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Create a high-signal bug issue or PR in the repo that owns the defect. Use this whenever the user asks to report, file, open, or triage a LazyCodex, lazycodex-ai, omo-codex, Codex plugin, or upstream Codex CLI bug, especially when they need source-backed root cause, reproduction steps, fix guidance, and GitHub routing.

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Extract report views, ratings, key assumptions and risks with sources and dates. Use when the user asks to research report breakdown with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.

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 Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).

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Use when work in this repo depends on a change in a different repo that has its own running Claude session (frontend needing a backend endpoint, backend needing a client change, a shared package bump). Covers finding the peer session, what to put in the request so it needs no follow-ups, and how to handle the reply.

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 reproducible final report, literature-outcome synthesis, JSON summary, and refreshed progress plot for a stopped or interrupted NVFLARE Auto-FL campaign.

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。

Search 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.

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。

Search 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.

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 "run a launch retro / post-mortem", "compare launch results vs targets by channel", or "decide what to keep or kill for the next launch"; produces a structured D1/W1/M1 retrospective — a per-channel actual-vs-target table (UTM-attributed own analytics as the truth column, platform self-reported numbers as reference, every figure labeled Measured / User-provided / Estimated), a 5-Whys chain on the single largest miss, keep / kill / change decisions per channel, 3-5 actionable learnings for the next launch, and an outcome snapshot submitted to the launch registry. Not for return math (CPA / ROI) — use roi-calculator; not for the stakeholder-facing report writeup — use report-generator; not for a metric deep-dive — use performance-analyzer. 发布复盘/渠道归因/5-Whys/keep-kill

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 "create a campaign report", "build an executive summary", or "deliver client results"; produces audience-tailored influencer marketing reports (executive, client, internal team) with data tables, narrative, key learnings, and recommendations. Not for raw metric computation — use performance-analyzer. 达人营销报告/结案汇报

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Step-by-step process for merging a previously-standalone Grails plugin repository (e.g. grails-spring-security, grails-redis) into the grails-core monorepo as one or more Gradle subprojects, wiring it into the shared build, publishing, docs, and CI the same way the existing modules are.

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 local repository risk receipt before Claude Code or other AI-agent edits. Use when the user asks to prepare a repository for agent changes, check for risky hooks or credential-writing automation, or run the /agent-preflight command. Trigger with "run agent preflight", "check this repo before agent edits", or "/agent-preflight".

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Build evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios. Use for market definition, industry and customer evidence, competitive landscapes, TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds.

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。

Searching internet for technical documentation using llms.txt standard, GitHub repositories via Repomix, and parallel exploration. Use when user needs: (1) Latest documentation for libraries/frameworks, (2) Documentation in llms.txt format, (3) GitHub repository analysis, (4) Documentation without direct llms.txt support, (5) Multiple documentation sources in parallel

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 modern full-stack web applications with Next.js (App Router, Server Components, RSC, PPR, SSR, SSG, ISR), Turborepo (monorepo management, task pipelines, remote caching, parallel execution), and RemixIcon (3100+ SVG icons in outlined/filled styles). Use when creating React applications, implementing server-side rendering, setting up monorepos with multiple packages, optimizing build performance and caching strategies, adding icon libraries, managing shared dependencies, or working with TypeScript full-stack projects.

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 creating a DeepSeek Harness plugin, choosing public names for a new external DSH plugin, validating a dsh-plugin.naming.json manifest, checking reviewed central registrations for known conflicts, or creating a workspace package inside the deepseek-harness repository. Covers the full workflow from repository-mode and plugin-form selection through separate offline naming validation, optional online registry lookup, and package validation. Routes tool, LLM adapter, hook, service, and configuration forms to their corresponding references while separating upstream-monorepo rules from external-package rules. For an existing plugin crossing Harness versions, use this Skill's built-in version-adaptation workflow before implementing against the exact target contract.

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Runs environment, health and safety on an operating site — hazard controls in order of effectiveness, incident recording and reporting obligations, and safety measurement that does not reward silence. Use this to build or audit a safety program, decide what controls a hazard actually needs, work out whether an injury is recordable or reportable, investigate an incident, or fix safety metrics that have stopped producing reports.

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 reporting and self-serve analytics that people actually use — metric trees, dashboard design, distribution, and the discipline that stops dashboards proliferating. Use this to build a dashboard or report, design a metrics framework, set up self-serve analytics, decide what to measure, or diagnose why reporting exists but nobody uses it or trusts 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。

Submit a GitHub repository to be indexed by the OpenAkita Skill Store. Use when user wants to share their skills repo with the community.

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。

Checks biomedical manuscripts against reporting guidelines such as CONSORT, STROBE, PRISMA, and TRIPOD to identify missing or weak reporting elements before submission or revision.

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。

For a repository in the babysitter-users catalog, locate its babysitter processes and any committed runs (.a5c/runs/<runId>/) and perform a retrospective on a chosen run -- what went well, what failed, process suggestions, quality of effect design, breakpoint patterns -- mirroring the /babysitter:retrospect workflow but applied to an external repo. Invoke when asked to "retrospect on repo X's run", "analyze how someone else used babysitter", or "review an external babysitter 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。

Atlas turns your STATED NEED into a real systems atlas by SCANNING your actual sources (Azure via `az`, git repos, local dirs) and process/data mining them, THEN enriching against the Atlas knowledge graph. Use this skill when asked to inventory/map your real systems, scan your cloud + repos + directories, mine the real processes or data they contain, or collect their real constraints/gotchas. (atlas, scan my systems, inventory our azure account, map my repos, real systems atlas, process mining, data mining, collect nuances, system discovery)

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 compression reports for video processing. Use when you need to create structured JSON reports with duration statistics, compression ratios, and segment details after video processing.

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 structured CSV security audit reports from vulnerability data with proper filtering and formatting. This skill covers CSV schema design for security reports, using Python csv.DictWriter, severity-based filtering, and field mapping from JSON to tabular format.

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Safely package codebases with repomix by automatically detecting and removing hardcoded credentials before packing. Use when packaging code for distribution, creating reference packages, or when the user mentions security concerns about sharing code with repomix.

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。