1.4K skills · sorted by relevance
Turn clear requirements into small implementation tasks with acceptance criteria, verification steps, dependencies, and estimated scope. Produce a written plan and ordered task list, with checkpoints and opportunities for parallel work identified before coding begins.
Organize code changes into focused commits and manageable branches, prepare pull requests, and maintain release versions and changelogs. The skill also covers separate working directories for parallel work and checks before committing.
Coordinate multiple AI agents with agentic-flow to run tasks in parallel or through ordered stages. Configure shared memory, team structure, workload distribution, retries, and task reassignment, then monitor how the group performs.
Coordinates multiple AI agents with agentic-flow to run tasks in parallel or through dependent stages. It covers team communication structures, shared memory, workload balancing, failure recovery, and performance monitoring for complex workflows.
Coordinates a named team of Codex workers with concrete responsibilities and shared progress records. It selects available collaboration tools, manages communication and separate working copies when needed, and handles integration, team archival, and cleanup after the work ends.
Research many companies, people, or topics in parallel using the same required fields. The skill coordinates individual research tasks, combines results into a consistent structure, and reports coverage, failed inputs, and remaining gaps.
Implement large parallel workloads in Java with Azure Batch. Manage groups of computing machines, organize jobs and tasks, inspect progress and output, adjust computing capacity, and schedule recurring jobs using SDK examples.
Set up Antigravity 2.0 Agent Manager alongside Antigravity IDE to coordinate parallel development agents. Assign roles and folder boundaries, review their changes in the editor, and use Git checkpoints to manage shared work.
Guide a development brief through specification, dependent tickets, implementation, review, and verification. Coordinate parallel work while keeping human approval at key decisions and recording agreed vocabulary, business rules, and the reasons behind technical choices.
Helps configure and troubleshoot DeepSpeed for training large models across multiple devices. Covers memory optimization, parallel training, and DeepNVMe storage transfers, with examples for tuning data movement and configuring models that divide work among specialized components.
Manage shell commands and AI agent tasks through a shared gbrain job queue. Track progress, steer agents, pause or resume work, and coordinate parallel tasks, with guidance for long operations, completion reporting, and reusable stage checkpoints.
Coordinate multiple Mastra Code workers to investigate and fix GitHub issues in parallel. Keep each issue in a separate working directory, track progress in reports, review changes, and manage pull requests, reviewer feedback, and automated checks.
Apply the same operation across multiple files using parallel worker agents. The skill finds matching files, divides the work, and reports successes, failures, and skipped files, with a preview option before edits.
Write Workflow scripts that divide research, reviews, or migrations among agents. The reference explains parallel and staged processing, independent verification, failure handling, budgets, and resuming runs so the script has a clear execution structure.
Delegate research, coding, and testing from Claude Code to opencode workers. Run independent tasks in parallel with separate Git working directories, combine findings, track token use, and compare solo execution with coordinated workers.
Reproduce chat errors, retries, parallel tool calls, and app creation in a running desktop application. Check how messages and cards appear, including interrupted replies, grouped steps, and error details.
Run batch processing, scientific simulations, and machine learning training on Google Kubernetes Engine. Configure parallel jobs, queues that manage resource access, and distributed computation, with guidance on scaling idle capacity down and recovering from interruptions.
Delegate coding, analysis, refactoring, or reviews from Claude Code to Codex CLI. The skill explains unattended execution, permission settings, output capture, parallel tasks, and independent checks of changed files and test results.
Route code changes and SQL analysis to isolated Kortix work sessions with clear requirements and workspace details. Coordinate parallel investigations or independent pull request reviews, then summarize deliverables, verification results, and differences between findings.
Coordinate development work by breaking tasks down, writing six-part Task Prompts, and managing P8 agent teams. This skill takes a technical lead role, directing parallel agents and their delivery without writing code itself.
Stress-test ideas, strategies, and plans by breaking them into individual claims for parallel expert agents to challenge. Receive the strongest supporting case, surviving counterarguments, and findings ranked by severity with suggested ways to address weaknesses.
Design systems where multiple agents work with separate task information. Choose coordination structures, define handoffs and shared state, and plan parallel work while checking whether communication costs and failure risks justify using more than one agent.
Write and review launch prompts for agents working autonomously for hours or days. Define successful deliverables, excluded partial results, stopping rules, worker handoffs, and evidence-based review requirements so completion can be assessed against explicit criteria.
Coordinate multiple coding agents through Superset in separate workspaces. Split work into bounded tasks, track dependencies and progress, send follow-ups, and collect structured results covering changed files, verification checks, blockers, and the order for combining work.