4,061 件 ・ 関連度順
概要と使いどころ
Builds an automated malware submission and analysis pipeline that collects suspicious files from endpoints and email gateways, submits them to sandbox environments and multi-engine scanners, and generates verdicts with IOCs for SIEM integration. Use when SOC teams need to scale malware analysis beyond manual sandbox submissions for high-volume alert triage.
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。
Leverages Splunk Enterprise Security and SPL (Search Processing Language) to investigate security incidents through log correlation, timeline reconstruction, and anomaly detection. Covers Windows event logs, firewall logs, proxy logs, and authentication data analysis. Activates for requests involving Splunk investigation, SPL queries, SIEM log analysis, security event correlation, or log-based incident investigation.
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。
Investigate supply chain attack artifacts including trojanized software updates, compromised build pipelines, and sideloaded dependencies to identify intrusion vectors and scope of compromise.
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 Windows Security, System, and Sysmon event logs in Splunk to detect authentication attacks, privilege escalation, persistence mechanisms, and lateral movement using SPL queries mapped to MITRE ATT&CK techniques. Use when SOC analysts need to investigate Windows-based threats, build detection queries, or perform forensic timeline analysis of Windows endpoints and domain controllers.
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。
Investigate USB device connection history from Windows registry, event logs, and setupapi logs to track removable media usage and potential data exfiltration.
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。
Investigate compromised Docker containers by analyzing images, layers, volumes, logs, and runtime artifacts to identify malicious activity and evidence.
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 fix the bug described on this card
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 a support investigation as a suggest-and-interpret loop, never executing anything yourself — orient to the product's support pack and follow the signal with judgment. Use when someone asks for help triaging, investigating, or resolving an operational or support issue on a deployment. Not for feature-development cards (see investigate-and-fix and implement-this).
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 a live investigation as an operator-driven query loop: the operator runs each query on the live system and pastes the result back, and you guide the investigation one labelled query at a time. Use alongside support-assist (which covers what to investigate) whenever someone is pasting query or command output back from a deployment, especially during an incident. Covers labelling, pacing, making each query decide the next step, version-grounding, and keeping queries cheap and correctly classified.
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。
Multi-language test infrastructure for the Pump SDK — Rust unit/integration/security/performance tests, TypeScript Jest tests, Python fuzz tests, shell test orchestration, Criterion benchmarks, and CI quality gates.
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。
Full SolanaOS operator skill — install the runtime, query Solana blockchain data via SolanaTracker RPC, manage wallets, run OODA trading loops, configure multi-venue strategies (spot + Hyperliquid + Aster perps), control BitAxe mining fleets, pair Seeker devices, and interact with the SolanaOS Hub. Use when asked about SolanaOS installation, Solana wallet balances, token research, trading strategy, OODA loops, gateway setup, Telegram bot configuration, mining fleet management, or any SolanaOS runtime operation.
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。
Complete SolanaOS agent skill — install, configure, and operate the autonomous Solana trading runtime with Honcho v3 epistemological memory, multi-venue perp trading (Hyperliquid + Aster), on-chain intelligence with USD pricing, Telegram bot, gateway API, Tailscale mesh, hardware integration, and cross-session recall. Use when asked to install SolanaOS, query Solana blockchain data, manage wallets, run OODA trading loops, configure strategies, control BitAxe mining fleets, pair Seeker devices, or operate any SolanaOS runtime surface.
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。
Delegate coding tasks to Codex, Claude Code, or Pi agents via background process. Use when: (1) building/creating new features or apps, (2) reviewing PRs (spawn in temp dir), (3) refactoring large codebases, (4) iterative coding that needs file exploration. NOT for: simple one-liner fixes (just edit), reading code (use read tool), thread-bound ACP harness requests in chat (for example spawn/run Codex or Claude Code in a Discord thread; use sessions_spawn with runtime:"acp"), or any work in ~/clawd workspace (never spawn agents here). Claude Code: use --print --permission-mode bypassPermissions (no PTY). Codex/Pi/OpenCode: pty:true required.
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。
Explicit-only interview loop for stress-testing a plan, decision, or idea. Use only when the user asks to grill, interrogate, interview, or stress-test their thinking before action.
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。
使用有界本地报告诊断 Codex Flight Control 的安装、runtime、文档、持久状态、Wave、Guidance、Private Skill、角色策略、托管工作区、Evidence、Completion Gate 和恢复状态。用户询问飞控状态、健康、支持信息、恢复分析或阻断原因时使用；禁止上传数据或执行破坏性修复。
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。
使用状态绑定的最小 Tool Surface、exact Action Gateway、来源可追踪的 MissionSpec 与 Verification Manifest、宿主无关 Flight Progression Engine、可选且无权威的 App Server continuation、顺序持久 Wave、一层原生 Agent、困难后强制战术指导、证据型 Capability Profile、显式 Manual Verification、不可变宿主 Evidence、恢复检查点和仅本地 Git，治理复杂 Codex 开发。用户要求飞控接管、继续、自主开发、修复或完成多步骤软件项目，需要有界并行子代理，或实现前必须建立文档工程时使用。
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。
Review skills in any project using a dual-axis method: (1) deterministic code-based checks (structure, scripts, tests, execution safety) and (2) LLM deep review findings. Use when you need reproducible quality scoring for `skills/*/SKILL.md`, want to gate merges with a score threshold (for example 90+), or need concrete improvement items for low-scoring skills. Works across projects via --project-root.
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。
Coordinate Codex work across the current task, internal subagents, user-owned tasks, worktrees, handoffs, formal review gates, or recurring automation. Use for delegation, parallel roles, another Codex task, cross-repo work, QA/review handoffs, scheduled follow-up, or task inspection and continuation. Chinese triggers include 子Agent/子进程/子对话, 另一个对话接手, 并行处理, 分给QA, 多仓库收口, 巡检, 持续推进, 定时自动继续, 创建/读取/转交任务.
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。
Post-fix verification — re-scan the repo, gate on `--exploits weaponized --severity high`, recheck the specific CVE against the new installed version, write the verdict to `.vulnetix/memory.yaml`. Use when confirming a fix landed, validating a version bump did not introduce regressions, or producing a clean-scan attestation for compliance.
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。
Apply a set of Rosetta Stone attribute mappings to a Narrative dataset by wrapping them in a one-shot workflow that calls the `CreateRosettaStoneMappingsIfNotExist` task. Consumes the structured output of `/generate-rosetta-stone-mappings`, normalizes the generator's snake_case to the workflow task's camelCase, re-validates every expression against the dataset's current schema, gates on user approval, submits via `narrative_workflows_create`, polls the triggered run, and reports per-mapping created / conflict / failed. Use when: "apply these mappings to dataset N", "create the Rosetta Stone mappings I just generated", "push the mappings I saved earlier to <dataset>", "productionize this mapping list", "submit the suggested_mappings array". (narrative-common)
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 look-alike audience from a seed audience and a candidate population dataset. Classifies Rosetta Stone attributes, generates the same materialized-view scoring pipeline Lookalike Studio emits (Naive-Bayes categorical weights + Gaussian continuous similarity), gates on approval, submits via `narrative_workflows_create`, and monitors the build to completion. Use when: "create a lookalike audience", "find more users like this segment", "expand my seed audience to 500k similar users", "score the population against my customers", "build a look-alike of dataset X". (narrative-audience)
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。
Analyze Codex provider rollout JSONL and ego-benchmark-harness run artifacts to identify slow or failed individual tasks, tool retries, token/cost anomalies, and differences in agent execution paths. Use when users ask to analyze a Codex session or rollout, explain why a Codex task was slow or failed, inspect a Codex provider execution trace, compare Codex runs, count function_call or tool output events, or investigate agent-home/.codex/sessions.
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。
Analyze pi (coding-agent) session JSONL and ego-benchmark-harness run artifacts to explain slow or failed individual tasks, compare execution-path differences between agents or browser tools, and count tool calls and error types. Use this skill whenever users ask to analyze a pi session, explain why a task was slow or failed, compare two runs, investigate an error, locate the session corresponding to tasks.jsonl, inspect an agent execution path, count tool calls, analyze a run ID, or perform any forensic or retrospective analysis of JSONL under ~/.pi/agent/sessions/ or agent-home/.pi/agent/sessions/.
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 a research project as a folder on disk — open the run root first, record the user's own instruction verbatim, open the two frame gates and stop for the human to answer them, and keep the stage the ledger says it is. Use when the user asks to start, resume or check a research run, a paper, a review, a brief, a report, a literature review or a protocol.
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。