「fan」の検索結果

Use when facing 2+ independent tasks or investigations that can be worked on without shared state or sequential dependencies — fan out to specialized sub-agents with isolated context, then synthesize the results.

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。

Chinese journal scout — searches candidate journals via Wanfang API, performs L1 deterministic rejection screening (language/funding/subject mismatch), and L2 citation fingerprint analysis (reference journal distribution → academic ecosystem positioning).

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。

International journal scout — searches candidate SCI/SSCI/EI/Scopus journals via Wanfang foreign journal API, performs L1 deterministic rejection screening, and L2 citation fingerprint analysis.

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 about Russian state-sponsored cyber operations or specific actors (APT28/Fancy Bear, Sandworm, Cozy Bear/APT29, Turla, GRU-affiliated hacktivist fronts like CARR/NoName057), wartime ICS/OT campaigns, or pro-RU information operations. Self-updating knowledge cell.

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Entwurf einer BAG-konformen Abmahnung im Arbeitsrecht – konkrete Schilderung der Pflichtverletzung, klare Verhaltenserwartung, ausdrückliche Sanktionsandrohung. Use when AG eine verhaltensbedingte Sanktion vor einer Kündigung dokumentieren muss oder AN die Wirksamkeit einer empfangenen Abmahnung prüft.

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-deploy observability for production services — structured logging, RED metrics + Prometheus, Grafana dashboards, SLO-based alerting. Use when setting up monitoring or instrumenting a live service. Trigger on "add logging", "metrics", "dashboard", "alerting", "observability", "monitor this service".

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。

Orchestrate a whole-registry sweep of Gaia — fan out 13 parallel audit agents across every skill, run adversarial verification, surface Semantic Fusion candidates, propose new generic skill references, and synthesize a publish-ready HTML report under docs/meta/reports/. Use this skill for broad, systemic analysis across many skills at once: "run a meta sweep", "sweep the meta", "full meta audit", "audit the whole registry against META.md", "widespread nomenclature issues", "find all skills missing a GitHub link", "produce a meta report", "check for evidence type mismatches across the registry", "find skills that document a third-party tool with no attribution", or explicitly types /gaia-meta-sweep. This is the registry-wide macro companion to /gaia-meta-audit (a prioritized queue, single-pass) and /gaia-audit (fixes one skill). Use it when you need the full surface — 13 audit dimensions, adversarial verification, fusion proposals, and a durable findings artifact — not just a queue.

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。

Builds reusable malware configuration extractors by applying a declarative JSON spec (offsets, decode layers, field definitions) to a sample to produce structured, defanged config. Activates for requests to build a config extractor, write a reusable family config parser, or run a spec-driven configuration extraction.

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 Tilt and scaffold or audit Tiltfile + tilt/ configurations with ecosystem-aware templates. Auto-detects Java/Gradle (Spring Boot), Next.js, Python/uv, and external infrastructure; recommends single-file or modular tilt/*.star + service-config.yaml + environments.yaml patterns based on project complexity. Bakes in production-context safety guards, PVC persistence toggles, JDWP debug ports, and optional Prometheus/Grafana/Traefik scaffolds. Use when user runs /devtools:tilt-setup, mentions "tilt setup", "setup tilt", "scaffold tiltfile", "audit tiltfile", "tilt configure", "tilt project setup", "Tiltfile", "local kubernetes dev", or "kubernetes development environment".

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。

Set up application observability with Prometheus, Grafana, Datadog, or CloudWatch — instrument metrics endpoints, configure Golden Signal dashboards, define alert rules with burn-rate SLOs, and add structured logging

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 a production-grade OEE (Overall Equipment Effectiveness) measurement pipeline for a manufacturing line — data ingestion from MQTT/OPC-UA/Modbus/CSV, A×P×Q calculation engine, Six Big Losses categorizer, MTBF/MTTR/TEEP metrics, Grafana or Streamlit dashboard.

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。

Run the Yuzu full governance pipeline on a commit range. Produces Gate 1 Change Summary, then orchestrates Gates 2-6 as parallel agent fan-outs with pre-written prompt preambles. Use when the user says "/governance <range>" or "full governance" or asks to run the multi-gate review pipeline on a PR/commit set.

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。

How to use the coding agents installed on this machine (claude, codex, droid, grok, vktr, hermes, opencode, copilot, pi) as plain sub-agents in orchestrated workflows: one headless invocation, one prompt in, one result out. Deliberately ignores each CLI's own orchestration features (droid --mission, codex multi_agent, hermes delegation/moa/kanban, grok --agents, opencode personas). The orchestrator is whatever session is running the skill; the CLIs are interchangeable workers. Use when the user asks "which agent should run this", "fan out workers", "run X headless", or when a lifeos skill (overnight, timeboxed-iterating, workgraph, gauntlet, bughunt, dark-factory) needs to launch an agent CLI, or when a worker needs company context it should ask Viktor for (vktr).

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。

Cold-start brownfield reconnaissance — reconstruct the WHOLE game design from an existing codebase when there is no GDD yet. Optionally accepts a free-text game description, notes, or reference links to guide and enrich the scan. Use when the user wants to build the game design from the code, e.g. "create a GDD from this codebase", "reconstruct the design from our code — it's a roguelike deck-builder", "build a design doc from the existing project, here are some refs". Scans the project (engine auto-detected), extracts a system roster + dependency graph and content-type schemas / resources / entities into one passive .unikit/gamedesign/RECON.md, tags every fact provenance:extracted-from-code, and writes a mandatory Intent Gap for what code cannot know (pillars, fantasy, the "why"). Writes nothing else and calls no skill. STRICTLY whole-project cold-start — if a GDD already exists and the user wants a specific part investigated, use /unikit-gd-explore (code lens); to author the GDD use /unikit-gd-spec.

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 the SQL or MongoDB query that answers a question and keeps answering it: the right grain, no fan out, parameterised window, checked against something known. Use when a number is needed that no report carries, when an existing query returns something that looks wrong, when a query is slow or expensive, or when somebody asks for a one off pull.

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。

Trust-boundary security audit of cqs — fans out unbiddable-auditor agents across 6 categories (RT-INJ/RT-FS/RT-RES/RT-DATA/RT-RELAY/RT-EXFIL), attacker mindset, run-the-attack PoC + regression guard.

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 monitoring dashboards that answer real operator questions for Grafana, SigNoz, and similar platforms. Use when turning metrics into a working dashboard instead of a vanity board.

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 fantasy landscape with a vibrant, sunset-inspired color palette of orange, pink, and purple.

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。

Epic fantasy group portrait in a magical forest, mystical lighting, dynamic poses, remove objects from original photo, using reference faces

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。

Structured logging conventions for DraftForge backend (Django/Celery/Daphne) and frontend (React). This skill should be used when adding log statements, creating new modules, debugging with logs, or reviewing logging patterns. Covers structlog usage, system/subsystem taxonomy, required fields, log levels, and Grafana query patterns.

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。

Investigate reviewed Grafana APM evidence for request rate, error rate, and operational latency. Use when an application is slow, erroring, dropping traffic, regressing against a baseline, or needs a bounded request-rate, error, and p95 latency health assessment.

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。

Inspect reviewed Grafana infrastructure evidence for host or fleet CPU usage, memory load, disk space, and system load. Use for server-health checks, capacity symptoms, resource saturation, disk pressure, cloud or local host comparisons, and bounded infrastructure triage.

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 reviewed Grafana log evidence for event patterns, error-rate changes, and enrolled security markers. Use when a user needs bounded log analytics for an incident window, error-log comparison, anomaly triage, operational debugging, or a cautious check of approved security signals.

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Review approved Grafana business-intelligence evidence for revenue, conversion, and operational KPIs. Use for bounded KPI scorecards, financial or operational metric checks, baseline comparisons, and business-unit reviews without changing source 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。