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Generator economic dispatch and cost optimization for power systems. Use when minimizing generation costs, computing optimal generator setpoints, calculating operating margins, or working with generator cost functions.

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。

Diagnostic guide for RL-based post-training of language models (GRPO, PPO, REINFORCE, DPO). Use proactively when debugging a training pipeline that shows no improvement, loss anomalies, reward stagnation, NaN gradients, or other unexpected behavior during reinforcement learning fine-tuning. Work through all pipeline stages — reward, advantages, log-probs, loss, generation/decoding — before concluding the diagnosis is complete; stopping after one or two fixes is a common failure mode. Covers log-probability math, advantage estimation, numerical stability, reward processing, and generation/decoding pipeline issues.

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。

Reference for paired-reversal handling on GL batch tapes: an RV row whose ref-trace points at an earlier row cancels BOTH legs (the RV and the row it references) — but ONLY when the two value-dates fall within the shop's reversal settlement window; an RV that references a too-old posting is NOT a cancellation and posts one-sided. Useful when the posting tape carries a reference-trace column alongside reversal codes and the running balance is off by twice the reversal magnitude, or by a whole leg on stale references.

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 effective blameless postmortems with root cause analysis, timelines, and action items. Use when conducting incident reviews, writing postmortem documents, or improving incident response processes.

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。

You are a cloud cost optimization expert specializing in reducing infrastructure expenses while maintaining performance and reliability. Analyze cloud spending, identify savings opportunities, and implement cost-effective architectures across AWS, Azure, and GCP.

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 existing Azure resources and analyze Reservations or Savings Plans. WHEN: "optimize Azure costs", "reduce cloud spending", "rightsize resources", "find idle resources", "orphaned disk", "deleted VM still charged", "public IP still charging", "reservation utilization", "Savings Plan coverage", "commitment recommendation", "why is pay-as-you-go still charged". DO NOT USE FOR: cost spikes, forecasts, pricing estimates, budgets, or 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。

Writes educational Teams channel posts about Claude Code features and best practices, using templates emphasizing concrete examples and underlying principles (e.g. context engineering). Use when writing a Teams post or announcement to teach colleagues Claude Code usage, announce a feature, share a tip, or document a lesson learned.

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。

Snapshots, restores and reconciles Claude Code / Codex sessions inside Ghostty tabs across reboots. Use when quitting the Mac for an update (保存终端会话 / 重启前备份终端), after restart to reopen tabs with their original session IDs (恢复之前的窗口 / restore my ghostty tabs), or to audit which sessions survived. Not for resuming one conversation via its own --resume, terminal screenshots, or tmux state. Also use for periodic change-only snapshots (定期增量快照 / 没变化不记录). Also use before or after a manual Codex account switch (额度耗尽换号 / 换号后恢复全部 Codex).

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。

Reconstruct where you were and what's next after an interruption, so a broken focus doesn't cost you the whole thread. Use when asked where was I, I got interrupted and lost my place, help me pick back up, or I forgot what I was doing. Produces a quick rebuild of the task's state from what you remember (what you'd done, what you were mid-thought on), the single next action to re-enter it, and a 'breadcrumb' habit for next time — cutting the expensive re-immersion cost that interruptions inflict, especially on ADHD brains.

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。

Compute what a degree will actually cost — sticker minus real aid, inflated per year, split into cash and loans, with the loan's decade-long monthly tail made visible before enrollment instead of after. Use when asked what will college really cost, compare these two offers' real prices, how much loan payment after graduation, or is this school affordable. Produces the all-in number from the script, the offer-letter decode (grants vs loans untangled), the monthly-tail reality check, and the two-school comparison.

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。

Compile the team's REAL updates into one async standup — pull what people posted in Slack (and moved in Notion/Linear), not a template for running standups. Use when asked to compile today's standup, pull the team's updates into one post, what did the team ship, or run async standup in Cowork. Reads a Slack channel and (optionally) the tracker via connectors, groups updates by person into shipped / in-progress / blocked, surfaces the blockers needing attention, and produces a standup-digest artifact ready to post back.

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-mortem on what the user has already posted - which reels actually worked, why, and what to stop making. Use when the user pastes their Instagram insights or past posts and asks "what's working", "why did this flop", "read my analytics", "audit my content", or wants to know what to do more of.

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 Neon serverless Postgres: projects, branches, databases. Branch create and delete need exact-match confirmation; connection passwords are masked. Trigger phrases: neon, serverless postgres, database branch, postgres project.

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 Nest device state (thermostats, cameras, doorbells) and set thermostat modes and setpoints via the Smart Device Management API. Trigger phrases: google nest, nest thermostat, nest camera, sdm.

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。

Backend infrastructure for a project via Cohesivity (cohesivity.ai). Provisions Postgres, Redis, object storage, vector database, hosting, auth, realtime, email inbox, and AI model APIs through one HTTP API. No account or API keys required to start. Trigger phrases: cohesivity, provision backend, need a database, need hosting, need storage, deploy backend, on-the-fly infrastructure.

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。

Plan and implement OpenMeld PostgreSQL business persistence, schemas and migrations, transactions, Hyperdrive access, and data cutover. Use for the shared relational database transition or PostgreSQL work; not for unrelated D1 performance fixes or OpenConnector's upstream database.

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。

Plan and implement OpenMeld PostgreSQL business persistence, schemas and migrations, transactions, Hyperdrive access, and data cutover. Use for the shared relational database transition or PostgreSQL work; not for unrelated D1 performance fixes or OpenConnector's upstream database.

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。

Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.

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。

Scrape recent posts from LinkedIn profiles using Apify. Use when you need to monitor what specific people are posting on LinkedIn, track founder/exec activity, or gather LinkedIn content for competitive intelligence.

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。

Detect buying intent from job postings. When a company posts a job in your problem area, they've allocated budget and are actively thinking about the problem. This skill finds those companies, qualifies them, extracts personalization context, and outputs everything to a Google Sheet. Does NOT do outreach — just delivers qualified leads with reasoning.

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。

Turn public social videos, transcripts, posts, creator research, or the user's own source material into platform-specific LinkedIn posts, X posts and threads, short-form scripts, newsletters, blog outlines, carousel briefs, and content calendars. Use when the user wants to reuse a strong idea without copying the source.

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。

Normalizes and transforms RNA-seq count matrices for DE, visualization, clustering, and ML. Covers between-sample (TMM, TMMwsp, RLE/median-of-ratios, upper quartile), within-sample (TPM, FPKM/RPKM), variance-stabilizing (VST, rlog, log-CPM), GC-content correction (cqn, EDASeq), and single-cell (scran deconvolution, scanpy normalize_total). Encodes the composition-bias rationale, the "most genes not DE" assumption and its catastrophic failure modes (MYC amplification, apoptosis, viral host shutoff, prokaryotic stress), the "lengthScaledTPM is not TPM" naming trap, the "TPM is not for DE" rule, the blind=TRUE vs FALSE decision, ERCC spike-in normalization (SBN), and the single-cell zero-inflation breakdown of TMM/RLE. Use when choosing or applying normalization, debugging shifted-MA-plot diagnostics, handling zero-heavy single-cell data, or correcting GC bias.

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 DE-specific diagnostic and result visualizations using DESeq2/edgeR built-in functions and lightweight ggplot2 wrappers. Covers MA plot (with the shrunken-LFC compression effect), volcano (with the apeglm caveat that p-values are unchanged), PCA on VST/rlog (never raw counts), sample distance heatmaps, top-DE-gene heatmaps with the row-scaling trap, dispersion / BCV plot interpretation, p-value histogram diagnostics, plotCounts for individual genes, blind=TRUE vs FALSE rationale, and the n=3 visualization stake. Use when generating DE diagnostic plots, choosing VST vs rlog for visualization, troubleshooting suspicious plot patterns (shifted MA cloud, batch-dominated PCA, anti-conservative p-value histogram), or building a standard QC figure panel.

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。

Microstrip, stripline, CPW, differential pairs, and crosstalk analysis for impedance-controlled PCB interconnects. TRIGGER: user asks to design or analyze a transmission line (microstrip, stripline, CPW, coplanar, differential pair), extract RLGC or per-unit-length parameters, compute trace impedance, analyze a PCB trace cross-section, or perform crosstalk/coupling analysis. Invoke BEFORE writing code — preferred over RF Toolbox analytical functions (txlineMicrostrip, txlineStripline, txlineCPW). SKIP: EM simulation/S-parameter extraction of an existing component (use matlab-analyze-em), material/stackup definition only (use matlab-manage-pcb-material), building custom non-catalog geometry (use matlab-assemble-pcb-layout), optimization sweeps (use matlab-optimize-pcb-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。