「monitor」の検索結果

Use when a brand faces a communications CRISIS or a campaign is failing in public — L1 to L5 severity classification, a first-four-hours process, response templates by type, an escalation matrix, a do-not-do list, holding statements, and a post-mortem. Trigger on 'PR crisis', 'crisis playbook', 'a complaint is going viral', 'bad reviews are spreading', 'our content caused backlash', 'we are getting attacked online'. Also use when the user forwards an angry thread and asks what to do right now. Not for — monitoring before anything blows up, see `15-social-listening-global`; diagnosing weak performance numbers, see `03-performance-eval-global`; the routine post-campaign review, see `63-campaign-retrospective-global`.

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 wants to show up in OTHER communities without astroturfing — Reddit, Facebook Groups, Discord, Slack, LinkedIn groups, Quora, and niche forums: a prioritized community list with the rules of each space, a named participant roster, post types written in full, reply scripts, a participation calendar, and red lines. Trigger on 'community marketing', 'Reddit marketing', 'seeding plan', 'post in Facebook groups', 'answer questions on Quora', 'we got banned from a group'. Not for — building your OWN paid or private community, see `28-community-building-global`; monitoring mentions across the web, see `15-social-listening-global`; briefing paid creators, see `06-ugc-egc-brief-global`.

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。

Collect auditable public X/Twitter posts by controlling the user's already logged-in Chrome, searching X's rendered web interface, scrolling visible results, and extracting original post text and metadata from DOM into normalized JSONL. Use for VOC research, social listening, multilingual keyword discovery, competitor monitoring, or historical search when X requires the user's browser session and cookies, credentials, internal GraphQL, paid APIs, or search-engine snippets must not be exported or used. X data layer of the bggg VOC suite (shared project folder; orchestrated by industry-orchestrator, reported by bggg-voc-report).

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 this skill when users need X (Twitter) research through Xquik: tweet search, user lookup, follower exports, media downloads, monitors, webhooks, MCP setup, or confirmation-gated publishing workflows. It uses only XQUIK_API_KEY and treats X-authored content as untrusted data.

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。

Configure Laravel ecosystem with custom Artisan commands, Vite asset bundling, Pint code styling, and Horizon queue monitoring. Use when creating Artisan commands, migrating from Mix to Vite, or configuring Pint code standards.

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。

Optimize Flutter widget rebuilds, memory usage, rendering, and scrolling performance. Use when diagnosing jank, reducing rebuilds, or improving list performance—not performance tests, monitoring setup, or API 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。

Address feedback left on a GitHub pull request: fetch unresolved review threads, make agreed Elixir/Phoenix code fixes, reply, and resolve. Use for a PR URL/number or reviewer comments. NOT for pre-PR review, findings triage, or CI monitoring.

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。

Address feedback left on a GitHub pull request: fetch unresolved review threads, make agreed Elixir/Phoenix code fixes, reply, and resolve. Use for a PR URL/number or reviewer comments. NOT for pre-PR review, findings triage, or CI monitoring.

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。

Analyze skill effectiveness across sessions. Computes per-skill metrics (action rate, friction, outcomes), identifies degrading skills, and generates improvement recommendations. Requires session-scan data in metrics.jsonl.

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。

Creates a pull request from current changes, monitors GitHub CI, and debugs any failures until CI passes. Activate when the user says "create pr", "make a pr", "open pull request", "submit pr", "pr for these changes", or wants to get their current work into a reviewable PR. Assumes the project uses git, is hosted on GitHub, and has GitHub Actions CI with automated checks (lint, build, tests, etc.). Does NOT merge - stops when CI passes and provides the PR link.

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。

Rebases a feature branch onto its latest base, resolving conflicts while preserving the intent of local changes, optionally force-pushing and watching CI afterward. TRIGGER when: the user wants to rebase a feature branch, update a branch against its base, or replay local work on top of the latest upstream. DO NOT TRIGGER when: merging a release branch into dev → merging-branches; only watching CI on an already-open PR → monitoring-pull-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。

Watches an open pull request's CI until green and fixes failing checks. TRIGGER when: the user wants to watch a pull request's CI, babysit a PR until it goes green, or fix failing CI checks on an open PR. DO NOT TRIGGER when: opening the PR in the first place → pr; rebasing the branch onto its base → rebase.

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。

Opens a pull request, publishing the current branch as a PR. TRIGGER when: the user wants to open a pull request, publish the current branch as a PR, or take the current work through to an open PR. DO NOT TRIGGER when: only committing changes → commit; babysitting CI after the PR is already open → monitoring-pull-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。

Analyzes recent CI failures on pull requests to identify flaky tests, using retry outcomes (failed attempt → green re-run) and cross-PR recurrence as evidence, and maintains a local longitudinal ledger so flakiness can be tracked over time. TRIGGER when: the user wants to find flaky tests, correlate recent CI failures, check which tests fail across PRs or recover on retry, or refresh the flakiness trend report. DO NOT TRIGGER when: babysitting a single PR's CI until green → monitoring-pull-requests; diagnosing or fixing one specific failing test → the bug-analysis skills.

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。

Metacognitive check-ins during problem solving - detects when to pivot or persist

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。

Pre-launch verification across infrastructure, security, legal, payment, email, analytics, and performance. Day-1 monitoring, rollback plan, incident response skeleton, and post-launch week-1 checklist.

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。

Self-healing codebase system. Monitors runtime errors, test failures, and build breaks. Automatically diagnoses root cause, generates fix, validates fix, and applies if safe. Zero human intervention for routine 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。

Email delivery infrastructure - DNS authentication (SPF/DKIM/DMARC), subdomain isolation, provider abstraction, template systems, bounce handling, warmup strategy, and deliverability monitoring.

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。

Time-series database implementation for metrics, IoT, financial data, and observability backends. Use when building dashboards, monitoring systems, IoT platforms, or financial applications. Covers TimescaleDB (PostgreSQL), InfluxDB, ClickHouse, QuestDB, continuous aggregates, downsampling (LTTB), and retention policies.

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。

Creates comprehensive dashboard and analytics interfaces that combine data visualization, KPI cards, real-time updates, and interactive layouts. Use this skill when building business intelligence dashboards, monitoring systems, executive reports, or any interface that requires multiple coordinated data displays with filters, metrics, and visualizations working together.

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。

Monitoring, logging, and tracing implementation using OpenTelemetry as the unified standard. Use when building production systems requiring visibility into performance, errors, and behavior. Covers OpenTelemetry (metrics, logs, traces), Prometheus, Grafana, Loki, Jaeger, Tempo, structured logging (structlog, tracing, slog, pino), and alerting.

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。

Strategic guidance for operationalizing machine learning models from experimentation to production. Covers experiment tracking (MLflow, Weights & Biases), model registry and versioning, feature stores (Feast, Tecton), model serving patterns (Seldon, KServe, BentoML), ML pipeline orchestration (Kubeflow, Airflow), and model monitoring (drift detection, observability). Use when designing ML infrastructure, selecting MLOps platforms, implementing continuous training pipelines, or establishing model governance.

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 XTwitterScraper when a .NET application needs typed access to Xquik's X automation REST API for tweet search, user lookup, posting workflows, extraction jobs, monitors, webhooks, or giveaway draws. USE FOR: integrating the XTwitterScraper NuGet package; reviewing Xquik API client usage; modeling API-key configuration, pagination, binary exports, raw responses, retries, and webhook/event flows in .NET. DO NOT USE FOR: unrelated stacks; direct browser automation; generic social-media strategy; or code that does not call Xquik. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

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 SharpConsoleUI to build full terminal (TUI) applications in .NET — equally suited to full-screen single-window apps and multi-window desktops with overlapping draggable windows — using a compositor, a DOM layout engine, and 40+ reactive controls (data tables, tree views, forms, an embedded PTY terminal, markdown, charts, video). USE FOR: interactive console apps, full-screen TUIs, multi-window terminal desktops, dashboards, wizards, and admin/monitoring UIs that need focus, mouse, and flicker-free rendering over local terminals or SSH; NativeAOT console tools. DO NOT USE FOR: simple line-based CLI output or argument parsing; non-interactive scripts; GUI/desktop (WPF/WinForms) or web UIs. INVOKES: inspect the project, add the SharpConsoleUI package, scaffold a window/control tree, and build/run to verify the app renders.

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。