「agent memory」の検索結果

Optimizes Atlassian Forge apps to reduce platform consumption and avoid unnecessary costs using Atlassian's "Optimise Forge platform costs" guidance. Use when the user asks to optimize Forge app costs, reduce Forge invocations, lower GB-seconds, reduce storage or log usage, tune memory, replace polling, improve scheduled triggers, reduce KVS writes, move work to the frontend, use bridge APIs, batch API calls, add caching, or evaluate Forge Remote trade-offs. By default, perform an audit first and offer to make the recommended changes after presenting the audit. Only modify files immediately when the user explicitly asks the agent to implement or apply optimizations.

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。

Reactive programming with RxJS - Observables, operators, Subjects, error handling, and memory leak prevention

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。

Client-side image handling - preview generation, Canvas API resizing, compression, EXIF orientation, format conversion, memory management with object URL cleanup

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。

React Native performance profiling, optimization, and monitoring - JS/UI thread analysis, re-render prevention, list optimization, image performance, bundle size, startup time, memory leaks, React Compiler, New Architecture benefits

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。

Redis in-memory data store patterns with ioredis and node-redis -- caching, sessions, rate limiting, pub/sub, streams, queues, transactions, cluster

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Use when generating or editing diagrams, charts, visual assets, posters, UI mockups, product images, infographics, academic figures, comics, avatars, storyboards, brand boards, or image-edit workflows, especially when exported PNGs need visual QA and bounded self-repair. Prefer deterministic Mermaid/SVG/HTML/canvas sources for text-heavy diagrams; use HTML technical diagrams for browser-ready system blueprints, architecture, deployment topology, agent runtime, memory flow, before-after architecture, workflow, sequence, data-flow, lifecycle, runbook, PII/data-lineage, and state-machine diagrams. Do not use for ordinary UI polish without generated imagery.

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 long conversations coherent — summarization checkpoints, entity tracking, topic stacks, and graceful context handoffs. Use when dialogues run long or span sessions and the agent keeps losing the thread.

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。

Feature discovery agent — mines project docs, memory, user feedback, and competitor gaps to surface the highest-leverage features to build next. Outputs a prioritized feature backlog.

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。

micro-ROS: agent, rclc client API, micro_ros_setup, custom transports, static memory.

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Read and reuse AI coding session context across Claude Code, Codex, Antigravity/agent hooks, Cursor adapters, and compatible AI tools. Use this skill whenever the user asks to read, inspect, resume, compare, or continue another session by name or session ID, asks what happened in the previous session, or starts a new session that should inherit the nearest prior context. The paired provider adapter automatically loads the nearest previous project session at startup and resolves explicit session-read requests.

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Comprehensive MCP server development guide covering FastMCP 2.14.3 features, Anthropic standards, ecosystem integration, and production deployment across all agentic IDEs

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Master AI-integrated development environments with comprehensive coverage of Windsurf, Cursor, Antigravity, Zed, Cline, and FOSS newcomers, including intelligent usage patterns, cost optimization, and the evolution toward fully agentic development

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。

Structured Zettelkasten workflow for AMD — observe, draft, enrich, retrieve, decide, preview, write, verify. Produces high-quality atomic knowledge cards with deliberate linking.

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Pre-compaction housekeeping. Walks a checklist (persistent memory updates, git hygiene, trash cleanup) plus an open-judgment audit, produces an SBAR with a go/no-go recommendation, and emits a copy-pasteable resume prompt for the post-compaction agent if work remains. Run this immediately before /compact.

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 AI-first interfaces that build ongoing relationships through memory, trust evolution, and collaborative planning, not just isolated screen interactions

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。

Implements the Active Learning Protocol (R3). Allows the agent to programmatically internalize lessons into MEMORY.md and generate structured "ask for help" requests.

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。

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.

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。

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.

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。

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.

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 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.

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。

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.

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 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.

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。