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概要と使いどころ
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
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。
Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.
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。
Vibe Code Orchestrator (VCO) is a governed runtime entry that freezes requirements, bounds execution, and enforces verification and phase cleanup.
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。
Remove AI-generated code slop from a branch: unnecessary comments, redundant defensive checks, boilerplate, style drift, and type casts. Use for cleanup of AI-written code, not for broad code review, security audit, TDD, or final verification.
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。
Default code-quality route for broad code review, PR review, maintainability, correctness, and regression-risk checks. Do not use as the primary route for dedicated OWASP/security audits, review-feedback handling, completion verification, AI-code cleanup, or TDD/test-first work.
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。
Domain routing and boundary guidance for authorized post-exploitation testing after initial access, including privilege escalation, persistence, lateral movement, data collection, and cleanup considerations. Use when a task belongs to the post-exploitation domain and needs scope, evidence, pivot, or exit criteria.
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 whenever the agent creates, writes, moves, or renames a file in a team/delegate (shared) workspace, OR when the user asks to organize, clean up, restructure, audit, or find files in any workspace or the Vault, OR when starting a multi-file task or named project. Enforces a purpose-based folder convention (flat mode: notes/, data/, outputs/, scripts/, archive/; project mode: projects/<slug>/{docs,assets,source,reports,research}/), per-agent namespacing under shared/<agent_key>/, and pre-write discovery via memory_search, vault_search, knowledge_graph_search to surface related files and avoid duplicates. Trigger before any write_file or exec at workspace root, when starting a project, generating reports/assets/exports, delegating, or when the user says "messy", "where did I save", "tổ chức lại", "dọn workspace", "tạo report", "find related", "search vault". Do NOT trigger for read-only ops, edits inside an existing project tree (cloned repo), or short-lived files deleted in the same turn.
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。
Create a clean PR branch by filtering out .planning/ commits — ready for code review
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。
Archive accumulated phase directories from completed milestones
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。
Remove pauses, filler words (um, uh), and dead air from raw YouTube recordings via the Tubeify API. Use when the user wants to edit a video, clean up audio, trim silences, or polish a raw recording for YouTube.
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。
Verify that a watermark-removal or "humanizer" step actually removed a statistical text watermark, by measuring a sample whose key the user holds. Use after any tool, script or service claims to have cleaned a text, or when the user asks whether such a tool works, which one to trust, or how to test one. Reports a detector score against fixed thresholds plus what the run cost in meaning, facts, verbatim overlap and length. This skill only measures and never removes a mark.
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。
Triggered by "tidy up", "clean up transactions", "categorize uncategorized", "organize my transactions"
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。
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
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。
⧉ Copy a message to the system clipboard cleanly formatted — no blockquote pipes, no terminal bars, no Claude commentary. Use whenever you draft a message the user will paste (Slack, Teams, PR comment, email) to add a clickable "⧉ ctrl + click" copy link under it, and when the user says "/ctrl-clip", "copy that", "put it on the clipboard" (in any language). Optional argument picks the target format: slack (default), md, plain.
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 the session to durable vault memory and prepare a clean resume point
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, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or Megatron-Bridge), pretraining/CPT, RL alignment (DPO/RLVR/GRPO/RLHF), BYOB/MCQ benchmarks, checkpoint conversion, ModelOpt optimization, env profiles, and evaluation of trained checkpoints or existing/hosted endpoints. Use when a request names a Nemotron step or workflow, or asks to clean, translate, train, fine-tune, align, convert, optimize, evaluate, or compose these into a pipeline. Do NOT use for frontend/dashboard/visualization work, generic ML advice, billing/access, or non-Nemotron coding tasks.
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 for reusable Holoscan Module work with ./holohub: scaffold, tests, editable install, DEB/WHEEL packaging, and clean-consumer proof.
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 the user runs doca_dpa_hl_tracer to capture/decode DPA-side traces at the programming-events layer (kernel entry/exit, sync points, comm primitive calls, RDMA WR submission, completion drain) — picking TRACE vs CRIT, tuning the JSON config (file-size limits + file_size_limit_policy, thread priorities/cores), decoding against the matching DPA-side ELF, or diagnosing empty/noisy captures. Trigger even when the user does not explicitly mention "DOCA DPA tracer" or "high-level tracer" — typical implicit phrasings include "DPA kernel returns wrong result but host completions look clean", "kernel-entry to first-comm latency is huge", "RDMA WR to drain gap on the DPA", "trace file truncated mid-run", "TRACE doubled my DPA latency", or "tracer wrote a file but parser shows zero events". Refuse and route elsewhere for writing DPA kernels, DPA-Comms/DPA-Verbs programming, raw per-cycle DPA profiling, host-side doca-dpa debugging, or production DPA telemetry — those belong to other skills.
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 the user is writing their first DOCA app or asking a library-agnostic programming question — picking a shipped sample to copy and modify, wiring pkg-config + meson (or FFI from Rust / Go / Python against the public C ABI), walking the Core lifecycle (create → configure → start → connect → use → stop → destroy), or decoding a DOCA_ERROR_*. Trigger on implicit phrasing: "write my first DOCA program", "meson line for doca_rdma_*", "DOCA_ERROR_BAD_STATE on first call", "call DOCA from Rust", "built clean but nothing on the wire". Refuse install / hugepages / pkg-config (doca-setup), docs or version lookup (doca-public-knowledge-map), and library-internal API work (matching library 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。
Run and operate the DeepStream Multi-View 3D Tracking reference app, also known as MV3DT. Use when the user asks to set up prerequisites, run shipped MV3DT samples, run Multi-View 3D Tracking on custom synchronized MP4 datasets, import camera calibration, delegate missing calibration to AutoMagicCalib, inspect OSD or BEV visualization, consume MV3DT Kafka metadata, or clean up MV3DT run state in the DeepStream MV3DT app directory.
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。
Maintain a structured planning document tree made of roadmap/status files, implementation status or handoff TODO files, topic notes, decision records, open questions, ideas/inspiration pools, and repository/file-structure hygiene plans. Use when Codex needs to create, reorganize, audit, or update a multi-file plan, design-doc folder, roadmap tree, active implementation-status file, repo cleanup/filesystem plan, ADR/decision log, ideas inbox, or linked planning knowledge base; reconcile Done/In Progress/Next state; resume work from TODO/handoff state; move resolved questions into decisions; promote ideas into formal plan artifacts; or keep plan documents and file-structure planning internally consistent without making this project-specific.
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。
Idiomatic Golang design patterns — functional options, constructor APIs, `init()` and global-state avoidance, enums, panic vs error decisions, resource management and lifecycle, graceful shutdown, timeouts and retries, streaming and iterators, and architecture styles (clean, hexagonal, DDD, flat). Apply when choosing between architectural patterns, implementing functional options, designing constructor APIs, setting up graceful shutdown, applying resilience patterns, or asking which idiomatic Go pattern fits a specific problem. Not for wiring a DI container or comparing DI libraries (→ See `samber/cc-skills-golang@golang-dependency-injection` skill), nor for error wrapping, `errors.Is`/`As`, or logging mechanics (→ See `samber/cc-skills-golang@golang-error-handling` 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。
Compile-time dependency injection in Golang using google/wire — wire.NewSet, wire.Build, wire.Bind (interface→concrete), wire.Struct, wire.Value, wire.InterfaceValue, wire.FieldsOf, cleanup functions, //go:build wireinject injector files, and generated wire_gen.go. Apply when using or adopting google/wire, when the codebase imports `github.com/google/wire`, or when wiring an application graph at compile time via `wire.Build`. For runtime DI with reflection, see `samber/cc-skills-golang@golang-uber-dig` 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。