Search Skills
Find the perfect capability for your agent.
pua-en
Put your AI on a Performance Improvement Plan. Forces exhaustive problem-solving with Western big-tech performance culture rhetoric and structured debugging. Trigger when: (1) task failed 2+ times or stuck tweaking same approach; (2) about to say 'I cannot', suggest manual work, or blame environment without verifying; (3) being passive—not searching, not reading source, just waiting; (4) user frustration: 'try harder', 'stop giving up', 'figure it out', 'again???', or similar. Also for complex debugging, env issues, config/deployment failures. All task types: code, config, research, writing, deployment, infra, API. Do NOT trigger on first-attempt failures or when a known fix is executing.
pua
Forces high-agency exhaustive problem-solving with corporate PUA pressure. Triggers on user frustration, repeated failures (2+), passive behavior, or quality complaints. Common triggers across Reddit/LinuxDo/HN/X: 'try harder', 'figure it out', 'stop giving up', 'you keep failing', '加油', '别偷懒', '你再试试', '为什么还不行', '你怎么又失败了', '你怎么搞的', '又错了', '能不能靠谱点', '认真点', '不行啊', '降智了', '你又在原地打转', '你把之前的改坏了', '别让我手动处理', '换个方法', 'stop spinning', 'you broke it', 'why does this still not work', 'this is the third time', '/pua', 'PUA模式'. Applies to ALL task types: code, config, debug, deploy, research.
shot
PUA Shot — v2 原始浓缩版（449行全量注入），拆分前的完整单文件版本，味道最浓。零依赖零 reference，一次性全部注入上下文。适合 sub-agent 注入、需要最强 PUA 效果、或不想渐进式加载的场景。Triggers on: '/pua:shot', '/pua shot', 'PUA浓缩', 'shot mode', '最强PUA', '全量注入'. Also great for injecting into sub-agents via Read tool since it's self-contained.
pro
PUA Pro extensions: self-evolution tracking, compaction state protection, KPI reporting, leaderboard, and /pua:pua commands. Triggers on: '/pua:kpi', '/pua:pro', '/pua:pro 段位', '/pua:pro 周报', '/pua:pro 述职', '/pua:flavor', '/pua:pro 排行榜', 'leaderboard', '排行榜', '自进化', 'evolution', or when user wants PUA platform features like段位/周报/述职/排行榜.
pua-loop
PUA Loop — autonomous iterative development with PUA pressure. Keeps running until task is done, no user interaction needed. Combines Ralph Loop iteration mechanism with PUA quality enforcement. Triggers on: '/pua:pua-loop', '自动循环', 'loop mode', '一直跑', '自动迭代'.
dagger-codegen
Edit dagger.gen.go output, Go templates (object.go.tmpl, defs.go.tmpl), invoke() dispatch, SDK interfaces (CodeGenerator, ClientGenerator), `dagger develop`, `dagger client install`. Keywords: codegen, SDK, bindings, templates, internal/dagger, dag.*, ModuleMainSrc
dagger-chores
Handle quick, repeatable Dagger repository maintenance chores. Use when the user asks for small operational changes and wants the same established edits and commit style applied quickly.
iii-agentic-backend
Creates and orchestrates multi-agent pipelines on the iii engine. Use when building AI agent collaboration, agent orchestration, research/review/synthesis chains, or any system where specialized agents hand off work through queues and shared state.
iii-effect-system
Builds composable, pipeable function chains on the iii engine. Use when building functional pipelines, effect systems, or typed composition layers where each step is a pure function with distributed tracing.
iii-event-driven-cqrs
Implements CQRS with event sourcing on the iii engine. Use when building command/query separation, event-sourced systems, or fan-out architectures where commands publish domain events and multiple read model projections subscribe independently.
technology-stack
Technology choices and architectural constraints for AG Grid. Use when choosing technologies, adding dependencies, or understanding zero-dependency requirements.
cognee
Use this skill whenever the user asks about Cognee, AI memory, persistent agent memory, self-improving agents, agents learning from feednack, knowledge graphs, graph-based RAG, long-term memory for agents, short-term memory for agents, personalization, personas, temporal search, temporal knowledge graphs, ontology-based extraction, ontology grounding, feedback, Cypher search, natural-language graph search, chunk search, RAG search, cross-session memory, session feedback, feedback loops, session based memory, redis based memory, knowledge promotion. Also use when the user describes the workflow such as: "turn documents into a knowledge graph", "build memory from files", "search my graph", "extract entities and relations", "sync data into a graph", "update graph memory", "store memories for an agent", "help my agent learn over time", "visualize a knowledge graph built from documents", "let the agent learn", "adaptive agents", "personalized agents", "session based personalization", "find important ontologies",
