Builds drip email campaigns for leads not ready to buy. Determines segment and buying stage, selects content per stage, and generates a complete 5-7 email sequence over 30 days with timing and content.
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メール、カレンダー、タスク管理、自動化(7,437 件)
概要と使いどころ
Builds drip email campaigns for leads not ready to buy. Determines segment and buying stage, selects content per stage, and generates a complete 5-7 email sequence over 30 days with timing and content.
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。
Weekly churn risk detection across active client accounts. Scans for signals like decreased engagement, missed meetings, delayed payments, and competitor mentions. Scores risk 1-10 and outputs prioritized alert list.
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Analyzes email sequence performance metrics. Evaluates open rates, click rates, reply rates, and conversion by step. Identifies drop-off points, benchmarks against industry averages, and recommends optimizations.
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Track Slack communities, Discord servers, Facebook groups, and forums for buying signals and engagement opportunities
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Find and validate email addresses using Snov.io via Chrome DevTools MCP. Takes LinkedIn profile URLs and returns verified emails. Replaces ZeroBounce.
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Framework-based cold email composer with 3 personalization tiers. Generates subject line, body, and follow-up variants. Never uses templates -- builds from frameworks (PAS, BAB, AIDA, Signal-Proof-Ask).
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Draft professional emails for various contexts including business, technical, and customer communication. Use when the user needs help writing emails or composing professional messages.
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Analytical methods for decomposing expert performance into cognitive and physical task components
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Expo managed workflow expert for EAS Build, Submit, Update, config plugins, and custom dev clients. Activate on: Expo project, EAS Build, EAS Update, config plugin, expo-dev-client, Expo Router, Expo SDK 52, app.json configuration. NOT for: bare React Native (use react-native-architect), native module authoring (use react-native-architect), Flutter (use flutter-bloc-state-manager).
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Decompose DAGs into execution chains using width bounds, stratification, virtual nodes, and matching. Use when minimizing workflow lanes in dependency graphs. NOT for cyclic graphs, generic scheduling, or one-off queries with no preprocessing payoff.
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Apply GPGP/TAEMS coordination as local-scheduler constraints under explicit task, view, commitment, and delivery assumptions. NOT for assuming global task visibility, reliable delivery, or modern execution authority.
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Monitors a specified object against explicit stopping criteria and distinguishes replica convergence, iterative progress, and workflow terminal state. NOT for execution or setting goals.
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Matches natural language task descriptions to appropriate skills using semantic similarity. Handles fuzzy matching, intent extraction, and capability alignment. Activate on 'find skill', 'match task', 'semantic search', 'skill lookup', 'what skill for'. NOT for ranking matches (use dag-capability-ranker) or skill catalog (use dag-skill-registry).
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Parses complex problems into candidate DAG (Directed Acyclic Graph) execution structures. Decomposes tasks into nodes with dependencies and identifies candidate parallelization opportunities. Activate on 'build dag', 'create workflow graph', 'decompose task', 'execution graph', 'task graph'. NOT for simple linear tasks or when an existing DAG structure is provided.
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Executes DAG waves with controlled parallelism using the Task tool. Manages concurrent agent spawning, resource limits, and execution coordination. Activate on 'execute dag', 'parallel execution', 'concurrent tasks', 'run workflow', 'spawn agents'. NOT for scheduling (use dag-task-scheduler) or building DAGs (use dag-graph-builder).
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Produce feasible non-preemptive DAG schedules from declared predecessors, durations, gates, capacities, and calendars. NOT for authorizing task execution or hiding resource and calendar infeasibility.
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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).
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Identifies when task outputs require iteration based on quality signals, unmet requirements, or explicit feedback. Triggers appropriate re-execution strategies. Activate on 'needs iteration', 'retry needed', 'not good enough', 'try again', 'refine output'. NOT for feedback generation (use dag-feedback-synthesizer) or convergence tracking (use dag-convergence-monitor).
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Methodology for eliciting expert knowledge about cognitive processes, decisions, and mental models in complex tasks
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Choose, compare, and decompose work into the right coordination topology: dag, workflow, manager-driven team, swarm, blackboard, team-builder, or recurring loop. Use when the coordination shape is unclear, when you need topology-native breakdown instructions instead of a generic DAG, or when planning topology and runtime topology may differ. NOT for actual execution, node-level skill matching, or framework/tool installation.
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Expert bot developer specializing in Discord, Telegram, Slack automation with deep knowledge of rate limiting, state machines, event sourcing, moderation systems, and conversational AI integration. Activate on 'Discord bot', 'Telegram bot', 'Slack bot', 'chat automation', 'moderation system'. NOT for web APIs (use backend-architect), general automation scripts (use python-pro), or frontend chat widgets (use frontend-developer).
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license: Apache-2.0 NOT for unrelated tasks outside this domain.
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Systematic methodology for eliciting, representing, and operationalizing expert cognitive skills—pattern recognition, situation assessment, mental simulation—from practitioners without requiring research training. Bridges academic rigor and practical usability.
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。
Systematic methodology for eliciting, representing, and operationalizing expert cognitive skills—pattern recognition, situation assessment, mental simulation—from practitioners without requiring research training. Bridges academic rigor and practical usability.
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。