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概要と使いどころ
Dolt-powered issue tracker for multi-session work with dependencies and persistent memory across conversation compaction. Use when work spans sessions, has blockers, or needs context recovery after compaction. Trigger with "create task", "what's ready", "track this work", "resume after compaction". Make sure to use this skill whenever managing multi-session work, tracking dependencies, or recovering context.
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 file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; Gemini lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. The session-end hook reports status only; it does not request continuation or run commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ 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。
Planificación persistente basada en archivos para tareas multipaso de agentes de IA. Mantiene task_plan.md, findings.md y progress.md en disco; los hooks del ciclo de vida inyectan contexto seleccionado de planificación del proyecto. La recuperación automática solo lee los archivos de planificación del proyecto. session-catchup.py --metadata, solicitado de forma explícita, puede inspeccionar metadatos locales de sesiones del mismo proyecto; --replay puede emitir extractos limitados y enmarcados con nonce. El modo con gate opcional solo puede solicitar que el host continúe si este lo admite y nunca ejecuta comandos declarados en Markdown. El skill no tiene ninguna ruta de carga por red. Úsalo para investigación o trabajo que requiera 5 o más llamadas a herramientas.
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 file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. Optional gated mode can request continuation only when the host supports it and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ 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。
Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; Kiro skill instructions and steering state read selected project planning context. Recovery reads project planning files and their timestamps only, not agent transcript stores. This adapter registers no Stop hook, never requests continuation, and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ 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。
Persistente dateibasierte Planung für mehrstufige Arbeit mit KI-Agenten. Hält task_plan.md, findings.md und progress.md auf dem Datenträger; Lebenszyklus-Hooks speisen ausgewählten Planungskontext des Projekts ein. Die automatische Wiederherstellung liest nur die Planungsdateien des Projekts. Nur ein ausdrücklicher Aufruf von session-catchup.py --metadata darf lokale Sitzungsmetadaten desselben Projekts prüfen; --replay darf begrenzte, nonce-gerahmte Auszüge ausgeben. Der optionale Gate-Modus kann nur bei Unterstützung durch den Host eine Fortsetzung anfordern und führt niemals in Markdown angegebene Befehle aus. Der Skill hat keinen Netzwerk-Uploadpfad. Verwenden für Forschung oder Arbeit mit mehr als 5 Tool-Aufrufen.
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 file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; agent instructions read selected project planning context when invoked. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. This adapter registers no lifecycle or Stop hook, never requests continuation, and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ 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。
Diagnoses and resolves Filestore client mount failures on Google Cloud, permission errors (EACCES), and network timeouts (ETIMEDOUT). Use when an NFS mount hangs or fails from a Compute Engine VM, GKE pod, Cloud Run service, or Vertex AI workload, when `mount.nfs` reports "Connection timed out" or "access denied by server", when checking whether VPC ingress firewall rules or `nfsExportOptions` allow a client IP, or when a previously working Filestore share suddenly stops mounting after an administrative change. Don't use for Cloud Storage (GCS) buckets, Persistent Disk, or Cloud NetApp Volumes, and don't use for Filestore capacity scaling or backup and export-policy auditing.
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。
Stores, retrieves, and manages data as objects in Cloud Storage on Google Cloud (also known colloquially as GCS) buckets. Use when you need to interact with Cloud Storage — set up a Storage MCP server (remote or local Toolbox), create or configure buckets, upload, download, stream, or transfer data, organize objects with folders, generate signed URLs, control access (IAM, ACLs, public access prevention), set storage classes (Standard, Nearline, Coldline, Archive), manage lifecycle and cost, protect data (versioning, CMEK, retention, Bucket Lock, holds, soft delete), host static websites, trigger Pub/Sub notifications, mount buckets (gcsfuse), or optimize performance. Covers gcloud storage / gsutil, JSON/XML APIs, client libraries, Terraform, and Cloud Storage MCP servers. Don't use for non-Storage MCP servers, block storage (Persistent Disk), BigQuery, or databases (Cloud SQL, Spanner, Bigtable, Firestore).
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。
Audits Filestore instances on Google Cloud across projects for disaster recovery readiness (missing or stale backups), security access governance (overly permissive NFS export rules, 0.0.0.0/0 exposure, missing ROOT_SQUASH), and reliability compliance (Physical Zone Isolation PZI and Physical Zone Separation PZS). Use when assessing storage health posture, auditing NFS export permissions, identifying unprotected file shares, or validating zone failure domains. Don't use for Cloud Storage buckets, Persistent Disk, or NetApp Volumes.
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。
Inspects, searches, and reads files and POSIX metadata on Filestore (NFS) instances on Google Cloud without local NFS client packages or root privileges. Use when browsing Filestore shares, searching files, reading remote logs, or inspecting file attributes; don't use for Cloud Storage buckets, Cloud NetApp Volumes, Persistent Disks, or modifying/deleting files.
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。
Inspects Filestore capacity and utilization on Google Cloud, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization). Use when monitoring Filestore instance headroom, resizing instance shares, configuring automated growth/shrink thresholds (custom thresholds apply globally across projects in session memory), or preventing out-of-space outages. Don't use for Cloud Storage (GCS) buckets, Persistent Disk block storage, or NetApp Volumes.
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 GKE storage, including PVCs, PersistentVolumes, and Filestore. Use when configuring GKE storage or creating PVCs. For GCS FUSE mounts, use google-cloud-storage-fuse. For diagnosing storage failures (volume attach/mount errors, disk performance/node storage pressure, or Cloud Storage FUSE OOM), use gke-storage-troubleshooting. Don't use for database administration or replication strategies outside volume provisioning context.
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。
Diagnoses GKE persistent-storage failures — volume attach/mount errors (Regional PD on optimized VMs, fsGroup mount timeouts), disk-performance and node storage-pressure issues, slow-disk Pod-creation failures, volume-expansion problems, Local SSD / Hyperdisk Storage Pool creation errors, and Cloud Storage FUSE OOM. Use when Pods are stuck in ContainerCreating, volumes fail to attach or mount, or nodes report storage pressure. Don't use for routine storage provisioning or StorageClass/PVC authoring (see the gke-storage skill).
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。
Daily reusable-session flaky-test triage for {{target_repo}}. Pulls CI run history from GitHub, scores each test's non-determinism against a persistent per-test ledger, and once a test reaches {{quarantine_threshold}} opens a quarantine PR (skip + reason, never delete) plus a running tracking issue, and posts a summary to {{alert_channel}}. Never merges.
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-session, per-sweep QA runbook for {{target_repo}}. Discovers PRs since the last check, then for each one checks out the branch, runs the full verification suite, deploys the change to the test environment, exercises it through the edge, and posts a pass/fail result as a GitHub check and comment. Test environment only — no production access, no merge.
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, deploy and operate Kortix Apps through the pre-authenticated CLI or SDK: static sites and SPAs, Dockerfile or OCI servers, workers, and stateful backends (a database, a Convex backend) with persistent volumes, snapshots and built-in Kortix sign-in. Use when the user asks to publish, host, deploy, preview, inspect, scale, wake, suspend, roll back, debug, or remove an App; asks for a database, an API, a backend, a data model, auth, or 'store this'; asks for an internal tool, business app, CRM, tracker, dashboard, portal, or any app the team logs in to; before writing any Convex code; or asks what an App costs or how it 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。
Pi-compatible PUA high-agency governance skill. Use for explicit PUA/PIP requests, repeated failures, passive/giving-up behavior, user frustration, or unverified completion. Pair with /pua-on extension command when persistent pressure is desired.
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 world-model harness that stress-tests ideas, strategies, and investments against 11 time horizons from 6 months to 50 years, each a deep analysis of geopolitics, tech, economics, society, and security, in Fast/Standard/Deep tiers. USE WHEN threat model, world model, test idea, future analysis, time horizon, stress test against future, long-term risk. NOT FOR single-shot idea attack (use RedTeam).
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。
Defensive threat modeling and risk management for your own estate — map where sensitive data lives across your asset graph, run compromise scenarios (what a hacked asset exposes, its blast radius, how you'd respond), and maintain a persistent risk register with likelihood×impact scoring, owners, mitigations, and review cadence via a deterministic CLI. All real data stays in your private USER tree; this skill is code only. USE WHEN threat model, threat modeling, risk register, risk assessment, what if X got hacked, compromise scenario, blast radius, sensitive data map, where is our sensitive data, data classification, risk review, add a risk, accept a risk, security risk posture. NOT FOR active pentesting or exploitation (use an offensive-security skill), world-scale futures stress-testing of ideas (use WorldThreatModel), or executing incident response (use your incident-response runbooks — this skill plans them).
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。
This skill should be used for persistent semantic memory in agent systems: cross-session knowledge retention, entity tracking, temporal validity, graph or vector retrieval, memory consolidation, and memory benchmark selection. Route file-backed scratchpads to filesystem-context, handoff summaries to context-compression, and token-efficiency tactics to context-optimization.
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。
Initialize, adopt, and route work for a separate Obsidian knowledge vault through the portable claude-obsidian core. Use for vault setup, scaffolding, workspace selection, cross-project configuration, or choosing the correct wiki sub-skill. Triggers: /wiki, set up wiki, scaffold vault, create knowledge base, adopt this vault, Obsidian vault, second brain setup, persistent wiki.
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。
Drive a real stealth browser from your shell — act on websites (order food, file an expense, pull data behind a login), with per-person persistent sign-ins via the provider's managed auth (Kernel, Anchor, or Browserbase — picked by which API key you have). Use for ACTING on a site; to just read a page, use curl/wget first. Requires managed model access and a keychain grant for the browser provider key; follow the missing-key steps below.
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。
Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation 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。