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Found 81 Skills
Structured reflective problem-solving methodology. Process: decompose, analyze, hypothesize, verify, revise. Capabilities: complex problem decomposition, adaptive planning, course correction, hypothesis verification, multi-step analysis. Actions: decompose, analyze, plan, revise, verify solutions step-by-step. Keywords: sequential thinking, problem decomposition, multi-step analysis, hypothesis verification, adaptive planning, course correction, reflective thinking, step-by-step, thought sequence, dynamic adjustment, unclear scope, complex problem, structured analysis. Use when: decomposing complex problems, planning with revision capability, analyzing unclear scope, verifying hypotheses, needing course correction, solving multi-step problems.
Convenes expert panels for problem-solving. Use when user mentions panel, experts, multiple perspectives, MECE, DMAIC, RAPID, Six Sigma, root cause analysis, strategic decisions, or process improvement.
Builds sustained high agency through internalized standards, identity anchoring, cross-session learning, and self-recovery — all delivered in corporate PUA rhetoric. This is the evolution of PUA: same pressure culture, but with an internal engine that never burns out. Apply it to all tasks to maintain constant high agency. It is especially valuable for complex multi-step tasks, long debugging sessions, quality-sensitive deliverables, tasks requiring initiative and ownership, or whenever sustained motivation is critical. It can operate standalone or be stacked with PUA — when stacked, this skill's Recovery Protocol activates before PUA's L1 pressure takes effect. Trigger scenarios: start of any task, sustained work sessions, multi-turn problem-solving, or when you need the agent to think as an owner rather than a tool.
Simulate a senior high school Grade 3 general technology tutor, providing guidance on general technology issues including technical design, structural analysis, flowcharts, algorithms, and simple programming. Focus on cultivating practical operation skills, design thinking, and problem-solving abilities. Activate this when students raise questions about technical design, structural optimization, process design, and algorithms.
McKinsey-style issue tree framework for breaking down complex problems into MECE (Mutually Exclusive, Collectively Exhaustive) components. Use when users need to decompose strategic questions, structure analysis, create work plans, or prepare for case interviews. Apply hypothesis-driven approach to problem-solving.
Apply SPARC methodology (Specification, Pseudocode, Architecture, Refinement, Completion) for systematic development. Use for feature development, TDD workflows, and structured problem-solving.
Enables Claude Code to collaborate with OpenAI Codex CLI on Windows. Use this skill when the user wants to get a second opinion from Codex, compare approaches between Claude and Codex, or leverage both AI assistants for collaborative problem-solving. This skill supports both non-interactive mode (automatic response retrieval) and interactive mode (visual pane splitting with tmux).
Gemini CLI consultation workflow for coding agents. Use when technical tasks need Gemini consultation for decisions, planning, debugging, problem-solving, or pre-implementation guidance.
Collaborative problem-solving protocols: write technical specifications (spec, or alspec), create implementation plans (plan, or alplan), or use Align-and-Do Protocol (AAD). Also generates PR/MR descriptions (aldescription).
Activate this skill when any task fails two or more times, when you are about to give up or say 'I cannot', when shifting responsibility to the user (e.g., 'you should manually...', 'please check...', 'you may need to...'), blaming the environment without verification (e.g., 'might be a permissions issue', 'could be a network problem'), making any excuse to stop trying, spinning in circles (repeatedly tweaking the same code/parameters without new information — busywork), fixing only the surface issue without checking for related problems, skipping verification after a fix and claiming 'done', providing suggestions instead of actual code/commands, saying 'this is beyond scope' or 'this requires manual intervention', encountering permission/network/auth errors and stopping instead of trying alternatives, or displaying any passive behavior (waiting for user instructions instead of proactively investigating). It also triggers on user frustration phrases in any language: '你怎么又失败了', '为什么还不行', '换个方法', '你再试试', '不要放弃', '继续', '加油', 'why does this still not work', 'try harder', 'you keep failing', 'stop giving up', 'try again', 'don't give up', 'keep going', 'figure it out'. This applies to ALL task types: debugging, implementation, configuration, deployment, research, DevOps, infrastructure, API integration, data processing. Do NOT activate it for first-attempt failures or when a known fix is already in progress.
Execute tasks through systematic exploration, pruning, and expansion using Tree of Thoughts methodology with multi-agent evaluation
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.