「memo」の検索結果

Query Sentry issues, events, releases, replays, and org/project metadata via REST API. Use when the user wants to diagnose a production error, pull stack traces, list recent issues, inspect a release, or fetch event data programmatically — prefer this over asking for UI screenshots or guessing from 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。

Collective research memory for AI coding agents — search prior research before hitting the web, save findings back to the shared cache, view karma stats. Use when the user asks a library/API/framework question, before running WebSearch/WebFetch, or after deep web research so the next agent doesn't repay the cost. Talks directly to the hosted MCP endpoint via JSON-RPC — no local MCP server required.

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。

Reimagine a supplied photo as a tactile fuse-bead mosaic keepsake on a spacious editorial canvas. Use for 拼豆纪念画、照片拼豆效果、fuse bead photo art or perler-style visual mockups, not exact craft patterns or bead-count charts.

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 findings into a defensible intelligence product — BLUF key judgements, standardised estimative probability language, per-claim sourcing with timestamps and archived copies, separated observation, inference and assessment,… Use when writing an intelligence report, due-diligence memo, evidence pack or executive summary, or when asked to write up an investigation so it survives challenge

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。

Get a second opinion from an external LLM at three checkpoints: T1 is the plan valid, T2 which path at a fork, T3 finish plus a QA breaker that tries to break the result. One structured move per exchange (PROPOSE, COUNTER, VERIFY, ACCEPT, BLOCK) with memory across turns, and every exchange mirrored into a human-visible channel. Supports a multi-vendor panel instead of a single reviewer. Triggers: "/secondop", "get a second opinion", "run the review panel".

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。

Route a new rule, preference or policy edit into every home it belongs in (always-loaded canon, memory, the behavioral codex, a skill, a hook) and leave a trace in the always-loaded layer so parallel sessions pick it up on their own. Flow: dedup recall, classify by form, write to all homes, back up, report. Triggers: "/intake", "record this rule", "route this to its homes".

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。

Recover a fleet whose machines cannot see each other over the file-sync network: establish ground truth at the hub from the live sync API rather than memory or one peer's claim, publish the hub's verified device id over the messaging rail, and walk each disconnected peer through re-pairing. Triggers: "/raise-sync", "sync is down", "machines cannot see each other".

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。

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>".

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。

Print a ready-made /compact line in a canonical handoff format, so the operator pastes it as the next message and shrinks working memory without losing the thread. Use at the end of a long session. Triggers: "/cc", "compact", "finish via 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。

Decision protocol for strategic work: recall the knowledge vault, run a gap analysis, emit a deep-research prompt for external tools, then synthesize the returned reports into a decision memo. Use before any new product, feature, market, pricing, GTM or architecture call, where local recall alone is not enough. Triggers: "/alfa-search-recall-deepresearch", "alpha protocol", "R+DR".

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。

Restructure an always-loaded rules file such as CLAUDE.md or MEMORY.md: build a top block of key rules plus numbered categories, move rule bodies verbatim with a script that proves zero byte loss, fold heavy mechanics into trigger-plus-pointer form, then guards, a canary window and fleet rollout. For scheduled maintenance, not ad-hoc trimming. Triggers: "/canon-revision", "revise the canon".

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 a website needs a strong visual point of view, distinct concept routes, composition, typography, color/materiality, imagery direction, spatial rhythm, or a memorable signature idea.

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 meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.

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。

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.

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 an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.

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。

Route a goal through acc's scored-memory loop via acc_act(runtime="solve"); deliberate any returned brain_frame and submit via continue.

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 the user asks to "codify how our founder sounds", "build a founder voice dossier", or "set our content pillars"; runs an 80%-extraction interview over the user's OWN posts, emails, and decks (never competitor scraping, never an invented persona) and produces the versioned voice record — a per-platform register map (incl. 小红书/微信公众号), banned phrases, per-context disclosure lines (the ECHO C2 upstream), a few-shot bank built exclusively from own posts, and 3-5 content pillars with Estimated %-allocations — submitted via memory/events/channels.ndjson for channel-registry to store as voice-dossier.md, the record every Craft-phase skill reads first. Not for the brand-level voice canon — use brand-language-codifier; not for audience/persona research — use audience-mapper. 声音档案/品牌语气/创始人语气/内容支柱/披露声明

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 the user asks to "plan launch pricing", "design pricing tiers / packaging", or "set up a launch discount / early-bird offer"; produces a launch pricing and packaging plan — tier structure and naming, a value-to-price map aligned to the message house, a launch-offer ladder with a true deadline reason, beta / early-adopter pricing with a post-launch graduation path, and guarantee / refund terms — with every price claim and offer term submitted to memory/events/claims.ndjson. Not for the canonical offer / claim record — use offer-claims-registry; not for paid-newsletter subscription economics — use newsletter-monetization-planner; not for ad bidding — use bid-strategy-planner. 发布定价/梯度打包/早鸟优惠/保证设计

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 long-lived objects (caches, listeners, singletons) that capture an entire enclosing scope via closures/environment capture, keeping large arrays or buffers alive, and proposes copying only the needed fields.

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。

Background processing and heavy computations using Dart Isolates with Isolate.run(), compute() function, and platform channels. Use this skill when performing CPU-intensive operations without blocking UI (image processing, data parsing, encryption), implementing background tasks that prevent jank or frame drops, handling large file operations (JSON parsing, database migrations), running parallel computations, fixing UI freezes caused by main thread blocking, using compute() for one-off background work, creating long-lived Isolates with ReceivePort/SendPort, implementing multi-threaded algorithms, debugging isolate communication issues, or preventing memory leaks from unclosed ReceivePorts. Covers isolate spawn, message passing, ReceivePort cleanup (CRITICAL for leak prevention), SendPort communication patterns, error handling, serialization rules, and performance optimization for compute-heavy operations.

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Integrates Google Mobile Ads (AdMob) into Flutter using google_mobile_ads v7.x with Banner, Interstitial, Rewarded, and Native ad formats. Use this skill whenever implementing app monetization, adding AdMob ads to Flutter, fixing ad loading or display errors, managing ad lifecycle (preload/dispose), preventing memory leaks from undisposed ads, handling GDPR/ATT consent flows, troubleshooting AdMob dashboard integration, or any time the words 'AdMob', 'google_mobile_ads', 'banner ad', 'interstitial', 'rewarded ad', 'native ad', or 'ad monetization' appear in the request. Supports Android (GMA SDK 24.9+) and iOS (GMA SDK 12.14+).

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 local UI state and side effects in Flutter using the flutter_hooks package (v0.21.x) with HookWidget, useState, useEffect, useMemoized, useAnimationController, and custom hooks. Use this skill when replacing StatefulWidget boilerplate with hooks, reusing stateful UI logic across widgets, managing controller lifecycles (TextEditingController, AnimationController, ScrollController) without manual dispose, implementing countdown timers or subscriptions in widgets, mixing flutter_hooks with Riverpod via HookConsumerWidget, or any time the words 'flutter hooks', 'useEffect', 'useState', 'HookWidget', or 'flutter_hooks' appear in the 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。

Expert-level guidance for Flutter production applications: architecture decisions (Clean/Layered/Hexagonal/Feature-First), advanced state management (BLoC/Riverpod/GetX), performance optimization (eliminating jank, memory profiling, reducing rebuild overhead), code review with design pattern enforcement, scalability assessments, native platform integration (MethodChannel/EventChannel/FFI), complex UI challenges (custom render objects, slivers), testing strategies (unit/widget/integration/golden), CI/CD pipeline architecture, build optimization, and accessibility compliance. Triggers: 'architecture decision', 'design pattern', 'performance issue', 'code review', 'production problem', 'scaling concerns', 'best practices', 'technical debt', 'refactoring strategy'. Essential for complex enterprise apps, critical production debugging, architectural refactors, or when choosing between competing technical approaches.

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。

Hive CE (Community Edition v2.19.x) NoSQL object database for Flutter providing blazing-fast key-value and object storage with TypeAdapters. Use this skill when implementing offline-first architecture, high-performance local data caching, NoSQL document-style object stores, custom TypeAdapter serialization for complex objects, lazy loading boxes for memory efficiency, encrypted boxes (HiveAES encryption), database compaction for size optimization, storing large datasets without SQL schema overhead, implementing local-first sync patterns, or migrating from SQLite to NoSQL. Supports primitive types, custom objects, lists, and maps. Ideal for apps requiring ultra-fast read/write operations (microsecond latency), object persistence without ORM complexity, or local-first data architecture.

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。