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概要と使いどころ
Judge performance or resource claims on real hardware: benchmark design or review, latency, throughput, memory or headroom numbers, and accept-or-reject decisions on optimizations. Not for refactors with no resource claim.
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 designing, reviewing, modifying, migrating, optimizing, securing, operating, troubleshooting, or decommissioning data architectures across data model exploration, SQL, ISO SQL conformance, NoSQL, vector, graph, document, time-series, NewSQL, search, in-memory, SQLite, CDC/Debezium, DBMS storage/query/recovery internals, database incident prevention, hardware acceleration, cache, big-data, lakehouse, and warehouse systems.
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 developing, reviewing, debugging, porting, or engineering Linux kernel device drivers, kernel modules, device tree bindings, bus clients, subsystem drivers, DMA/IRQ/memory paths, userspace interfaces, or hardware bring-up plans.
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。
Post-fix verification — re-scan the repo, gate on `--exploits weaponized --severity high`, recheck the specific CVE against the new installed version, write the verdict to `.vulnetix/memory.yaml`. Use when confirming a fix landed, validating a version bump did not introduce regressions, or producing a clean-scan attestation for compliance.
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 OpenVEX / CycloneDX VEX attestations from `.vulnetix/memory.yaml` triage decisions, optionally sign with cosign, optionally upload to Vulnetix and post to a GitHub PR. Use when documenting triage decisions for supply-chain consumers, attaching VEX to a CycloneDX SBOM, or satisfying customer attestation 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。
Non-streaming and streaming SSR, RouterClient/RouterServer, renderRouterToString/renderRouterToStream, createRequestHandler, defaultRenderHandler/defaultStreamHandler, HeadContent/Scripts components, head route option (meta/links/styles/scripts), ScriptOnce, automatic loader dehydration/hydration, memory history on server, data serialization, document head management.
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。
Break a feature or project area into frontier items and update `memory/PLAN.md`. Re-run to retire completed work, reorder priorities, or add new items.
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。
Author a completed-spec fixture — a seeded intent graph plus a believable four-phase interview transcript — for a brunch feature, so it can feed any downstream tooling that consumes a completed spec or dogfood the UI. Use when you need a real completed specification in .brunch/brunch.db for testing or demo: pick a feature from memory/SPEC.md (or a free description), choose a stress profile (coverage|clean), and produce a registered scenario seed + an interview-questions doc that match exactly.
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。
Define one thin vertical slice with target behavior, risks, and acceptance criteria. Use when scoping the next piece of work before building, or when a slice from `memory/PLAN.md` needs precise definition.
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。
Erkennt Aufträge, eine Regel- oder Gedächtnisdatei zu kürzen ("kürze meine CLAUDE.md", "MEMORY.md ist zu lang", "komprimiere die Doku, ohne Technik anzutasten", "diese Regeldatei wird über die Zeichengrenze abgeschnitten") und nutzt dafür das Modul paveman — ein deterministisches, modellfreies CLI-Werkzeug zum Kürzen von Prosa in Markdown-/Textdateien mit Trockenlauf als Standard, Rollback und strengem Schutz-Validator für Pfade, Überschriften und Code. Nutze diesen Skill bei Sätzen wie "kürze <Datei>", "diese Datei ist zu lang/wird abgeschnitten", "shrink this rule file", "komprimiere ohne Inhalt zu verändern" oder wenn eine Regel-/Gedächtnisdatei erkennbar an eine Zeichen- oder Zeilengrenze stößt.
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。
Erweitert automation-self-care um Letter Hooks, Preflight-Bootloader, Dokument-Traversierungsregeln und selbstheilende Prompt-Kontext- Anreicherung für KI-Agenten und CLIs ohne native, ereignisgetriebene JSON-Lifecycle-Hooks (wie Antigravity / Gemini CLI). Nutzen, wenn ein Agent Preflight-Regeln injizieren, vor Arbeitsbeginn Memory/Gardener durchsuchen, Verzeichnis-Dokument-Lesestrategien erzwingen (CLAUDE.md / AGENTS.md) oder Sidecar-Tasks dynamisch an Skills und Sicherheitsprotokolle routen soll.
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。
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.
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。
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。
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。
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。
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。