ReddRadar
Agent skills
Skills you can use with AI coding agents, indexed from public GitHub repositories.
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condition-based-waiting
Use when tests have race conditions, timing dependencies, or inconsistent pass/fail behavior - replaces arbitrary timeouts with condition polling to wait for actual state changes, eliminating flaky tests from timing guesses
Dmccarty30/Journeyman-Jobs 3
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github-project-management
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Dmccarty30/Journeyman-Jobs 3
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ReasoningBank Intelligence
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.
Dmccarty30/Journeyman-Jobs 3
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ReasoningBank with AgentDB
Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
Dmccarty30/Journeyman-Jobs 3
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testing-skills-with-subagents
Use when creating or editing skills, before deployment, to verify they work under pressure and resist rationalization - applies RED-GREEN-REFACTOR cycle to process documentation by running baseline without skill, writing to address failures, iterating to close loopholes
Dmccarty30/Journeyman-Jobs 3
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flow-nexus-swarm
Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform
Dmccarty30/Journeyman-Jobs 3
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root-cause-tracing
Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior
Dmccarty30/Journeyman-Jobs 3
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sequential-thinking
Use when complex problems require systematic step-by-step reasoning with ability to revise thoughts, branch into alternative approaches, or dynamically adjust scope. Ideal for multi-stage analysis, design planning, problem decomposition, or tasks with initially unclear scope.
Dmccarty30/Journeyman-Jobs 3
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using-git-worktrees
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Dmccarty30/Journeyman-Jobs 3
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Swarm Orchestration
Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.
Dmccarty30/Journeyman-Jobs 3
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github-release-management
Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management
Dmccarty30/Journeyman-Jobs 3
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receiving-code-review
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Dmccarty30/Journeyman-Jobs 3
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brainstorming
Use when creating or developing anything, before writing code or implementation plans - refines rough ideas into fully-formed designs through structured Socratic questioning, alternative exploration, and incremental validation
Dmccarty30/Journeyman-Jobs 3
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sparc-methodology
SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
Dmccarty30/Journeyman-Jobs 3
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test-driven-development
Use when implementing any feature or bugfix, before writing implementation code - write the test first, watch it fail, write minimal code to pass; ensures tests actually verify behavior by requiring failure first
Dmccarty30/Journeyman-Jobs 3
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performance-analysis
Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms
Dmccarty30/Journeyman-Jobs 3
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Collision-Zone Thinking
Force unrelated concepts together to discover emergent properties - "What if we treated X like Y?"
Dmccarty30/Journeyman-Jobs 3
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When Stuck - Problem-Solving Dispatch
Dispatch to the right problem-solving technique based on how you're stuck
Dmccarty30/Journeyman-Jobs 3
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using-superpowers
Use when starting any conversation - establishes mandatory workflows for finding and using skills, including using Read tool before announcing usage, following brainstorming before coding, and creating TodoWrite todos for checklists
Dmccarty30/Journeyman-Jobs 3
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AgentDB Memory Patterns
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
Dmccarty30/Journeyman-Jobs 3
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flow-nexus-neural
Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus
Dmccarty30/Journeyman-Jobs 3
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Scale Game
Test at extremes (1000x bigger/smaller, instant/year-long) to expose fundamental truths hidden at normal scales
Dmccarty30/Journeyman-Jobs 3
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stream-chain
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
Dmccarty30/Journeyman-Jobs 3
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sharing-skills
Use when you've developed a broadly useful skill and want to contribute it upstream via pull request - guides process of branching, committing, pushing, and creating PR to contribute skills back to upstream repository
Dmccarty30/Journeyman-Jobs 3