'filesystem' 검색 결과

pytest testing patterns for any Python project: test structure, fixtures, parametrize, conftest.py, monkeypatch, tmp_path, markers, unittest.mock (MagicMock, patch), pytest-cov coverage, and best practices. Stack-agnostic — referenced by every Python plugin in the marketplace. Use this skill to: - Organise tests with conftest.py shared fixtures and a clear test/src layout. - Write parametrized tests to cover multiple inputs without duplication. - Mock external dependencies (HTTP, DB, filesystem) with unittest.mock and monkeypatch. - Measure and enforce code coverage with pytest-cov. Do NOT use this skill for: - Framework-specific test types (Django TestCase / WebTestCase, FastAPI TestClient, Flask test client — see framework plugin skills). - Language idioms — see python-foundation:python-conventions.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

File system operations guidance - read, write, search, and manage files using Claude Code's built-in tools.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Work with the @upstash/box SDK for sandboxed cloud containers with AI agents, shell, filesystem, and git. Use when building with Upstash Box, creating sandboxed environments, running AI agents in containers, or orchestrating parallel boxes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use this skill when tool outputs exceed 2000 tokens, tasks span multiple conversation turns, sub-agents need to share state, context window is bloating, plans need to persist across summarization, terminal/log output needs selective querying, or when user mentions "offload context", "dynamic context discovery", "filesystem memory", "scratch pad", "reduce context bloat", or "just-in-time context loading".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Optimize a pydantic-ai agent's instructions, tool descriptions, output type, and signature inputs using the gepa CLI. Trigger when the user asks to "optimize this agent", "improve tool descriptions", iterate on prompts driven by eval failures, or otherwise improve a pydantic-ai agent against a dataset. Operates in the user's repo with full filesystem access — YOU are the reflection model; the gepa CLI handles minibatches, evaluation, and Pareto bookkeeping.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use for Desktop Commander MCP capabilities — persistent shells and REPLs, long-running processes, filesystem beyond the workspace, structured files (.xlsx, .docx, .pdf, images) and large local data files such as CSVs, ripgrep search at scale, SSH, or cross-turn state.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

How to write a Grafema batch-mode plugin that reads the graph and filesystem, then writes new edges/nodes directly to RFDB. Use when: (1) need to add project-specific edges that generic analyzers can't produce, (2) need to read config files (JSON/YAML) and trace values into code, (3) implementing framework-specific resolvers (Django settings, Express routes, pipeline configs). Covers: grafema.config.yaml plugin config, RFDB field naming (src/dst NOT source/target), addEdges/addNodes API, RFDBServerBackend connection pattern.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

SurrealFS virtual filesystem for AI agents. Rust core + Python agent (Pydantic AI). Persistent file operations backed by SurrealDB. Part of the surreal-skills collection.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Work with the @upstash/box TypeScript/JavaScript SDK for sandboxed cloud containers with AI agents, shell, filesystem, git, cron schedules, snapshots, and a headless browser. Use when building with Upstash Box, creating a sandbox or isolated environment to run untrusted or agent-generated code, running AI coding agents in containers, giving an agent a cloud dev environment with a shell and repository, browser automation from a box, scheduling recurring jobs inside a box, saving and restoring snapshots, or orchestrating parallel boxes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Work with the upstash-box Python SDK for sandboxed cloud containers with AI agents, shell, filesystem, git, cron schedules, snapshots, and a headless browser. Use when building with Upstash Box in Python, creating a sandbox or isolated environment to run untrusted or agent-generated code, running AI coding agents in containers, giving an agent a cloud dev environment with a shell and repository, browser automation from a box, scheduling recurring jobs inside a box, saving and restoring snapshots, or orchestrating parallel boxes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when the user asks about NixOS, Nix language, flakes, nixpkgs, configuration.nix, nixos-rebuild, modules, options, overlays, derivations, mkDerivation, callPackage, home-manager, nix-darwin, devenv, packaging, cross-compilation, binary caches, garbage collection, NixOS containers, networking, firewall, systemd services, filesystems, LUKS, Wayland, X11, kernel, profiles, NixOS testing or VM tests, ISO images, Docker images, Raspberry Pi, Terraform, distributed builds, remote machines, pinning nixpkgs, rollback, generations, Nix Pills, or any topic related to configuring, packaging, deploying, or troubleshooting NixOS and the Nix ecosystem.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use this skill when the user wants local Obsidian note or metadata work done primarily through documented official desktop `obsidian` CLI commands, with limited local vault filesystem support when needed for parent folders, path checks, ambiguity resolution, verification, or safe vault structure operations. Best for local vault search, note reads, exact-path note updates, backlinks, tasks, properties, templates, and local history. Do not use it for runtime admin, devtools diagnostics, workspace/navigation administration, community tools, `obsidian://` launcher tasks, Headless Sync or Publish workflows, or plugin-specific APIs.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Path traversal and LFI playbook. Use when file paths, download endpoints, include operations, archive extraction, or wrapper behavior may expose filesystem control.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Linux lateral movement playbook. Use after gaining initial access to pivot across Linux hosts via SSH hijacking, credential harvesting, internal pivoting, D-Bus exploitation, sudo token reuse, and shared filesystem abuse.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Linux security mechanism bypass playbook. Use when facing restricted bash/rbash, read-only or noexec filesystems, AppArmor, SELinux, seccomp filters, or audit logging that must be evaded during post-exploitation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Searches, retrieves, and synthesizes official Google developer documentation across Google Cloud, AI/Gemini, Android, Chrome, Web, Flutter, Go, Firebase, and other Google developer platforms. Integrates with the Developer Knowledge MCP server (search_documents, get_documents, answer_query) or the Developer Knowledge REST API fallback. Use when searching for gcloud CLI commands, API syntax, IAM permissions, official documentation, architectural comparisons, or product choice overviews. Don't use for local filesystem lookups or non-Google documentation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Run a task iteratively over a user-specified duration by dispatching subagents. The orchestrator stays strictly linear and time-checked, but each iteration fans out MULTIPLE subagents in parallel over independent units (and those subagents may fan out further). Shared state — a compact progress digest and a growing environment cheatsheet — lives on disk and is passed to every subagent BY REFERENCE, killing the per-subagent rediscovery tax. Every subagent first reads an initialiser preamble that points it at that shared state and makes it write findings back, so the cheatsheet populates itself; role prompts are produced ONCE on the filesystem by a single scaffold command and dispatched by path, never re-typed per dispatch. Subagents persist their results to disk and return only a tiny status, so the orchestrator's context stays small and lasts. The orchestrator classifies the goal as FINITE or OPEN-ENDED: finite lists may finish early; open-ended goals use the full duration, never idle, never manufacture busywork. Use when the user gives a task and a duration and wants it ground out iteratively by subagents over that time.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Canonical patterns for caching in Yuzu CI workflows. Two snippets — one for ephemeral GHA-hosted runners (split actions/cache/restore + actions/cache/save, never `save-always: true`) and one for self-hosted runners (local filesystem cache under `runner.tool_cache`, no GHA cache round-trip). Use when adding a new vcpkg/ccache/dependency cache step to any workflow under `.github/workflows/`, or when reviewing a PR that touches `actions/cache@`.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Execute a swarm plan wave by wave with filesystem isolation via git worktrees. For each wave, main context decides the scenario recipe + implementation contract for every task, then spawns one swarm-worker per task in parallel. Each worker executes its recipe and reports JSON status. Worktree merge-audit verifies write-set discipline before changes land on main. Aborts remaining waves on any audit or task failure.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Write scripts and programs against gatOS — the KSA mod that exposes live Kitten Space Agency simulation state as a 9P filesystem at /sim (also over HTTP /v1, MQTT, and an AI-oriented MCP server). Use this when asked to read game/celestial/vehicle telemetry, control vehicles (throttle, ignite, staging, attitude, burns, RCS, lights, docking), use game/debug controls (teleport, impulse kick, refuel, time-warp, switch vessel), direct the in-game camera / author cinematic shots and tracks, schedule timed command sequences, or write flight-computer / autopilot programs. Covers the full /sim catalog, the command model, KSA coordinate frames, and worked Bun/TypeScript + Rust examples.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Author tutorial-style documentation for the gatOS Astro/Starlight docs site (under site/) — the progressive `guides/` series that teaches writing flight-computer / autopilot programs against the gatOS /sim filesystem and its HTTP /v1 mirror. Use this when asked to write, add, or revise a gatOS tutorial or guide, plan the tutorial curriculum, or turn a /sim feature into a lesson. Covers the house style, Starlight/MDX mechanics, the dual-transport (/sim file + HTTP) presentation convention, the reusable code-snippet library, and the beginner→advanced tutorial ladder. Pairs with the `gatos` skill (how the sim works) and docs/TUTORIAL_DATA_REFERENCE.md (the data tutorials are built from).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Install npm packages in a Docker sandbox environment. Use this skill whenever you need to install, reinstall, or update node_modules inside a container where the workspace is mounted via virtiofs. Native binaries (esbuild, lightningcss, rollup) crash on virtiofs, so packages must be installed on the local ext4 filesystem and symlinked back.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when designing long-horizon agents that need subagents, isolated context windows, filesystem-backed work, persistence, human approval, MCP tools, or production tracing.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Manus-style file-based planning for multi-step work. Keep task_plan.md, findings.md, progress.md in your run workspace so the filesystem is your working memory. Use for any research/build with 5+ tool calls. Adapted for OpenMark sub-agents from Ahmad's planning-with-files v3.0.0.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.