Results for “task”

The intelligence layer of Jury-rig. Decomposes natural language tasks into proposed Hierarchical Task DAGs (HTDAGs), matches subtasks to skills, proposes wave and revision contracts, and expands nodes only when evidence supports a revised graph. Use for 'orchestrate', 'execute DAG', 'parallel agents', 'decompose task', 'coordinate skills'. NOT for single-skill tasks or simple linear workflows.

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ストーリーからTDD/E2E/TASK分岐付きタスクリスト（task-list.json）を生成。 ストーリー駆動開発の起点となるスキル。 「タスクを作成」「/dev:story」で起動。 Trigger: タスクを作成, ストーリーからタスク, /dev:story, story to tasks

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[70] CLOSE. Manage task lifecycle with correct statuses and no duplicates. Ensure each task has one status, artifacts match claims, and no task appears in multiple places. Use when managing task lists, updating progress, or ensuring task tracking integrity across systems.

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Meta-agent skill for orchestrating complex tasks through autonomous sub-agents. Decomposes macro tasks into subtasks, spawns specialized sub-agents with dynamically generated SKILL.md files, coordinates file-based communication, consolidates results, and dissolves agents upon completion. MANDATORY TRIGGERS: orchestrate, multi-agent, decompose task, spawn agents, sub-agents, parallel agents, agent coordination, task breakdown, meta-agent, agent factory, delegate tasks

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Manage Apple Reminders from your Mac with remindctl, a terminal tool. View tasks by date, add or edit reminders, organize lists, and mark tasks complete or delete them, including personal to-dos that sync to iOS.

• Review today’s tasks and overdue reminders
• Add personal to-dos with due dates
• Organize tasks visible on an iPhone or iPad

Carry out an implementation plan by assigning each task to a separate agent, then reviewing specification compliance and code quality. Keep progress in files and review the complete set of changes after all tasks are finished.

• Implementing a plan with mostly independent tasks
• Reviewing specification compliance after each task
• Resuming work from recorded progress

Design an LLM API workflow that controls spending through task-based model selection, budget tracking, selective retries, and caching repeated prompts. Use the examples to route simpler tasks to cheaper models and track cumulative costs.

• Reviewing costs in an LLM API application
• Choosing models by batch task complexity
• Tracking cumulative spending against a budget

Design task-specific workflows for repeated agent work, with pass/fail checks, progress records, and handoff notes. Identify when a temporary workflow should become a shared skill that teammates can run and evaluate again.

• Designing a workflow for repeated agent tasks
• Adding task-specific pass/fail checks
• Turning recurring work into a shared skill

Delegate work to an existing Paperclip agent by selecting a suitable assignee and creating a task with clear objectives, constraints, and deliverables. Receive a lasting task reference and check progress after the conversation ends.

• Assign requested work to an existing agent
• Create tasks with clear constraints and deliverables
• Keep a task link for follow-up after the conversation

Coordinate multiple Orca workers by assigning tasks, exchanging threaded messages, and waiting for results or escalations. Use task dependency graphs and decision gates to supervise work that needs ongoing coordination across agents.

• Splitting work across multiple Orca workers
• Coordinating tasks with dependencies
• Waiting for worker results or escalations

Use the command line to send tasks to OmniRoute's A2A server, which supports communication between agents. Inspect execution history and logs, monitor or cancel tasks, and interactively test the JSON-RPC 2.0 communication protocol.

• Check server status and available skills
• Invoke a skill with JSON input
• Inspect task history and logs

Automate supported Appointo tasks through Rube MCP and Composio. The skill finds available tools, checks the service connection, and follows current input requirements to execute requested operations, including batches of supported tasks.

• Find tools for an Appointo task
• Check the Appointo connection before running tasks
• Run multiple supported operations together

Investigate failed GAIA benchmark questions by inspecting execution records and classifying causes such as missing tools, reasoning errors, or answer extraction bugs. Follow targeted fixes, verify them through another run, and save findings for future debugging.

• Investigate an incorrect answer for a specific task
• Diagnose a question that timed out
• Investigate a drop in benchmark pass rate

Choose an agent and model tier using the task description and learned patterns. The skill can explain its recommendation, use compiler-based edits for supported simple changes, and record task outcomes to inform future routing decisions.

• Choose an agent and model before starting a task
• Review the reasoning behind a routing recommendation
• Apply supported code changes through the TypeScript compiler

Run one cycle of autonomous task work in Claude Code: check progress, select and execute the next action, log the work, and schedule another cycle. Stop when all tasks are complete or the iteration limit is reached.

• Continuing work from a Claude Code task list
• Working through Markdown checklist items
• Running tasks managed through MCP

Implement pending tasks from an OpenSpec change using its specifications and design documents. The skill updates task checkboxes, confirms progress, supports resuming unfinished work, and pauses when requirements or implementation issues need clarification.

• Start implementing a planned OpenSpec change
• Resume partially completed implementation
• Track completed and remaining tasks

Find available computers and remote environments, then start or continue a task in the requested location. Route work involving files or apps on the user's computer to that computer, and follow progress while preserving the selected environment.

• Start a task on a named remote environment
• Route work involving files on your own computer
• Select your computer for work with a desktop app

Coordinate a task from a verifiable goal through completion. Handle work directly or split independent tasks across separate agent sessions, track progress, verify results, and arrange pull request merging when included in the goal.

• Split independent tasks across agents
• Check progress across ongoing tasks
• Resume a previously started project

Store preferences, task lessons, and procedure outcomes in Hindsight, then retrieve relevant context before starting new work. It records detailed observations and can synthesize past experience into guidance for approaching the next task.

• Remembering preferences and project conventions
• Recording bug fixes and workarounds
• Keeping successful and failed procedure outcomes

Build Apache Airflow workflows for data pipelines and scheduled jobs. The skill guides task dependencies, retries, waiting for conditions, testing, and deployment, with patterns for tasks that can be safely rerun.

• Building scheduled data pipelines
• Designing task order and dependencies
• Implementing custom tasks and condition checks

Create and update GitHub issues for bugs, feature requests, and tasks. Organize owners, labels, dates, and priorities, connect related work, and track dependencies and project progress through MCP tools and the GitHub API.

• File bug reports and feature requests
• Update issue owners, dates, and priorities
• Organize parent tasks, subtasks, and dependencies

Coordinate multiple agents in tmux, a terminal session manager, using shared tasks and persistent messages. Assign work, monitor progress and blockers, verify worker results, and shut down the team after tasks and state updates are complete.

• Divide a task among multiple agents
• Track progress through a shared task list
• Coordinate workers with persistent messages

Coordinate a worker agent in a tmux-based OMX Team through startup acknowledgements, task claims, status transitions, and mailbox checks. Keep task ownership, completion evidence, and idle status visible to the team.

• Coordinate startup and task assignment for an OMX Team worker
• Record task ownership and completion evidence
• Check and acknowledge team mailbox messages

Execute an implementation plan in one session by assigning a fresh subagent, a separate task-focused agent, to each task. Check specification compliance first, then code quality, and repeat fixes and reviews before proceeding.

• Execute an existing plan with mostly independent tasks
• Check specification compliance before reviewing code quality
• Repeat fixes and reviews for each implementation task