101 件 ・ 関連度順
概要と使いどころ
Expert-level waste management covering solid waste characterization, collection systems, landfill design, composting, waste-to-energy, recycling, and hazardous waste regulations.
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。
Calculate material waste factors and losses using CWICR norms. Apply waste percentages, cutting losses, and spillage factors to material quantities.
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。
Evaluates water treatment, waste management, and environmental services assets with regulatory compliance and growth drivers. Use when analyzing water infrastructure, evaluating waste assets, or assessing utility investments.
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。
Expert-level environmental engineering covering water treatment, wastewater treatment, air quality, solid waste, site remediation, and environmental regulations.
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。
Assigns pathogen lineages (SARS-CoV-2 Pangolin via UShER mode; Nextclade clade + QC; pango-designation alias_key.json resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage fitness modelling (Wenseleers / Bedford-Figgins multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data version pinning (mandatory for reproducibility), Nextclade dataset versioning (lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme version churn (V3 / V4 / V4.1 / V5.3.2 / Midnight 1200) with documented dropout regions, recombinant X-prefix Pango designation lag, GISAID vs INSDC dual-deposition tensions, and the Karthikeyan 2022 wastewater early-detection signal with explicit reproducibility caveats. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater pooled samples into lineage frequencies with Freyja, tracking lineage frequencies and growth advantages over time, pinning pangolin-data / Nextclade dataset versions for reproducibility, handling ARTIC primer dropouts (V4.1 amplicons 64 / 76 / 88-90), or running variant surveillance for SARS-CoV-2 / influenza / Mpox / RSV / H5N1 / measles.
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。
Assigns pathogen lineages (SARS-CoV-2 Pangolin via UShER mode; Nextclade clade + QC; pango-designation alias_key.json resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage fitness modelling (Wenseleers / Bedford-Figgins multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data version pinning (mandatory for reproducibility), Nextclade dataset versioning (lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme version churn (V3 / V4 / V4.1 / V5.3.2 / Midnight 1200) with documented dropout regions, recombinant X-prefix Pango designation lag, GISAID vs INSDC dual-deposition tensions, and the Karthikeyan 2022 wastewater early-detection signal with explicit reproducibility caveats. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater pooled samples into lineage frequencies with Freyja, tracking lineage frequencies and growth advantages over time, pinning pangolin-data / Nextclade dataset versions for reproducibility, handling ARTIC primer dropouts (V4.1 amplicons 64 / 76 / 88-90), or running variant surveillance for SARS-CoV-2 / influenza / Mpox / RSV / H5N1 / measles.
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。
Find money leaking between search ads and SEO — queries you pay for while already ranking organically, and paid queries with no organic coverage. Use when asked "am I paying for clicks I'd get free", "brand bidding waste", "SEO vs ads overlap", or "cut wasted ad spend with SEO".
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 wasted paid-ad spend, pacing, and allocation, then propose safe evidence-backed optimizations. Use for waste, negatives, budgets, bid changes, poor CPA or ROAS, underpacing, overspend, or scaling 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 the user asks to "mine my search terms", "find new keywords from converting queries", "build a negative-keyword list", or "cut wasted paid spend"; harvests converting queries into new keywords/ad-groups, builds a standing negative-keyword list and an n-gram waste report from the search-terms export, and delivers a maintenance diff (add / negate / move). Not for account structure — use campaign-architect; not for budget split — use budget-optimizer; not for computing the final RQS — use ad-account-auditor. 付费广告搜索词挖掘/否定关键词/浪费词清单
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。
Assigns pathogen lineages (SARS-CoV-2 Pangolin UShER mode; Nextclade clade + QC; pango-designation alias resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage-fitness modelling (multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data and Nextclade dataset version pinning (mandatory; lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme churn (V3/V4/V4.1/V5.3.2/Midnight) with dropout regions, and recombinant X-prefix designation lag. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater into lineage frequencies with Freyja, tracking lineage frequencies over time, handling ARTIC primer dropouts, or running surveillance for SARS-CoV-2/influenza/Mpox/RSV/H5N1/measles.
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。
Amazon negative keyword management and optimization. Search term analysis, waste reduction, savings estimation, and automated negative keyword strategies. Use when the user asks about negative keywords, search term analysis, ad waste reduction, or PPC 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。
Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run.
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 estimates, quotes, and bids for trades and field-service businesses (HVAC, plumbing, electrical, roofing, landscaping, painting, cleaning, remodeling, general contracting, IT/AV installs). Turns a scope into line items with waste factors, burdened labor, materials, equipment, subs, permits, mobilization, contingency, overhead, profit, and tax, then writes a client-ready xlsx (live formulas) and PDF plus an internal cost sheet, with good/better/best options, add-ons, a payment schedule, exclusions, and assumptions. Use whenever someone asks for a quote, estimate, bid, proposal price, or job price, asks "how much should I charge for this job", wants to check a price or margin on a job, or is confused about markup vs margin. Computes deterministically with a script instead of mental math, because models routinely treat a 30% markup as a 30% margin and drop labor burden, waste, and mobilization.
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。
Systematic analysis of Google Ads and Meta advertising spend to identify wasted budget. Produces actionable exclusion lists with thematic categorization and statistical validation. Use when onboarding new accounts, performing monthly hygiene, or preparing for budget 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。
Operational efficiency audit — identify waste, redundancy, and friction across processes, tools, and team workflows. Use when asked to "audit our operations for waste", "where are we inefficient", "what tools are we paying for but not using", or "reduce operational overhead".
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。
Audit cloud spend — identify waste, rightsizing opportunities, and reservation gaps. Use when asked "our cloud bill is too high", "find cloud waste", or "where can we rightsize".
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。
Audit AI spend — per-model cost breakdown, top consumers, waste identification, optimization levers. Use when asked "why is our AI bill so high", "audit LLM spend", or "where is our token waste".
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。
Operations management and lean production techniques for turning inputs into outputs under variability. Covers the Toyota Production System, seven wastes, just-in-time, kanban, jidoka, single-minute die exchange, 5 Whys, value stream mapping, bottleneck theory, and the distinction between mass production and flexible production. Use when diagnosing operational waste, designing production flows, setting up quality systems, or comparing batch-and-queue to one-piece flow.
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。
Orchestrator context window discipline enforcement. Prevents the orchestrator from reading source files it will not edit, running diagnostic commands that waste context, and rationalizing delegation bypasses. Use when setting up orchestrator guardrails, reviewing delegation discipline, or diagnosing context window waste in multi-agent workflows. Activates PreToolUse hooks that surface decision points before source file reads and diagnostic command execution.
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。
Expert FinOps guidance for cloud, AI, and SaaS technology spend. Covers AI cost management, agentic FinOps, GenAI capacity planning, self-hosted vs managed inference, Anthropic billing, open-weight vendor APIs (DeepSeek, Qwen, Kimi, GLM), AWS (EC2, Bedrock, SageMaker, Savings Plans, CUR), Azure (reservations, AHB, OpenAI PTUs), GCP (Vertex AI, BigQuery), OCI, Kubernetes cost allocation, data platforms (Databricks, Fabric F-SKUs, Snowflake), tagging governance, SaaS management (SAM, shadow IT), AI coding tools (Cursor, Claude Code, Copilot, Codex), ITAM, allocation, showback, chargeback, anomaly management, KPIs and benchmarking, waste detection playbooks, workload onboarding and M&A, and GreenOps (cloud carbon, CSRD). Use for any question about technology cost or waste in your estate - expiring commitments or RIs, NAT gateway bills, idle VMs, snapshot sprawl - and for commitment sizing, rightsizing, allocation, SaaS sprawl, AI dev tool spend, or connecting spend to business value. Built by OptimNow.
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。
Audit Claude Code session logs (~/.claude/projects) for token waste and produce a ranked, attributed efficiency report (habit / skill_file / config). Use when the user asks to audit session efficiency, analyze token waste or cost blowups, review Claude Code usage cost, or asks "where are my tokens going".
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。
"Apply Lean and Six Sigma principles to eliminate waste and reduce process variation. Use this skill when the user needs to improve operational efficiency, identify the seven wastes (TIMWOOD), run DMAIC improvement projects, or streamline workflows — even if they say 'our process is too slow', 'where are we wasting resources', or 'how do we reduce defects'.".
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。
Map existing business processes using BPMN 2.0 notation or simplified swimlane diagrams. Identify waste, handoffs, decision points, and improvement opportunities using Lean principles (8 Wastes). Use when documenting workflows for SOP creation, automation assessment, or process improvement. Do not use for software architecture diagrams — use architecture tools instead.
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 a task needs the judgment of an Environmental Compliance Inspector — reviewing discharge monitoring reports or emissions data against permit limits, classifying a facility's hazardous waste generator status, calculating a penalty for a documented violation, deciding whether an exceedance warrants a Notice of Violation versus informal correction, or scoping a multimedia (air/water/waste) inspection.
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。