Discover and install skills, docs, and rules to enhance your AI agent's capabilities.
| Name | Contains | Score |
|---|---|---|
https-deeplearning-ai/sc-agent-skills-files Provides checklist for reviewing Typer CLI command implementations. Covers structure, Annotated syntax, error handling, exit codes, display module usage, destructive action patterns, and help text conventions. Use when user asks to review/check/verify a CLI command, wants feedback on implementation, or asks if a command follows best practices. | Skills | — |
https-deeplearning-ai/sc-agent-skills-files Generate pytest tests for Typer CLI commands. Includes fixtures (temp_storage, sample_data), CliRunner patterns, confirmation handling (y/n/--force), and edge case coverage. Use when user asks to "write tests for", "test my CLI", "add test coverage", or any CLI + test request. | Skills | — |
https-deeplearning-ai/sc-agent-skills-files Provides Typer templates, handles registration, and ensures consistency. ALWAYS use this skill when adding or modifying CLI commands. Use when user requests to add/create/implement/build/write a new command (e.g., "add edit command", "create search feature") OR update/modify/change/edit an existing command. | Skills | — |
https-deeplearning-ai/sc-agent-skills-files Generate educational practice questions from lecture notes to test student understanding. Use when users request practice questions, exam preparation materials, study guides, or assessment items based on lecture content. | Skills | — |
https-deeplearning-ai/sc-agent-skills-files Generate educational practice questions from lecture notes to test student understanding. Use when users request practice questions, exam preparation materials, study guides, or assessment items based on lecture content. | Skills | — |
https-deeplearning-ai/sc-agent-skills-files Analyze weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metrics (CTR, CVR) and compare to benchmarks, compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit), or get budget reallocation recommendations based on performance rules. | Skills | — |
https-deeplearning-ai/sc-agent-skills-files CraftedWell brand guidelines for presentations and documents. Use this skill whenever creating or styling documents (docx, pdf) or presentations (pptx) for CraftedWell. Apply warm, artisanal aesthetic with chocolate/caramel color palette, Georgia headings, and Arial body text. | Skills | — |
https-deeplearning-ai/sc-agent-skills-files Analyze weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metrics (CTR, CVR) and compare to benchmarks, compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit), or get budget reallocation recommendations based on performance rules. | Skills | — |
PolyArch/humanize Iterative development with AI review. Provides RLCR (Ralph-Loop with Codex Review) for implementation planning and code review loops. | Skills | — |
PolyArch/humanize Refine an annotated implementation plan into a comment-free plan and a QA ledger while preserving the gen-plan schema. | Skills | — |
PolyArch/humanize Generate a structured implementation plan from a draft document. Validates input, checks relevance, analyzes for issues, and generates a complete plan.md with acceptance criteria. | Skills | — |
PolyArch/humanize Consult Gemini as an independent expert with deep web research. Sends a question or task to Gemini CLI and returns a research-backed response. | Skills | — |
evo-hq/evo This skill should be used when picking or diagnosing a training move (SFT, LoRA, DPO/KTO/ORPO, RFT, GRPO/PPO/RLOO, RLHF), or when the user mentions fine-tuning, post-training, training recipe, reward design, or weight updates. Decision tree by reward shape, smoke-run gate, three failure diagnostics, five false-progress patterns. Provider recipes and I/O contract in references/. | Skills | — |
evo-hq/evo Protocol that evo optimization subagents follow when dispatched from /optimize. Auto-loaded by spawned subagents via their host's skill loader. The orchestrator may also invoke this skill to understand the brief shape its dispatched subagents expect + what they're required to emit -- useful when writing briefs or debugging a subagent's behavior. | Skills | — |
evo-hq/evo Read-only evo run reporting. Use when the user invokes /evo:report, asks what happened overnight, asks what improved recently, asks for the best/frontier candidates, asks for a quick score chart without opening the dashboard, or wants the scatter plot in chat output. Never run benchmarks, gates, Slurm commands, evo run, or ad-hoc verification scripts for report requests. | Skills | — |
evo-hq/evo Drive structured autoresearch iteration after evo:discover and the baseline commit. Use when the user invokes /evo:optimize or asks to try ideas, try variants, run experiments, use available GPUs, improve the current best/frontier, continue an evo search, or compare candidate changes in an evo workspace. The orchestrator plans and spawns optimization subagents; candidate edits/runs belong to those subagents. Width is set via subagents=N (1 for serial workloads, larger for parallel); the loop's structural value applies at any width. | Skills | — |
evo-hq/evo Non-user-invocable provider/setup reference for evo backend switching, prerequisite checks, and auth/install guidance. | Skills | — |
evo-hq/evo Initialize evo for the current repository by exploring the codebase, proposing unexplored optimization dimensions, constructing the benchmark inside a baseline worktree, and running the first experiment. Use when the user invokes /evo:discover, mentions setting up evo, wants to instrument a codebase for autonomous optimization, or asks to start a new evo run on a project. | Skills | — |
lyra81604/zhengxi-views 郑希观点库——基于易方达基金经理郑希 2012–2026 年全部公开观点原文语料,外加从语料蒸馏、有本人原话佐证的郑希投资方法的可溯源 research skill。能做: (1) 溯源问答——他怎么看 AI算力/光通信/新能源/半导体/ROE 等,引用其原话作答; (2) 讲解他的投资方法/框架/选股逻辑;(3) 前瞻应用——用他的方法分析当下任意主题/行业/个股,语料没谈过也能据框架推演; (4) 风格化点评——用他季报/手记的口吻写市场点评、季度展望; (5) 言行对照——用他全部基金真实数据(季度持仓/净值/业绩/规模/任职回报)核对"说的"与"买的",或答他的业绩/重仓/规模; (6) 全市场查询对比——内置约 2.7 万只基金列表,按需抓任意基金真实数据做查询或与郑希对比; (7) 郑希框架评分——给一只基金按他的方法打分(多像郑希会买的)。 When the user mentions 郑希/易方达郑希/zhengxi, asks his view on a sector/stock/theme, his 投资方法/框架/选股/风格/持仓/业绩/净值/规模, wants to apply his approach, a commentary 用郑希口吻, to check words vs holdings, or to look up/compare/score ANY China mutual fund (任意基金/某基金经理/同类对比/给基金打分)——use this skill, even if they don't say "skill", even if the topic isn't in his corpus (fall back to his method). 引用忠于原文、不杜撰;推演与原话区分。研究学习辅助,非投资建议。 | Skills | — |
wuji-labs/nopua The anti-PUA. Drives AI with wisdom, trust, and inner motivation instead of fear and threats. Activates on: task failed 2+ times, about to give up, suggesting user do it manually, blaming environment unverified, stuck in loops, passive behavior, or user frustration ('try harder', 'figure it out', '换个方法', '为什么还不行'). ALL task types. Not for first failures. | Skills | — |
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