4,367 件 ・ 関連度順
概要と使いどころ
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。
Designing data stories and narrative-driven analytics in Salesforce: structuring CRM Analytics dashboards for executive communication, text widgets and conditional highlights for annotation, sequential narrative in Tableau Story sheets, and Einstein Discovery narrative REST endpoints. Trigger keywords: data storytelling dashboard, executive analytics narrative, CRM Analytics text widget annotation, Tableau story sheet, smart data discovery narrative API. NOT for building the Einstein Discovery story or prediction definition - use admin/einstein-discovery-setup. NOT for choosing between Reports, CRM Analytics and Tableau - use admin/einstein-analytics-basics.
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 a practitioner needs to classify the risk level of an upcoming Salesforce deployment, define rollback trigger conditions, or assign decision authority before the release window opens. Triggers: 'how risky is this release', 'what needs rollback planning', 'classify deployment risk', 'pre-deployment risk checklist', 'rollback decision authority', 'high risk metadata types'. NOT for executing the deployment itself, writing CI/CD pipeline code, or troubleshooting failures after a deployment has already run — use admin/change-management-and-deployment for execution planning and devops/deployment-error-troubleshooting for post-failure diagnosis.
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。
Execute the tasks from an already-created feature plan in .unikit/code/plans/ — read the plan manifest (the PLAN.md file in the plan folder), work through the uncompleted tasks in order, write the code, mark progress, and resume across sessions. Supports selective runs by phase or by task numbers, and continuing from where the last session stopped. Use whenever a plan exists and the user wants to build it, e.g. "implement", "implement the plan", "start coding", "execute the plan", "run the plan", "do the next task", "implement phase 3", "implement tasks 2.1 and 2.3", "continue implementation", "continue where we left off", "keep going on the feature". To create the plan first, use the planning skill — this one carries an existing plan out.
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。
AI Executive Assistant — calendar, travel itinerary, expense, briefing doc, gatekeeping email
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 you have a written implementation plan to execute in a separate session with review checkpoints
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 a Prometheus work plan in Codex with Boulder state, evidence ledger updates, worktree discipline, parallel subagents, and Stop-hook continuation. Use after planning when the user says start work, execute plan, continue plan, resume plan, or asks to run a .omo/plans plan.
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 you have a written implementation plan to execute in a separate session with review checkpoints
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。
CEO/founder-mode scope review. Challenges the scope of any plan, workflow, or feature before execution. Four modes: SCOPE EXPANSION (dream bigger), SELECTIVE EXPANSION (cherry-pick worthwhile expansions), HOLD SCOPE (maximum rigor within current scope), SCOPE REDUCTION (strip to essentials). Use before executing any multi-step workflow or when questioning whether the scope is right. Prevents scope creep and missed opportunities. Use proactively when the user defines a plan, creates a workflow, or says "is this enough?" or "am I thinking too small?".
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。
Drafts U.S. executive Change in Control Agreements with double-trigger severance, equity acceleration, and 280G/409A compliance. Use when drafting or negotiating CIC agreements, change in control protections, executive severance in M&A, or golden parachute provisions.
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。
Produces U.S. litigation case chronologies with dated timelines, executive summaries, source attribution, gap analysis, and investigation recommendations. Use when asked for a chronology, timeline, case summary, or executive summary of a legal matter, or during case intake, deposition prep, or trial prep.
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。
Summarizes raw background check data into structured executive reports with risk categorization (GREEN/YELLOW/RED). Use when processing criminal records, court filings, employment/education verification, sanctions screening, or adverse media for pre-employment screening, executive due diligence, or investment-grade investigations.
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。
Own goal-first engineering outcomes: investigate, find root cause, design, plan, then delegate implementation unit-by-unit to implementation-loop with verification and honest reporting. Use to fix, build, or own an outcome end to end; investigate-and-fix; "make X work"; or plan-then-execute in one request. A request with an approved plan or equivalently precise spec that needs nothing beyond implementation belongs directly to implementation-loop. Requires implementation-loop and an authenticated backend CLI to execute.
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。
Reference for MCP Jupyter tools (kernel management, cell execution, Papermill). Use when executing notebooks, managing kernels, or running code interactively via MCP.
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 Jupyter notebooks using local scripts or MCP Jupyter. Arguments: <notebook_path> [--mode] [--cells] [--timeout] [--batch] [--save]
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。
Combines and synthesizes outputs from parallel DAG branches. Handles merge strategies, conflict resolution, and result formatting. Activate on 'aggregate results', 'combine outputs', 'merge branches', 'synthesize results', 'fan-in'. NOT for execution (use dag-parallel-executor) or scheduling (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。
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。
Validates agent outputs against schemas and quality criteria, scores confidence, detects hallucinations, monitors convergence, decides when to iterate, and synthesizes actionable feedback. Use when checking if a node's output is acceptable, scoring confidence, detecting fabricated content, deciding whether to re-execute, or generating improvement feedback. Activate on "validate output", "check quality", "confidence score", "hallucination check", "should we iterate", "improvement feedback". NOT for executing DAGs (use dag-runtime), planning DAGs (use dag-planner), or matching skills (use dag-skills-matcher).
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。
ALIAS for dag-orchestrator. The original DAG execution skill, now unified with orchestrator into dag-orchestrator. Use dag-orchestrator for the full HTDAG experience.
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。