633 件 ・ 関連度順
概要と使いどころ
Any live-web task via the Firecrawl CLI — including ordinary web research: searching the web, reading or extracting pages, gathering sources, discovering site URLs, bulk extraction, downloading a site, change alerts, or pages needing clicks/login — web only; local files route to firecrawl-parse. For papers use firecrawl-research-index; for library, API, error, or bug questions use firecrawl-developer-index.
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。
Coordinates an active production incident by establishing command, reducing blast radius, preserving evidence, communicating verified impact, restoring service, validating recovery, and creating owned follow-up actions. Use for outages, severe degradation, security or data-integrity events, failed releases, and urgent operational triage. Not for a normal local bug, routine alert tuning, or a postmortem after the incident is already closed.
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。
Designs or reviews logs, metrics, traces, alerts, correlation, dashboards, and diagnostic instrumentation so failures and performance changes can be detected and explained at component boundaries. Use for observability work, incident readiness, instrumentation, or production diagnostics. Not for fixing a specific incident before reproducing it or for adding noisy logging without an operational question.
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。
Implements OpenTelemetry logs/metrics/traces, SLI/SLO gates, burn-rate alerts, and APM integrations. Use when adding or validating observability.
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。
Reinforces an AI agent by turning Monte Carlo's reinforcement loop diagnosis into code fixes. Reads the daily reinforcement loop report for an agent's workflows, ranks the diagnosed issues, proposes what to fix, and — with the user's approval at each step — opens a pull request. Activates on "fix my agent", "improve my agent's health", "reinforce my agent", "what should I fix in my agent". Not for investigating a specific agent alert or trace (monte-carlo-troubleshoot-agent-traces), creating agent monitors (monte-carlo-monitoring-advisor), or instrumenting a new agent (monte-carlo-instrument-agent).
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 data-related requests to the right Monte Carlo skill or workflow. USE WHEN alerts, incidents, data broken, stale, coverage gaps, data quality, or any ambiguous data observability request.
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 incident response — triage, root cause, remediate, prevent recurrence. USE WHEN active alerts, data broken, stale, pipeline failure, or investigate and fix a data incident.
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。
Troubleshoots Monte Carlo AI agent alerts and traces — eval score drops, latency/token spikes, trajectory and validation breaches. Not for data incidents (monte-carlo-analyze-root-cause) or monitor creation (monte-carlo-monitoring-advisor).
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 and remediate data quality alerts using Monte Carlo MCP tools. Runs root cause analysis, assesses blast radius, discovers available tools (MCP/CLI/API), proposes and executes fixes, or escalates with full context when uncertain.
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 a Monte Carlo monitor and recommend config changes to reduce alert noise. Supports metric, custom SQL, validation, table, and agent (metric, evaluation, trajectory, validation) monitors. Fetches the report, identifies patterns, and suggests tuning.
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。
Engineering observability and reliability: SLO/SLI design, distributed tracing, alerting, dashboards, capacity planning, toil automation, reliability review. Use for instrumentation or SLO 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。
Optimizing FinOps and cloud cost: IaC-based estimation, right-sizing, RI/SP recommendations, anomaly detection, budget alerts, AI/GPU workload economics. Use to forecast or cut cloud spend.
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。
Remediating known failure patterns automatically from Triage diagnoses and Beacon alerts: runbooks with safety-tier classification, staged verification, rollback. Use for automated remediation.
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。
Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available 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。
Query Amazon is latest policy, regulation, and compliance feed. Supports paginated browsing by marketplace and time range (with AI-generated Chinese summaries), and fetching full article body by record ID. Trigger when users mention Amazon policies & regulations, seller compliance announcements, platform rule changes, policy alerts, FBA/fee policy updates, multi-marketplace policy tracking, policy original text, news details, or similar terms. Even if the user does not explicitly mention "policy feed," trigger this skill whenever the request involves Amazon is officially published policies, regulations, and news for sellers, including their full text.
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 Amazon product historical time-series data, including price trends, BSR (Best Sellers Rank) trends, rating changes, seller counts, and monthly sales, supporting any ASIN across multiple Amazon marketplaces. Triggered when users mention price history, price tracking, BSR history, BSR trends, historical pricing, price fluctuations, Nexscope data, rank history, price drop alerts, lightning deal historical prices, Buy Box price trends, coupon prices, FBA/FBM price comparison, seller count changes, rating trends, sales history. Even if users do not explicitly mention "Nexscope" or "time-series data", this skill should be triggered whenever the task involves analyzing Amazon product-level historical data (such as price, rank, or sales trends over time).
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。
Manage Apple Reminders on macOS via remindctl — list, add, edit, complete, delete to-dos that sync to iPhone/iPad. Trigger on "reminder", "Reminders app", "提醒我" with phone sync, or adding personal todos with due dates. macOS only. Skip when the user wants agent-internal alerts (use memory_store or external scheduling) or calendar events.
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。
SEO/GEO Agent Operations SOP v2 — Rebuilt from real-world operations (analook.com 0→launch, GSC incident, DataForSEO monitoring, gingiris.tools post-migration recovery). What's new in v2: • Step-by-step onboarding (Q1→Q6), multiple choice wherever possible — no big forms • Mandatory daily SEO log — first item is always GSC token status check • Data cross-validation rule: any external metric must come from ≥2 sources before use • Backlink progress tracking (6-week wait → check → alert if not indexed) • New vs. established site strategy matrix (new site <6mo: KD≤20; mature: KD up to 35+) Real incidents baked in: GSC token expired silently for 2 weeks (analook.com), P0 keywords dropped out of Top 100 after domain migration (gingiris.tools), traffic data off by 17× from single-source DataForSEO. Triggers: "SEO agent" | "SEO daily report" | "GSC monitoring" | "DataForSEO" | "GEO agent" | "backlink tracking" | "IndexNow" | "competitor comparison page" | "SEO SOP" | "autonomous SEO" | "GEO triple combo" 🇨🇳 SEO/GEO Agent 运营 SOP v2 — 基于真实运营经验重写（analook.com 从零建站 + GSC 断档 2 周 + DataForSEO 监控 + gingiris.tools 迁移权重恢复）。 对话式开局、强制日报（GSC token 是第一项）、数据交叉验证铁律、外链进度追踪、新老站区分策略。
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。
Twitter/X Agent Operations SOP v2 — Rebuilt from real dual-account operations. Real data: • CN account: grew from 1,150 → 3,679 followers (~14 months), 1 tweet/day, OAuth1 direct post • EN account: Buffer API • Real incidents: cron silent-failed for 2 weeks unnoticed, analytics data off by 17×, thread performance worse than single posts What's new in v2: • Step-by-step onboarding (Q1→Q6), multiple choice wherever possible — no big forms • Mandatory daily log after every tweet + weekly report every Monday • Pre-publish safety checklist (agent must pass before posting) • Content pool tracker (used/unused) + alert when ≤3 items remain • Dual-account credential separation (CN: OAuth1 / EN: Buffer API) • MASTER-STATUS.md as the single source of truth — read + write every session 🇨🇳 Twitter/X Agent 运营 SOP v2 — 基于真实双账号运营经验重写。 开局对话式收集 context、强制日报+周报、发推前红线自检、素材库追踪、双账号凭证分离、MASTER-STATUS.md 单一真相来源。 真实数据：中文账号从 1,150 粉增长至 3,679 粉（约14个月），1条/天。 Triggers: "twitter运营" | "推特agent" | "发推SOP" | "AI代运营" | "推文日报" | "素材库" | "Buffer API" | "OAuth1发推" | "twitter automation" | "tweet sop" | "推特涨粉"
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。
Debug validator checkpoint inconsistencies where some validators are behind others. Use when alerts mention "checkpoint inconsistency", "validators behind", or "inconsistent latest checkpoints", or when asked to debug validator sets, investigate validator delays, or troubleshoot metadata fetch failures for a chain. Defaults to default_ism app context if not specified.
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 stuck messages in relayer queue. Use when alerts mention "queue length greater than 0", to diagnose why messages are stuck, or to get message IDs for denylisting.
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。
Debug RPC provider health issues for a chain. Use when alerts mention RPC failures, high latency, stale blocks, or provider errors. Diagnoses the issue and recommends fixes.
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。
RxMemberSim generates realistic synthetic pharmacy data for testing PBM systems, claims adjudication, and drug utilization review. Use when user requests: (1) pharmacy claims or prescription data, (2) DUR alerts or drug interactions, (3) formulary or tier cohorts, (4) pharmacy prior authorization, (5) NCPDP formatted output.
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。
Survey existing cloud cost controls — tagging coverage, alerting, and FinOps maturity. Use when asked to "audit our cost controls", "is our tagging complete", or "assess our FinOps maturity".
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。