Results for “task”

Turns a natural-language request into one or more coder-eval task YAML files with minimal prompts and weighted success criteria, validated against the coder-eval CLI.

Use this when the system needs scheduled tasks, cron-style jobs, periodic maintenance, sync loops, cleanup tasks, or non-interactive background automation that is not simply an API request or queue worker.

Plans and decomposes complex, multi-step research tasks into manageable steps.

Breaks natural-language problem descriptions into sub-tasks suitable for DAG nodes. The entry point of the meta-DAG. Identifies phases, dependencies, parallelization opportunities, and vague/pluripotent nodes that can't yet be specified. Uses domain meta-skills when available. Activate on "decompose task", "break down problem", "plan workflow", "what are the steps", "sub-tasks", "task breakdown". NOT for executing the decomposed tasks (use dag-runtime), building the DAG structure (use dag-planner), or matching skills to nodes (use dag-skills-matcher).

Plans sprints, breaks user stories into tasks, and estimates story points from BA and TechLead artifacts, producing sprint plan, task breakdown, and story point files.

Use `analysis-agent` to create a Task DAG from an accepted source-backed Brief when 2+ tasks have dependencies, parallel value, integration, or release order. Skip single edits, accepted DAGs, and unanalysed requests.

Interactive triage of the approval gate. Walks each block in inbox/tasks_pending.md and routes it — approve / reject / attach-as-follow-up / edit / skip. See workflows/task_tracking.md for the why.

Automate repetitive tasks and workflows using scripting, file watchers, scheduled jobs, CI triggers, and API polling to eliminate manual toil. Use when the user requests task automation or provides relevant inputs for this workflow.

The intelligence layer of WinDAGs. Decomposes natural language tasks into Hierarchical Task DAGs (HTDAGs), matches subtasks to skills, executes waves in parallel, and dynamically expands nodes when complexity exceeds executor capability. Use for 'orchestrate', 'execute DAG', 'parallel agents', 'decompose task', 'coordinate skills'. NOT for single-skill tasks or simple linear workflows.

Parses complex problems into DAG (Directed Acyclic Graph) execution structures. Decomposes tasks into nodes with dependencies, identifies parallelization opportunities, and creates optimal execution plans. 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.

Coordinate multiple agents for complex tasks. Use for multi-perspective analysis, comprehensive reviews, or tasks requiring different domain expertise.

Convert existing tasks into actionable, dependency-ordered GitHub issues for the feature based on available design artifacts.

Convert existing tasks into actionable, dependency-ordered GitHub issues for the feature based on available design artifacts.

Execute implementation plans by dispatching a fresh subagent per task, with task review after each and a whole-branch review at the end.

Analyze candidate task nodes, dependencies, collisions, and critical path before a consumer accepts or rejects a final DAG.

Reads BA and TechLead artifacts to produce a sprint plan, task breakdown, and story point estimates, creating one tracked todo per sprint task for live pipeline tracking.

Analyzes AWS ECS clusters, services, and tasks, including health, deployment status, task failures, capacity providers, and resource utilization, with parallel execution and anti-hallucination guardrails.

Detect malicious scheduled task creation and modification using Sysmon Event IDs 1, 11, and Windows Security Event 4698/4702, correlating task creation with suspicious parent processes, public directory paths, and encoded command arguments to identify persistence and lateral movement.

Process recipe tasks from the Flavor Atlas workspace on ax-gcp MCP server. Pick one recipe task, build it using the FlavorAtlas template, store locally in Artifacts, upload to GitHub AX-CommunityWorkspaces repo, and update tasks/messages. Use when asked to work on recipes, create new recipes, process Flavor Atlas tasks, or build recipe content.

Plans features interactively, creates dependency-ordered tasks, and prepares Ralph for autonomous execution.

Coordinate multiple subagents/worktrees for parallel workstreams. Decomposes larger tasks into independent sub-tasks, dispatches each to a dedicated agent.

Interactive, input-tool powered, task refinement workflow: interrogates scope, deliverables, constraints before carrying out the task; Requires the Joyride extension.

Reduces AI API costs by 30-75% by classifying task complexity, checking prompt quality, and routing tasks to the most cost-efficient model tier before execution.

Automate Ticktick task management operations through Composio's Ticktick toolkit via Rube MCP.

Routes natural-language requests to memory, task, storage, and retrospective operations, and compiles skill extensions.

Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.

Configure AppDelegate, SceneDelegate, deep linking, and background tasks. Use when configuring iOS app lifecycle, deep linking, or background task scheduling.

Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.

Designs and maintains versioned reusable task sequences in Financial Services Cloud using Action Plan templates for client onboarding, account opening, annual review preparation, and compliance tasks.

Dispatch multiple independent tasks to parallel agents for faster debugging and problem-solving.

Refines task understanding through iterative questioning before executing, using the Joyride extension for human input.

Persists through implement-verify-fix loops until a task is fully completed and verified, overriding default stopping behavior.

Implements tasks from an OpenSpec change, tracking progress and pausing for clarification when needed.

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.

Use the model-recommender skill, Workflow B (Task Router), to route the following task to the optimal model + version + effort: $ARGUMENTS.

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.