「pack」の検索結果

Drive the AgentWiki knowledge platform via its CLI (`@aiagentwiki/cli`, command `agentwiki`) and MCP server (`https://api.agentwiki.cc/mcp`). Use this skill whenever the user mentions AgentWiki, agentwiki.cc, app.agentwiki.cc, the `agentwiki` CLI, the `@aiagentwiki/cli` npm package, the AgentWiki MCP server, or asks to create/list/search/share/publish documents, manage folders or tags, upload files or images, deploy static sites, traverse a knowledge graph, or query their AgentWiki workspace from the terminal or as an AI agent. Triggers include phrases like "agentwiki login", "aw_… API key", "create a doc on agentwiki", "search my wiki", "publish to agentwiki", "agentwiki MCP", or any task that would otherwise require opening app.agentwiki.cc manually.

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, improve, package, and review Codex skills from rough ideas, workflows, scripts, README/API/CLI docs, or existing skill folders. Use when the user wants to create a new Codex skill, convert a repeatable workflow into a reusable skill, scaffold SKILL.md plus references/scripts/assets, validate a skill, or prepare a skill for sharing on GitHub.

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。

آپلود امن S3 assistant for Codex; apply when building Persian/RTL web products, localizing content or integrating the related Iranian workflow. Local independent adaptation inspired by publicly documented VibeFarsi topics.

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。

Handle user-facing GUI, sign-in, and file handoffs from an isolated Windows agent session; not ordinary headless 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。

This skill covers detecting anomalies in Modbus/TCP and Modbus RTU communications in industrial control systems. It addresses function code monitoring, register range validation, timing analysis, unauthorized client detection, and deep packet inspection for malformed Modbus frames. The skill leverages Zeek with Modbus protocol analyzers, Suricata IDS with OT rules, and custom Python-based detection using Markov chain models for normal Modbus transaction sequences.

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。

Detect anomalies in DNP3 (Distributed Network Protocol 3) communications used in SCADA systems by monitoring for unauthorized control commands, firmware update attempts, protocol violations, and deviations from baseline traffic patterns using deep packet inspection and machine learning approaches.

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。

Detect command injection attacks against Modbus TCP/RTU protocol in ICS environments by monitoring for unauthorized write operations, anomalous function codes, malformed frames, and deviations from established communication baselines using ICS-aware IDS and protocol deep packet inspection.

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。

Deploy a Software-Defined Perimeter using the CSA v2.0 specification with Single Packet Authorization, mutual TLS, and SDP controller/gateway configuration to enforce zero trust network access.

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。

Detects and analyzes Bluetooth Low Energy (BLE) security attacks including sniffing, replay attacks, GATT enumeration abuse, and Man-in-the-Middle interception. Uses Ubertooth One and nRF52840 sniffers for packet capture, the bleak Python library for GATT service enumeration, and crackle for BLE encryption cracking. Use when assessing IoT device BLE security, monitoring for BLE-based attacks on wireless infrastructure, or performing authorized BLE penetration testing. Activates for requests involving BLE security assessment, Ubertooth sniffing, GATT enumeration, or BLE replay detection.

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。

Execute an internal network penetration test simulating an insider threat or post-breach attacker to identify lateral movement paths, privilege escalation vectors, and sensitive data exposure within the corporate network.

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。

Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek, and NetFlow analysis techniques. Activates for requests involving network traffic analysis, packet capture investigation, PCAP analysis, network forensics, C2 traffic detection, or exfiltration detection.

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。

Skill authoring and optimization skill; use when creating, improving, testing, or packaging skills for DSH agents.

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。

Validate CTO Build Framework governance artifacts and file version-bound evidence (runs, reviews, evidence packets) without inflating claims. Use for independent re-execution, internal-consistency reviews, and verdict filing.

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。

Monitor a build process (webpack, turbo, docker) for warnings and errors as they stream. Summarize issues and fix them before the build finishes.

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。

Test-driven development in Python using uv as the package manager. Covers the red-green-refactor cycle, vertical slicing, and uv project 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。

Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.

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 or update ToolUniverse in Claude Science — create the conda env, install the tooluniverse pip package, and (re)build the tooluniverse-research skill by fetching the current workflow library from GitHub. Use for first-time setup, upgrading the ToolUniverse version, refreshing the bundled workflows after an upstream release, or reinstalling on a new machine.

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。

Help teams prepare materials for an SCF referral. Use when a team wants to approach a referrer (SCF Pilot, SDF staff, alumni who completed deliverables, ambassador, or ecosystem partner) with a strong package that makes it easy for the referrer to evaluate and endorse them. Covers the referral form fields, what referrers assess, and how to present your project for referral.

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 requestor, ship-from, ship-to, service, package, and handling instructions from shipping requests.

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 company information, submitted identity-document references, and beneficial ownership data from onboarding packets.

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。

Merge a commercial invoice, packing list, and bill of lading into a unified customs declaration.

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。

Starts a CARLA UE 5.8 server from a ue58-dev tree — the editor binary in -game mode (the working headless server), the packaged shipping build, or the full editor — with offscreen/nullrhi rendering, custom RPC and streaming ports, and native ROS 2 via the single-dash -ros2 flag. Probes a running server, and stops one cleanly despite the 15-character process-name truncation. Use when the user asks to "run/start CARLA UE5", "launch a ue58 server", "run headless", "publish ROS 2 topics from UE5", or a client cannot reach the simulator.

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。

Answers "can CARLA do X here, and is there a vetted procedure for it" before you promise anything, and detects client/server/tree version skew — a support matrix over the whole collection (covered by a skill / works but undocumented / present but untested / broken or removed), an index of the features that are verified BROKEN on 0.10.0 (gbuffers crash the server, map layers do nothing, Landmark.waypoint is None, standalone asset packages are gone), and a probe that reports what this machine's build flags and running server actually offer. Use when the user asks whether CARLA supports something, when a feature has no skill, when a UE4 tutorial's steps do not exist, or before improvising a procedure.

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。

Installs CARLA's ScenarioRunner (the official scenario engine) and picks the branch that matches the CARLA in use — master for 0.9.14-0.9.16 (UE4), ue5-master for 0.10.0 (UE5), leaderboard-1.0/2.0/2.1 when driving the Leaderboard. Clones or checks out the branch, installs requirements, wires PYTHONPATH (including the `agents` package the carla wheel does not ship), and verifies the import. Use when the user asks to "install scenario runner", "set up SR", "run CARLA scenarios", "use OpenSCENARIO", or has a scenario_runner that fails to import.

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。