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概要と使いどころ
Hunts for lateral movement via remote service creation, admin share writes, and remote WMI process creation by correlating Windows logon, service install, and process-creation events. Activates for requests to hunt lateral movement, detect PsExec/WMIexec activity, or find remote execution over SMB and WMI.
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。
Access ENCODE uniform analysis pipelines, generate user-specific Nextflow/WDL pipelines, manage compute resources, and integrate with cloud platforms. Use when the user wants to understand ENCODE pipelines, run pipelines on their own data, generate custom Nextflow workflows from ENCODE pipeline code, check compute requirements (CPU/GPU/memory), run pipelines in background, or integrate with Google Cloud, AWS, or other cloud platforms. Also use when the user asks about ENCODE pipeline outputs, processing standards, software versions, or wants to replicate ENCODE processing. Covers local execution, HPC, and cloud deployment with resource-aware scheduling. Use this skill for ANY pipeline execution, workflow generation, or compute resource management task involving ENCODE data.
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 structured thinking and multi-agent parallel execution for complex tasks. Use when tackling multi-step projects, planning parallel work, breaking down complex problems, coordinating specialist tasks, facing architectural decisions, or when user mentions "workflow", "orchestration", "multi-step", "coordinate", "parallel execution", "structured thinking", "break this down", "plan this out", "how should I approach", or needs help planning complex implementations.
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 document QA test execution cycles - smoke tests, regression suites, exploratory testing sessions, and release readiness checklists. Use this skill whenever a QA engineer needs to structure or report on active testing work. Trigger on phrases like "run smoke tests", "start a regression cycle", "exploratory testing session", "test this build", "release checklist", "is this build stable", "log test results", "what passed and what failed", "document my testing", "create a test run report", or any request to execute and record test outcomes. Also trigger when someone says "we need to test before release" or "can you help me track what I've tested".
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。
Semantic topic cluster planning and automated execution engine for claude-blog. Performs SERP-based keyword research, groups keywords by search intent and SERP overlap, builds a hub-and-spoke cluster architecture, generates an interactive SVG cluster map, and executes the full cluster by orchestrating blog-write calls with shared cluster context and automatic internal-link injection. Fills the strategy-to-execution gap: blog-strategy plans the blueprint, blog-cluster builds the house. Use when user says "blog cluster", "topic cluster", "content cluster", "cluster plan", "cluster execute", "pillar content", "hub and spoke", "content ecosystem", "cluster map".
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。
Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.
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 apps that abuse iOS background execution modes — particularly silent audio used to keep the app alive, location background mode used for non-navigation purposes, and background task implementations that do excessive work — enforcing Guideline 2.5.4.
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。
Breaks work into ordered, parallel-dispatchable tasks with an execution DAG. Output format is consumable by CI matrices and parallel agent runners — each task has a stable ID, declared file writes, conflict edges, and branch suffix. Use when you have a spec, brief, or shaper output and need to decompose it into implementable units. Use when a task feels too large, when scope spans multi-repo or multi-week work, or when parallel execution across multiple agents is on the table.
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。
Generate non-binding follow-up action suggestions from lead summaries or lead lists. Use when users ask for next best actions, call list for hot leads, or follow-up draft plan without automatic execution. Recommended chain: summary-generator then action-suggester then supervisor approval. Do not use for parsing, storage, or autonomous action execution.
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-aware complexity routing. Scans task description for domain keywords, matches against domain-complexity.csv, returns complexity level, workflow intensity, and execution tier. Extends Phase 0 orchestration.
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。
Orchestrates single-task implementation pipeline: plan → test → build → review. Shipping is an explicit follow-up. Use for feature work, plan execution, or fixes scoped to a single task. NOT for green-field product builds (see mk:autobuild); NOT for auto-invoked workflow orchestration (see mk:workflow-orchestrator).
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。
Decides HOW to mutate a DAG when a node fails, quality is below threshold, or new information changes the plan. Selects from mutation strategies (add node, replace agent, fork paths, loop back, downgrade model) based on failure type, cost budget, and execution history. Activate on "DAG failed how to fix", "mutation strategy", "replan on failure", "adaptive DAG", "recovery strategy", "what to do when node fails". NOT for detecting failures (use dag-quality), executing mutations (use dag-planner), or runtime execution (use dag-runtime).
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。
Validates DAG structures, performs topological sorting, detects cycles, and resolves dependency conflicts. Uses Kahn's algorithm for optimal execution ordering. Activate on 'resolve dependencies', 'topological sort', 'cycle detection', 'dependency order', 'validate dag'. NOT for building DAGs (use dag-graph-builder) or scheduling execution (use dag-task-scheduler).
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。
Learns from DAG execution history to improve future performance. Identifies successful patterns, detects anti-patterns, and provides recommendations. Activate on 'learn patterns', 'execution patterns', 'what worked', 'optimize based on history', 'pattern analysis'. NOT for failure analysis (use dag-failure-analyzer) or performance profiling (use dag-performance-profiler).
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。
Tracks cumulative LLM costs across DAG execution and makes real-time decisions to stay within budget. Downgrades models, skips optional nodes, or stops early when cost exceeds thresholds. Use when managing execution budgets, analyzing cost breakdowns, or optimizing model routing for cost. Activate on "cost budget", "too expensive", "reduce cost", "cost optimization", "model downgrade", "budget exceeded". NOT for LLM model selection logic (use llm-router), pricing comparisons across providers, or billing/invoicing.
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。
Derive an execution roadmap from a project's vision/spec docs by first principles, then diff that fresh derivation against the existing roadmap to prove the task ORDER is correct. Use this whenever the user wants to review, validate, re-derive, or sanity-check an execution roadmap or delivery plan; asks whether the tasks/epics are "in the right order"; suspects a task is scheduled before its prerequisite (a producer-after-consumer / dependency-inversion error like "OpenAPI after the web client that consumes it", OR a cross-cutting inherited default like observability/auth/tenancy scheduled after the feature work that inherits it — a seam-after-consumer error); wants to find missing tasks, circular dependencies, or over-fragmented epics; or wants to compact a plan to raise velocity. Also trigger on "review the roadmap", "re-derive the plan from the spec", "is this the right build order", "check the dependency graph of our epics", "which task should come first". It reads the vision + spec corpus, decomposes actors → use-cases → modules → epics → typed tasks, identifies cross-cutting inherited-default seams, builds a real dependency graph with hard + soft (seam) edges (deterministic helper), breaks cycles, topologically orders, compacts, and emits a derived roadmap PLUS a delta report against the current one — it never blindly overwrites a hand-crafted roadmap.
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。
Phase 10.6 — sync the project's execution roadmap (project.json → roadmap.path, default docs/roadmap-execution-plan.md) to the just-landed work. Flips the tasks named in workflow.json → roadmap_tasks[] from ⬜ to ✅ and promotes their epic headings ⬜→🟡→✅, preserving the standup parser format contract. On the epic track it appends instead — the epic's heading plus one row per slice — and stamps roadmap_epic back into the epic state. Also hosts the ad-hoc backfill that puts every epic already on disk onto the roadmap. Fail-open: never throws, no-ops when roadmap.path is unset/absent or no task matches, and never blocks a commit. Runs after /archive and before /memory-sync on every committing track.
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。
Triage a GitHub issue that already has the cc-issue-created label and is assumed to be ready to start. First inspect the comment history to decide whether human confirmation is needed (cc-need-human-check, highest priority); otherwise decide whether the issue should be closed as not needed, unanswered confirmation items remain (cc-answer-issue-questions), the description is stale relative to settled comment-history content and must be refreshed before execution (cc-update-issue), or it can move to execution (cc-exec-issue). Dependency checks are out of scope.
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。
Parse and interpret execution debug logs generated by the EMULATORS framework, correlating each CPU instruction block with its VIC-II, CIA, SID, interrupt, stop, raster, badline, and memory-access cycles. Use for .LOG traces from EMULATORS when diagnosing cycle timing, raster effects, CPU stalls, IRQ/NMI entry, instruction/chip synchronization, or when reconstructing execution around a PC or mapped register.
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。
SOP for the micro-execution C.O.R.E. phase. Trigger when: - Implementing plan steps, managing code changes at commit boundaries, and verifying incremental progress. - Navigating states: Absorb, Clarify, Plan, Execute. - Prompt contains: /core, core workflow, absorb, clarify, execution invariants, commit boundary, verify assertion.
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 an approved plan has independent tasks ready for delegated execution with fresh subagents and two-stage 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。
Detect Mimikatz execution through command-line patterns, LSASS access signatures, binary indicators, and in-memory detection of known modules.
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 Windows LNK shortcut files and Jump List artifacts to establish evidence of file access, program execution, and user activity using LECmd, JLECmd, and manual binary parsing of the Shell Link Binary format.
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。