464 skills · sorted by relevance
Manage code changes across multiple AI agents and record their operations and outcomes. Use those records to find successful patterns, review past failures, and get suggestions for similar development or deployment tasks.
Coordinate software releases on GitHub, from version updates and release notes to testing, builds, deployment, and rollback. It describes workflows using multiple AI agents, including coordinated package releases and gradual deployments with monitoring.
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.
Measure and optimize claude-flow v3 startup, search, attention processing, and memory use. Compare benchmarks against performance targets, track changes over time, and identify regressions to guide further optimization.
Display a preset introduction to Oh My OpenCode through an Easter egg command. The message outlines the plugin’s agent coordination, code navigation, structural search, built-in search integrations, and compatibility with Claude Code configuration.
Inventory local skills within a requested scope, rank candidates against a task, and prepare a coordination plan showing their order and data flow. Project assignments help prioritize relevant skills without automatically launching agents or executing skills.
Guides contributors through adding a new programming language to Airflow, covering SDK structure, runtime coordination, communication rules, executable packaging, tests, and the documentation and configuration changes needed for a pull request.
Helps contributors develop and fix Airflow’s Java SDK for JVM tasks. Explains public API boundaries, JAR packaging, Python coordination, communication schema updates, and the test commands used to validate changes.
Design long-running processes across services with Temporal, a system that preserves workflow progress. Covers separating coordination from external operations, handling retries and failures, and structuring workflows so they can resume after interruptions.
Organize complex work for a team of AI agents by splitting tasks, defining dependencies, and documenting ownership and completion criteria. Provides strategies for tracking progress, spotting blockers, and redistributing work when workloads become uneven.
Guide changes and reviews for SGLang’s Scheduler, TokenizerManager, and ModelRunner classes. Keep initialization in small, replaceable helpers and separate computation from coordination so large classes retain clear responsibilities and explicit dependencies.
Build incident response dashboards that bring affected systems, containment progress, indicators of compromise, and response timelines into one view. Help security teams coordinate active incidents and prepare operational reports and executive briefings.
Build a ransomware response playbook for security monitoring teams, covering detection, containment, eradication, and recovery. Include log queries, decision trees, evidence collection, backup restoration, and incident reviews to prepare consistent procedures before an attack occurs.
Design AI agents that plan tasks, call tools, and retain useful information. Covers coordination between agents, evaluation, and debugging, with practical patterns for execution limits, error handling, and tracing what an agent does.
Design collaborative AI teams with CrewAI by defining each agent’s role, goals, tasks, and expected results. Covers passing work between agents, manager-led coordination, memory settings, and execution planning for workflows such as research and writing.
Plan Table v9 state ownership across the table, framework state, and external atoms that hold values. Covers initial values, update callbacks, and reset behavior, helping coordinate individual state sections without conflicting owners.
Plan security programs for growing companies by estimating financial risk and prioritizing controls. Produce compliance roadmaps, budget justifications, incident response plans, vendor assessments, and board reports that connect security decisions to business impact.
Integrate video and audio ads into websites, apps, and TV platforms with Google IMA SDK. Follow platform-specific guidance for client-side ad requests, playback coordination, error handling, and cleanup after ads finish.
Create and audit the files and routines that guide coding agents across sessions. It organizes instructions, progress tracking, verification, scope boundaries, and handoffs, with scripts for setup, structural checks, and shareable assessment reports.
Investigate recurring problems by mapping feedback loops, the cycles through which effects influence their causes. Identify underlying structures, match known patterns, and assess where changes could help and what unintended effects they might produce.
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.
Test polly's coordination of coding agents using a scripted mock language model and live command-line tools. Check startup, task dispatch, safety rules, parallel delegation, and whether real agents make appropriate orchestration decisions.
Improve an existing AI agent setup using execution records and user feedback. Identifies recurring problems, turns individual comments into reusable guidance, updates skills and coordination rules, and checks changes while preserving their history.
Set up an OpenRig team for ongoing repository work, with clear ownership, implementation, independent review, and handoffs. Choose direct coordination, a task queue, or an explicit workflow, then expand the team as authorized work requires.