktionen sowie CBT/ACT therapeutische Strategien.

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Master the LangChain framework for building sophisticated LLM applications with agents, chains, memory, and tool integration.

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Expert guidance for LangChain and LangGraph development with Python, covering chain composition, agents, memory, and RAG implementations.

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Use tsift for token-efficient repository navigation, code search and reading, call graphs, diffs, logs, tests, session context, and workspace memory. TRIGGER: exploring or changing a codebase with tsift installed, or working on the tsift repo. SKIP: plain file-level glob, non-code web search. VERSION CHECK: compare `tsift --version` against tsift-version below before trusting any command text copied from this file.

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Complete WhatsApp management for OpenClaw agents: per-conversation memory (groups + DMs), unanswered message tracking, loop prevention, and multi-PA coordination. Use when: tracking conversation context, recalling past decisions, finding unanswered messages, or preventing echo/duplicate message loops.

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Evaluate everything the PA agent manages — tasks, skills, PA network health, billing, calendar connections, and memory quality. Use when: owner asks for an evaluation, wants to know what's working and what isn't, or requests a performance report. Combines supervisor status with quality scoring.

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