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概要と使いどころ
Draft anonymous one-page company teasers for sell-side M&A processes. Creates a compelling summary without revealing the company's identity, designed to gauge buyer interest before NDA execution. Triggers on "teaser", "blind teaser", "anonymous profile", "one-pager for process", or "draft teaser for sell-side".
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 and organize a universe of potential acquirers for sell-side M&A processes. Identifies strategic and financial buyers, assesses fit, and prioritizes outreach. Use when preparing for a sell-side mandate, building a buyer universe, or evaluating potential partners. Triggers on "buyer list", "buyer universe", "potential acquirers", "who would buy this", "strategic buyers", or "financial sponsors".
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。
Author a NEW skin for the reskinnable-demo app. A skin is a self-contained domain plugin under src/skins/<id>/ that implements the frozen `Skin` contract (src/shell/skin-contract.ts) to swap the app's entire experience — brand, theme, layout, pages, tools, data, and agent — as a live sales demo. Use when the user says "add a skin", "create a skin", "new skin", "reskin the app", "make a <domain> skin", or wants the app re-themed as a new product. Do NOT use for editing the shell itself (src/shell/**), the shared token vocabulary (src/app/globals.css), or the shipped skins unless explicitly asked.
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。
Work on one hard mathematics problem in this session yourself, with no sub-agents: reason in stages, record each settled step in a notes file so that nothing written is lost if a response is cut off, and end with a self-contained proof.md. Usage: /math-proof:solo <the problem, stated in full, or the path of a file holding it>.
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 personal Claude Code usage & impact report ("receipts") from this machine's local session transcripts — for justifying Claude Code usage/spend to a manager, self-review, or "what have I been using this for" check-ins. Mines ~/.claude/projects locally (no extra API calls beyond one final write-up), cross-references local git history, and writes a markdown report plus a self-contained HTML receipt to your home directory. Use when the user asks for "receipts", an "impact report", "usage report", wants to "show my Claude Code activity", "prove the value of Claude Code", or runs `/receipts`.
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。
Start and persistently pursue a goal to babysit an SGLang pull request until selected GitHub Actions workflows pass on the latest PR head. Use when asked to monitor, babysit, retry, or fix PR CI for lint.yml, pr-test.yml, pr-test-extra.yml, AMD, or other named workflows; classify failures as PR-related versus flaky or infrastructural, auto-fix and push only small clean fixes, rerun failed jobs only up to 10 times, and ignore unselected workflows.
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 before opening a PR, or whenever asked to self-review a diffusers contribution. Applies the same rubric as the `@claude` CI (checks the diff against references/review-rules.md, traces call paths for dead code). Reports findings grouped by severity, flagging what to fix before submitting (blocking issues + dead code) vs what to leave for the actual review. Report-only — does not edit files.
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。
Deploys anomaly detection for OT/ICS environments using machine learning on OT network baselines, physics-based process models, and Modbus/DNP3/OPC UA traffic analysis to flag deviations, rogue devices, and mismatches against historian data. Use for continuous OT monitoring, baselining deterministic SCADA polling, or investigating alerts from Nozomi Guardian/Dragos needing deeper protocol 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。
When the user wants to create or optimize in-app paywalls, upgrade screens, upsell modals, or feature gates. Also use when the user mentions "paywall," "upgrade screen," "upgrade modal," "upsell," "feature gate," "convert free to paid," "freemium conversion," "trial expiration screen," "limit reached screen," "plan upgrade prompt," or "in-app pricing." Distinct from public pricing pages (see page-cro) — this skill focuses on in-product upgrade moments where the user has already experienced value.
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, extend, debug, or contribute to PicoClaw itself. Use when the task is about PicoClaw CLI commands, config.json, gateway, auth, models, skills, MCP servers, cron, routing, sessions, self-evolution, built-in slash commands, or repository internals. Use PicoClaw-native workflows, terminology, paths, and configuration.
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。
Structure a performance review with self-assessment, manager template, and calibration prep. Use when review season kicks off and you need a self-assessment template, writing a manager review for a direct report, prepping rating distributions and promotion cases for calibration, or turning vague feedback into specific behavioral examples.
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。
Support SOX 404 compliance with control testing methodology, sample selection, and documentation standards. Use when generating testing workpapers, selecting audit samples, classifying control deficiencies, or preparing for internal or external audits.
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。
This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research strategy, navigate decision trees, or get help choosing what scientific problem to work on. Typical requests include "I have an idea for a project", "I'm stuck on my research", "help me evaluate this project", "what should I work on", or "I need strategic advice about my research".
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。
End-to-end workflow for implementing a non-trivial qwen-code feature. Covers requirements investigation, design, E2E test planning, baseline dry-run, implementation, verification, self-audit, code review, and iteration.
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。
When the user wants to create or optimize in-app paywalls, upgrade screens, upsell modals, or feature gates. Also use when the user mentions "paywall," "upgrade screen," "upgrade modal," "upsell," "feature gate," "convert free to paid," "freemium conversion," "trial expiration screen," "limit reached screen," "plan upgrade prompt," or "in-app pricing." Distinct from public pricing pages (see page-cro) — this skill focuses on in-product upgrade moments where the user has already experienced value.
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。
Compliance OS — meta-orchestrator that lets compliance teams CONFIGURE which frameworks apply, COMPUTE cross-framework control overlap, SIMULATE internal audits, and CONSOLIDATE evidence across multiple frameworks. Four decisions: (1) Given a company profile, which of the 12 supported frameworks apply (ISO 27001/13485/42001/14971, EU AI Act, MDR 745, GDPR, SOC 2, FDA QSR, NIST CSF 2.0, NIS2, HIPAA)? (2) Across selected frameworks, which controls overlap and how much evidence reuses? (3) For a given framework + scope, what does a realistic mock audit produce — drawing from the 205-scenario library? (4) Across selected frameworks, what's the unified evidence checklist with reuse map? Use when standing up a multi-framework program, planning the annual audit calendar, or preparing for certification stage 1. Does NOT replace per-framework skills (it orchestrates them).
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。
/cs:caio-review <plan> — Eval-demanding Chief AI Officer interrogation of any plan that involves AI: model selection, risk classification, cost economics, or AI hiring. Use when shipping an AI feature without an eval set, choosing between API, fine-tune, and self-hosted, or classifying a use case under the EU AI Act.
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。
The meta-framework for how a company runs — the connective tissue between all C-suite roles. Covers operating system selection (EOS, Scaling Up, OKR-native, hybrid), accountability charts, scorecards, meeting pulse, issue resolution, and 90-day rocks. Use when setting up company operations, selecting a management framework, designing meeting rhythms, building accountability systems, implementing OKRs, or when user mentions EOS, Scaling Up, operating system, L10 meetings, rocks, scorecard, accountability chart, or quarterly planning.
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 how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains.
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 a sprint with capacity estimation, story selection, dependency mapping, and risk identification. Use when preparing for sprint planning, estimating team capacity, selecting stories, or balancing sprint scope against velocity.
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。
Commit, push, branch, and manage version control with GitButler. Use for commits, selective dirty-file or hunk commits, branches, diffs, PRs, history edits, squashes, amends, undo, merge, apply, and unapply. For selected dirty files or hunks, inspect with `but diff`; use compact `but status` for commit order, branch/stack placement, or conflict overview; use `but status -fv` when file/hunk IDs or per-commit file details matter. Replaces git write commands.
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。
Guides the migration of existing AI workloads (Cloud Run, Gemini API, Gemini Enterprise Agent Platform) to self-hosted GKE inference using gcloud and kubectl. Use when the user has an existing AI inference workload (on Cloud Run, the Gemini API, Gemini Enterprise Agent Platform, or a custom VM) and wants to move it to self-hosted inference on GKE, or asks follow-up questions during such a migration (hardware sizing, model staging, manifest generation, validation, traffic cutover). DO NOT use for brand new GKE inference deployments with no existing workload to migrate (use gke-inference instead). DO NOT use if the user intends to automate the migration via the Gemini Cloud Assist MCP server.
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。
Diagnoses, remediates, and manages Identity and Access Management (IAM) access issues on Google Cloud. Supports two distinct operational modes: (1) Requester Flow for developers encountering access denials (capturing error context, self-service PAM JIT activations, elevated developer self-remediation, or logging structured tickets), and (2) Resolver Flow for privileged administrators (authoritative Policy Troubleshooter analysis, deny policy exemptions, least-privilege role discovery, and PAM/IAM provisioning).
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。
Optimizes GKE costs, rightsizes workloads, and configures Spot VMs, CUDs, cost allocation, and resource quotas. Use when optimizing GKE cluster or workload costs, configuring GKE cost allocation or quotas, rightsizing CPU/memory requests, or selecting Spot VMs and machine types. Don't use for general compute class provisioning or GPU Selection (use gke-compute-classes 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。