Read and control Table v9 state in react. Use for tracked reads, subscriptions, controlled slices, and framework-specific reactive boundaries.
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。
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Read and control Table v9 state in react. Use for tracked reads, subscriptions, controlled slices, and framework-specific reactive boundaries.
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。
Read and control Table v9 state in alpine. Use for tracked reads, subscriptions, controlled slices, and framework-specific reactive boundaries.
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。
Read and control Table v9 state in ember. Use for tracked reads, subscriptions, controlled slices, and framework-specific reactive boundaries.
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。
Read and control Table v9 state in preact. Use for tracked reads, subscriptions, controlled slices, and framework-specific reactive boundaries.
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。
Read and control Table v9 state in octane. Use for tracked reads, subscriptions, controlled slices, and framework-specific reactive boundaries.
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。
Read and control Table v9 state in lit. Use for tracked reads, subscriptions, controlled slices, and framework-specific reactive boundaries.
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。
Read and control Table v9 state in svelte. Use for tracked reads, subscriptions, controlled slices, and framework-specific reactive boundaries.
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。
Read and control Table v9 state in vue. Use for tracked reads, subscriptions, controlled slices, and framework-specific reactive boundaries.
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 a prospective clinical study before submission — selecting and classifying endpoints (primary / key-secondary / exploratory, with surrogate-endpoint flagging), estimating sample size and power for two-arm designs (means / proportions / survival), or scoring a study plan for feasibility and a GO / GO-WITH-CONDITIONS / REDESIGN / NO-GO phase-gate decision. Every output is an ESTIMATE plus a named human owner (clinician / biostatistician / regulatory owner) — never clinical fact, never a finished protocol. Distinct from ra-qm-team, which handles the regulatory/QM submission (ISO 13485, EU MDR, FDA 510(k)/PMA/QSR), not the study design.
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。
Memory health dashboard showing line counts, topic files, capacity, stale entries, and recommendations. Use when the user runs /si:memory-status or asks how full or healthy the agent memory is.
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。
Write internal company communications — 3P updates (Progress/Plans/Problems), company-wide newsletters, FAQ roundups, incident reports, leadership updates, status reports, project updates, and general internal comms. Use this skill any time the user asks to draft, edit, or format something meant for internal audiences. Trigger on keywords like "3P", "weekly update", "newsletter", "FAQ", "internal comms", "status report", "company update", "team update", "incident report", or any request to summarize work for leadership, teammates, or the broader company. Even casual requests like "write my update" or "summarize what my team did this week" should trigger this 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。
World-class senior data scientist skill specialising in statistical modeling, experiment design, causal inference, and predictive analytics. Covers A/B testing (sample sizing, two-proportion z-tests, Bonferroni correction), difference-in-differences, feature engineering pipelines (Scikit-learn, XGBoost), cross-validated model evaluation (AUC-ROC, AUC-PR, SHAP), and MLflow experiment tracking — using Python (NumPy, Pandas, Scikit-learn), R, and SQL. Use when designing or analysing controlled experiments, building and evaluating classification or regression models, performing causal analysis on observational data, engineering features for structured tabular datasets, or translating statistical findings into data-driven business decisions.
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 adding, retiring, or auditing feature flags. Triggers on "add a flag", "ship behind a flag", "rollout plan", "kill switch", "stale flags", "flag debt", "LaunchDarkly", "GrowthBook", "Statsig", "Unleash", "Flipt", or any progressive-delivery question. Ships flag debt scanner, rollout planner, and kill-switch auditor (all stdlib Python), 4 references on flag taxonomy + provider trade-offs + rollout strategies + lifecycle, plus a /flag-cleanup slash command.
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 value proposition statements for marketing, sales, and onboarding from existing value propositions. Use when writing marketing copy, creating sales messaging, or crafting onboarding messages.
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。
Reproduce a known chat state in the running desktop on demand (model provider errors and retries, Code Mode and Den script failures, parallel tool steps, app creation, sequential commands) and check how it renders. Use when fixing or designing chat error, retry, tool-step or app-card UI.
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 reusable, composable n8n sub-workflows. Use when extracting shared logic, building anything multi-step or reused across workflows, or any workflow over ~10 nodes — and whenever the user mentions sub-workflows, Execute Workflow, reuse, shared/common logic, modular workflows, "Define Below" inputs, waitForSubWorkflow, mode each vs all, or exposing a workflow as an agent tool. Covers typed sub-workflow inputs, all-vs-each execution, verb-first naming for discovery, stateless vs stateful design, and splitting by input shape.
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。
Check Screenpipe health status, process state, and diagnose common issues
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Summarize one project against its stated milestones using recent work and verified outcomes.
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Commit, push, branch, and manage version control with GitButler. Use for commits, selective dirty-file or hunk commits, branches, diffs, PRs, history edits, squashes, amends, undo, merge, apply, and unapply. For selected dirty files or hunks, inspect with `but diff`; use compact `but status` for commit order, branch/stack placement, or conflict overview; use `but status -fv` when file/hunk IDs or per-commit file details matter. Replaces git write commands.
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。
Diagnose and mitigate GKE TPU or GPU nodes stuck in NotReady / NodeStatusUnknown ("Kubelet stopped posting node status") due to host kernel panics, hardware lockups, or disabled node auto-repair. Use when nodes stop heartbeating beyond the node auto-repair threshold and pods remain stuck in Terminating. Don't use for healthy nodes, pod-only application crashes, or routine GKE upgrades.
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 nodes reporting NotReady or Unknown status by inspecting node conditions, events, kubelet/containerd logs, and node metrics, then proposing safe remediations. Use when nodes show NotReady, when the kubelet stops posting node status, or when workloads are evicted or stuck Pending due to node health. Don't use for pod-level application failures (use gke-workload-troubleshooting), autoscaler scale-up/scale-down decisions (use gke-cluster-autoscaler), or non-GKE compute.
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。
Detects AI-generated writing four ways — a heuristic audit against a catalog of known AI patterns, deterministic statistical signals (n-gram entropy, burstiness, repetition, stylometry — features never verdicts), an empirical Pangram score calibrated against known-human baselines, and a keyless scan for watermark and steganography signatures (invisible characters, homoglyphs, bidi, odd whitespace) in the bytes. USE WHEN detect AI writing, is this AI, AI detection, AI detector, did an AI write this, does this sound like AI, AI writing score, pangram, scan for AI tells, flag AI patterns, AI-isms, statistical AI signals, burstiness, text entropy, is this watermarked, detect watermark, steganography, zero-width chars, hidden characters, invisible unicode, compare drafts for AI-ness. NOT FOR rewriting prose to strip AI patterns (use a voice/authoring skill), plagiarism detection, detecting AI-generated images/video/code, or judging whether writing is any good.
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。
Install and onboard a user into LifeOS — the Life Operating System (current state → ideal state via TELOS + the Algorithm). The agentic installer detects your OS + harness, wires hooks with permission, scaffolds your USER tree, pulls in sources you provide, and runs the TELOS / current→ideal interview that seeds your Pulse dashboard. USE WHEN install LifeOS, set up LifeOS, lifeos setup, lifeos-setup, lifeos interview, onboard me, run the interview, integrate LifeOS into my harness, update LifeOS, uninstall LifeOS, first-time setup, lifeos doctor, check my install, what capabilities are broken. NOT FOR building or cutting a LifeOS release (private release tooling), editing TELOS after onboarding (use Telos / Interview), or LifeOS system maintenance (use the private maintenance 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。