「inu」の検索結果

Background Agent Pings

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。

Completion Check: Verify Infrastructure Is Wired

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。

Agentic Workflow Pattern

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。

E-commerce SEO audit for online stores (WooCommerce, Shopify, Magento, custom). Covers category / product listing pages (PLP), product detail pages (PDP), faceted navigation and its crawl-budget and duplicate-content traps, pagination, canonicals for variants and filters, out-of-stock / discontinued products, internal linking and breadcrumbs, and Product / Offer / Review / AggregateRating / BreadcrumbList structured data. Use whenever the user runs an online store and asks about product or category page SEO, filter URLs being indexed, product rich results, or thin/duplicate product pages. Trigger on: "e-commerce SEO", "ecommerce SEO", "product page SEO", "category page SEO", "WooCommerce SEO", "Shopify SEO", "faceted navigation", "filter URLs in Google", "product schema", "rich snippets for products", "out of stock SEO", "duplicate product pages". For a single URL use /seo-page; for full-site use /seo-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。

Deterministic debugging with rr record-replay. Use when debugging crashes, ASAN faults, or when reverse execution is needed. Provides reverse-next, reverse-step, reverse-continue commands and crash trace extraction.

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。

Estimate causal effects from existing data. Use when fitting or interpreting DiD, ITS, synthetic control, regression discontinuity, or other treatment-effect analyses, including robustness checks and counterfactual plots. For choosing a study design before analysis, use designing-experiments 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。

Design experiments and quasi-experiments before analysis. Use when choosing study design, treatment/control structure, outcomes, assumptions, validation plans after scientific experiment failure, or which of DiD, ITS, synthetic control, or regression discontinuity fits the research question. For fitting models or estimating effects on existing data, use performing-causal-analysis 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。

CVE validation domain card. Use after CVE lookup has produced applicable or candidate CVEs and red-team mode needs scoped evidence to decide whether to continue, pivot, or report.

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。

CTF杂项知识库 — Python Jail逃逸、Bash Jail逃逸、编码链识别与解码、QR/音频/图像隐写、游戏VM逆向、CTFd API导航、Linux提权

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。

Cross-platform, hardware-adaptive system optimizer. Auto-detects macOS / Linux / WSL / Windows (MINGW/Cygwin/MSYS2) and CPU/RAM/disk/GPU profile, then picks the right cleanup strategy. Scans reclaimable disk space, memory pressure, runaway processes, startup bloat, network issues. CleanMyMac built into Claude Code.

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。

Automatically organizes invoices and receipts for tax preparation by reading messy files, extracting key information, renaming them consistently, and sorting them into logical folders. Turns hours of manual bookkeeping into minutes of automated organization.

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。

Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.

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。

Set up the BSP source workspace: Linux_for_Tegra overlay tracker, bsp_sources, Crosstool-NG toolchain. Use after jetson-init-image; not for fetching inputs.

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。

Download NVIDIA Jetson Linux BSP artifacts (BSP tarball, sample rootfs, public_sources, x-tools, guides) for the active target. Use for Auto Setup; not for extraction or profile edits.

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。

Extract Jetson Linux + sample-rootfs tarballs and run apply_binaries.sh for the active target, then record bsp_image in the profile. Use after jetson-init-target; not for source-tree setup.

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 you need to print Jetson BSP info (L4T version, board configs, rootfs state) from a Linux_for_Tegra root on the host PC. This is an example skill.

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。

Run predictions with a finetuned KERMT checkpoint on a SMILES-only CSV. The skill validates that the input ckpt has task FFN heads (refuses pretrain ckpts with a redirect to kermt-finetune), validates the CSV, prepares the data (clean + rdkit_2d features), then launches main.py predict inside the kermt container (blocking, minutes-scale).

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。

Pretrain a fresh KERMT model from scratch on a user-provided corpus. Builds a new vocabulary from the corpus, instantiates the model architecture from defaults, and launches pretrain_ddp.py inside the kermt container (detached for long runs). Unlike kermt-continue-pretrain, no starting checkpoint is loaded — the model is randomly initialized.

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 a named CCB agent by combining authoritative runtime and job lineage with deep read-only pane inspection, apply bounded recovery when evidence supports it, verify the result, and request authorization before submitting a redacted GitHub issue. Use for `$ccb_diagnose agentname`, `$ccb-diagnose agentname`, or reports that a CCB agent is stuck, disconnected, not continuing, not replying, or showing provider errors.

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 and recover CCB communication and reply delivery stalls. Use when a user reports a missing CCB_REPLY, stuck ask, agent stuck busy/delivering, queued work behind an active job, cancelled/incomplete reply, empty artifact, callback not continuing, duplicate retry after success, or a CCB mailbox/communication backend that appears stuck.

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 this skill when OpenStoryline is already installed and the user wants to start the local MCP/Web services, create or continue a session, send editing instructions, perform multi-turn re-editing, and verify rendered video outputs, as well as Chinese requests like “启动 OpenStoryline”, “把 OpenStoryline 跑起来”, “用 OpenStoryline 剪视频”.

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。

Security best practices and vulnerability prevention for Golang — injection (SQL, command, XSS), cryptography, path traversal, SSRF and HTTP security headers, cookies, secrets management, memory safety, PII in logs, STRIDE/DREAD threat modeling, plus `gosec` SAST, race detection, and fuzz testing. Apply when writing, reviewing, or auditing Go code for security, or when touching crypto, file or network I/O, secrets, user input, or authentication. Not for non-exploitable defensive bugs such as nil panics or slice aliasing (→ See `samber/cc-skills-golang@golang-safety` skill), dependency vulnerability scanning with govulncheck (→ See `samber/cc-skills-golang@golang-dependency-management` skill), or wiring security scanners into CI pipelines (→ See `samber/cc-skills-golang@golang-continuous-integration` skill).

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。

GitHub Actions CI/CD pipeline configuration for Golang projects — workflow files for test, lint, SAST, coverage and vulnerability-scan jobs, Dependabot and Renovate config files, GoReleaser release pipelines, Docker build/push, repository security settings, and AI-driven PR review. Use when setting up or improving Go project CI, writing or fixing `.github/workflows/*.yml`, adding a linter or security scanner as a pipeline job, wiring automated dependency-update bots, or adding quality gates. Covers wiring tools into a pipeline, not the analysis they perform: do NOT use for choosing or interpreting security findings (→ See `samber/cc-skills-golang@golang-security` skill) or for choosing, upgrading, or auditing dependency versions (→ See `samber/cc-skills-golang@golang-dependency-management` skill).

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。

Dependency management for Golang projects — go.mod and go.sum, `go get` install and upgrade flows, Minimal Version Selection, conflict resolution with replace/exclude/retract, `govulncheck` scanning of the module tree, outdated dependency and binary size auditing, vendoring, `tool` directives, and go.work workspaces. Use when adding, removing, or upgrading Go dependencies, deciding whether to take on a package, resolving version conflicts, or auditing what a module pulls in. Covers choosing and upgrading dependency versions, not the surrounding tooling: do NOT use for fixing an exploitable vulnerability in code (→ See `samber/cc-skills-golang@golang-security` skill) or for wiring Dependabot/Renovate update bots into CI workflows (→ See `samber/cc-skills-golang@golang-continuous-integration` skill).

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。