Agent Workflow Claude Skills
4 121 agent workflow skills from 665 authors. They configure the agents themselves: memory, prompts, context and other skills. Half of them fit into 1 845 tokens or less — that is what one costs your context window when the agent loads it. 778 ship runnable scripts rather than instructions alone. 5 of them cannot work without an MCP server, most often task. We also found 541 copies of these same skills sitting in other people's repositories — counted once here, not 541 times.
4 121 unique 665 authors 2 767 updated this month 506 from vendors
Designs high-performing team structures using organizational psychology AND creates new skills on-the-fly when team needs unmet expertise. Expert in team composition, personality balancing, collaboration ritual design, and skill creation for missing capabilities. Use for team design, role definition, skill gap identification. Activates on 'team building', 'team composition', 'skills needed', 'what skills'. NOT for general project management or solo work planning.
Summarizes very long texts (books, handbooks, biographies, codebases) using hierarchical multi-pass extraction with cheap model armies. Produces structured knowledge maps, not just summaries. Use when processing 50+ page documents, professional handbooks, career biographies, or any text too large for a single context window. Activate on "summarize book", "summarize handbook", "long document", "extract knowledge", "distill text", "professional biography". NOT for short text summarization (<10 pages), real-time chat summarization, or code documentation (use technical-writer).
Design, create, audit, and improve Claude Agent Skills with expert-level progressive disclosure. Use when building new skills, reviewing existing skills, debugging activation failures, encoding domain expertise, designing skills for subagent consumption, or understanding platform constraints and distribution surfaces. NOT for general Claude Code features, runtime debugging, non-skill coding, or MCP server implementation.
Use this skill when creating a new Claude skill from scratch, editing or improving an existing skill, or measuring skill performance with evals and benchmarks. Invoke whenever the user says things like "make a skill for X", "turn this workflow into a skill", "test my skill", "improve my skill", "run evals", "benchmark this", or "optimize my skill description". Also use proactively when the conversation has produced a repeatable workflow that would benefit from being captured as a skill. Covers the full lifecycle: capture intent → draft SKILL.md → run evals → review with user → iterate → optimize description → package. NOT for general coding help, debugging runtime errors, building MCP servers, writing Claude hooks, or creating plugins — use domain-specific skills for those.
Design, create, audit, and improve Claude Agent Skills with expert-level progressive disclosure. Use when building new skills, reviewing existing skills, debugging activation failures, encoding domain expertise, designing skills for subagent consumption, or understanding platform constraints and distribution surfaces. NOT for general Claude Code features, runtime debugging, non-skill coding, or MCP server implementation.
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Design, create, audit, and improve Claude Agent Skills with expert-level progressive disclosure. Use when building new skills, reviewing existing skills, debugging activation failures, encoding domain expertise, designing skills for subagent consumption, or understanding platform constraints and distribution surfaces. NOT for general Claude Code features, runtime debugging, non-skill coding, or MCP server implementation.
> Guide for creating, improving, benchmarking, and packaging Claude Agent Skills (SKILL.md files). Invoke when users want to create a skill from scratch, improve or test an existing skill, benchmark skill performance with variance analysis, or optimize a skill description for triggering accuracy. Also invoke when users say "turn this into a skill", "make a skill for X", "help me write a SKILL.md", "my skill isn't firing correctly", or want to convert a workflow/conversation into a reusable skill. Invoke proactively when a conversation has produced a repeatable workflow worth capturing. If the user mentions SKILL.md, skill files, skill descriptions, or skill triggering, this skill applies.
Expert in 3D computer vision labeling tools, workflows, and AI-assisted annotation for LiDAR, point clouds, and sensor fusion. Covers SAM4D/Point-SAM, human-in-the-loop architectures, and vertical-specific training strategies. Activate on '3D labeling', 'point cloud annotation', 'LiDAR labeling', 'SAM 3D', 'SAM4D', 'sensor fusion annotation', '3D bounding box', 'semantic segmentation point cloud'. NOT for 2D image labeling (use clip-aware-embeddings), general ML training (use ml-engineer), video annotation without 3D (use computer-vision-pipeline), or VLM prompt engineering (use prompt-engineer).
Guides creation of high-quality Agent Skills with domain expertise, anti-pattern detection, and progressive disclosure best practices. Use when creating skills, reviewing existing skills, or when users mention improving skill quality, encoding expertise, or avoiding common AI tooling mistakes. Activate on keywords: create skill, review skill, skill quality, skill best practices, skill anti-patterns. NOT for general coding advice or non-skill Claude Code features.
| Управление сессиями AI агентов через agent-deck CLI. "проверь сессию", "проверь статус", "покажи вывод агента", "что агент ответил". "check session", "show agent output".
| OAuth2 (app-only / user mode), кеш-first, опциональные write-операции с двойным предохранителем (REDDIT_ENABLE_WRITE=1 + --confirm). reddit search, парсинг reddit, посты reddit, комментарии reddit, реддит.
為使用者產生高品質的 AI 生圖、生影片、生音樂提示詞，並在需要時透過瀏覽器自動化實際送到目標平台。涵蓋 OiiOii、Kling 3.0/O-series、Seedance 2.0 pro、Suno v5.5、Seedream 5.0/4.0、Vidu Q3、Midjourney V8.1、Flux 1.1 Pro / Kontext、Runway Gen-4.5 / Aleph、Google Veo 3.1、Ideogram 3、Nano Banana Pro、Stable Diffusion 3.5（⚠️ OpenAI Sora 2 已於 2026-04-26 停運，API 撐到 2026-09-24，預設改推 Runway/Veo/Kling）。只要使用者提到「AI 生圖」「AI 影片」「AI 音樂」「做 MV」「做 storyboard」「寫 prompt 給 XXX」「我想用 Kling/Suno/Midjourney/Runway/Veo...」「幫我操作 OiiOii / 即夢 / 可靈」「txt2img / img2video / 文生圖 / 文生影片 / 圖生影片」「角色一致性」「多鏡頭分鏡」「運鏡」「結果有瑕疵 / 不夠精緻 / 怎麼修」，或任何跟上述平台或影像/影片/音樂生成工作流相關的任務，都要用這個 skill。即使他們沒講明平台，只要任務是要餵給某個生成模型的 prompt，就用這個 skill 幫他們選對的平台、寫對的格式。
Brief description of what this skill does and when to use it.
>- 百度网盘(Baidu Drive)文件管理 — 上传、下载、转存、分享、搜索、移动、复制、重命名、创建文件夹。 同时支持 Agent 记忆备份/恢复（kimiclaw/maxclaw/qclaw/openclaw）。 或用户提及"备份记忆"、"恢复记忆"、"查看记忆备份"等记忆相关操作。
CUMCM 国赛、MCM/ICM 美赛与电工杯数学建模竞赛的端到端协作工作流。Use when a user explicitly works on one of these modeling contests or asks to run/review a modeling-competition paper from problem selection through modeling, solving, robustness, writing, compliance, and final submission review. Provides 10 stages, persistent decision state, competition-specific rules/templates, deterministic scoring helpers, numbered decisions, and Codex/Claude Code handoff. Do not trigger for generic model selection, ordinary data analysis, or non-competition paper review.
Plugin shim for the mathmodel-skill competition workflow. Use when Codex invokes this plugin for a CUMCM, MCM/ICM, or Diangong Cup modeling-contest task, including problem selection, modeling, robustness, contest-paper writing, compliance, or final submission review. Do not use for generic data analysis or non-competition paper review.
Run a lightweight Ultracode workflow for serious coding tasks: plan, split, delegate when useful and allowed by the host, integrate, and verify. Use when the user explicitly invokes ultracode, $ultracode, ultra code, dynamic workflow, workflow orchestration, multi-agent workflow, subagent workflow, parallel agents, swarm, delegate this, split this across agents, or independent verification pass.
Review ClawHub or local Skill packages before installation, classify risk, and return a structured security report.
审查、安装、配置、激活、验证、更新和回滚 AgentDock Skill 时使用；负责来源校验、安全评估、环境配置和已安装版本验收。
Validate any Lattice SKILL.md against all tier conventions — atoms, molecules, and refiners. Catches structural errors, broken cross-references, and convention violations before they reach the repo. If you just wrote or modified a Lattice skill file and haven't run this yet, run it now — manual review consistently misses the same categories of errors this skill is specifically designed to catch. Use when the user says 'validate this skill', 'check this skill', 'does this follow conventions', 'review this skill file', 'check my SKILL.md', or 'skill validate'. Reports PASS/FAIL with specific file-and-section findings and actionable fixes. Standalone — does not call other skills.
Audit and fix all Lattice documentation, README, docs/, PROJECT.md, GitHub issue templates, and CLAUDE.md to ensure they are fully aligned with the current skill inventory. Documentation drift is the most common source of user confusion in Lattice — a skill exists in the codebase but not in the docs, or a renamed skill leaves a stale reference in the bug report template. If you've made any change to skills/ and haven't run this, run it now. Use when the user says 'align docs', 'audit docs', 'update documentation', 'skill align', 'check docs are in sync', 'audit skill inventory', 'ensure docs are aligned', 'are the docs up to date', or 'what needs updating'. Standalone — does not call other skills.
Create a new Lattice skill — atom, molecule, or refiner — following all framework conventions. Writing skill files manually almost always produces convention violations: wrong section order, missing confirmation gates, defaults.md without the right structure. This skill knows all of that and guides you through it. Use whenever adding any new atom, molecule, or refiner to Lattice, or when the user says 'create a new skill', 'add an atom', 'add a molecule', 'add a refiner', 'build X for Lattice', 'new lattice skill', or 'skill forge'. Does not validate, align docs, or deploy — those are separate skills you run after.
Audit any Lattice SKILL.md for language compliance — removes rationale prose, converts soft language to imperatives, adds STOP: gates on hard rules, and cuts redundant repetition. Complements skill-review (which finds behavioral gaps) by fixing phrasing that causes agents to skip or underweight instructions at runtime. Use after writing or significantly changing any skill, or when the user says 'tighten this skill', 'clean up the language', 'make this more effective', 'reduce the bloat', 'tighten the language', or 'skill tighten'. Standalone — does not call other skills.
Deep behavioral audit of a Lattice skill — proposes 3 review personas relevant to the skill, runs independent scenario analysis from each persona's perspective, then merges only the high-confidence, practical findings into a severity-ordered gap report with proposed fixes. Structural validation (conventions, cross-references) is skill-validate's job — this skill finds gaps that would realistically surface when someone actually uses the skill: missing scenario handling, ambiguous instructions, silent failure cases, and behavioral inconsistencies. Filters out theoretical edge cases, low-likelihood speculation, and findings owned by other skills. Use after writing or significantly changing any skill, or when the user says 'review this skill', 'deep review', 'does this skill work', 'find gaps in this skill', 'stress test this skill', 'review from different angles', or 'skill review'. Standalone — does not call other skills.
Use this skill to perform actions inside an Unreal Engine project via a live-editor MCP connection. Trigger when the user wants to change, query, or run something in their Unreal Engine project, not for conceptual or docs questions. Concrete triggers: spawn/move/duplicate/transform actors in a level, open a `.uproject`, add things around a PlayerStart, create or edit a Blueprint/Widget/Material/Niagara/Control Rig/Sequencer/Behavior Tree/GAS ability, read or write properties on actors (e.g. `bIsLocked` on `BP_DoorActor`), Live Coding recompile after editing C++ (`AActor`, `UMyComponent::Method`, `UPROPERTY`), or modify Static/Skeletal Mesh assets. Treat as Unreal context even without the word \"Unreal\": asset prefixes `BP_`, `WBP_`, `M_`, `MI_`, `NS_`, `CR_`, `SK_`, `SM_`, `ABP_`; UE C++ types/macros; `.uproject`; Content Browser; Outliner; PlayerStart; \"in my game\" plus UE signals. Skip for: pure conceptual/docs questions, Unity, Godot, or unrelated uses of \"blueprint\"/\"sequencer\"/\"widget\".
Use this skill when authoring or extending an Unreal Engine toolset, a class of static, AI-callable functions registered with `ToolsetRegistry` and exposed through the unreal-mcp server. Trigger when the user wants to add, expose, or register a new tool method, create a new toolset, or extend an existing one such as `BlueprintTools`, `StaticMeshTools`, `ObjectTools`, `LevelTools`, or `MaterialTools`. Concrete triggers: 'add a tool to X', 'expose this via MCP', 'register a function so Claude/the agent can call it', 'wire this into the toolset registry', 'create a new toolset for Y', 'add a Python toolset', 'make this AI-callable'; adding a `static` method to a `*Tools.cpp/.h/.py` file; editing files under a `Toolsets/` folder; designing tool parameters, return types, or struct schemas for a toolset. SKIP for: invoking existing tools at runtime (use unreal-mcp instead), authoring an Agent Skill (use unreal-skill), generic refactors that happen to touch a toolset file but don't add or redesign a tool, or unrelated uses of the word 'toolset'.
Use this skill when creating, editing, or reviewing an Unreal Engine Agent Skill, a named bundle of instructions registered with the unreal-mcp server (distinct from Claude Code's harness skills under `.claude/skills/`). Trigger when the user wants to add or change a skill that the in-editor agent will load. Concrete triggers: 'create a new Agent Skill', 'add a skill for X workflow', 'edit/update this skill', 'review my skill', 'make a Python skill class', 'create a skill UAsset', 'register a skill so Claude picks it up'; writing or editing a `SKILL.md` inside a UE plugin's `Skills/` or `Python/skills/` folder; defining a Python skill class registered with the skill registry; calling `CreateSkill`, `ListSkills`, or `GetSkills` MCP tools; designing a skill's name, description, or instruction body. SKIP for: authoring a toolset (use create-toolset), invoking an existing skill at runtime (use unreal-mcp), editing harness-level Claude Code skills under `.claude/skills/` or `~/.claude/skills/`, or generic uses of the word 'skill'.
Cast genjutsu on a UI - creative coding for motion, micro-interactions, and wow-factor. Scans the stack, proposes an interaction thesis, loads the right sub-skills, implements the illusion. Adapts to Web, Android (Compose), Apple (SwiftUI).
Split complex work into coordinated agent lanes with WIP checks, quality gates, rollback plans, and handoffs that prove what shipped.
Claude-directed parallel OpenAI Codex CLI worker fleet for bulk generation. Use when a job is high-volume, well-specified, and splits into independent worker-sized tasks (content batches, test generation, bulk refactors) and Codex CLI is installed and logged in. Claude decomposes, briefs, spawns codex exec runs in parallel, and review-gates every output. Workers are always codex exec processes billed to the user's OpenAI subscription — never substitute Claude subagent fan-out on any model, and halt rather than fall back if Codex CLI is unavailable. NOT FOR: multi-lane Claude agents coordinating one complex change (use suede-agent-teams); low-volume, judgment-dense copy Claude should write itself (use suede-copy or johnny-suede-write).
Outcome-bound router for broad, authorized work. Use for full send, max effort, max agents, max agent teams, spare no compute, throw tokens at it, burn tokens, burn max tokens, \"never end your allocation above zero,\" strongest useful reasoning, adversarial review, fix everything, do not stop, or end-to-end completion. Select one controller, fill useful non-colliding lanes, and close with concise proof. Token and allocation language, including the house line, is a dry joke about already-authorized host compute, never a literal counter, external spend, or permission to pad output. Explicit Full Send intent on atomic work selects one specialist and no parallel lanes.
Package finished work so people can use it: README, docs, install commands, proof links, QA, release copy, and handoff notes.
Catch MCP drift before release: skill catalogs, tool and resource schemas, prompts, install paths, JSON-RPC behavior, and docs alignment.
Suede-affiliated onboarding and activation strategy for first-run sequencing, empty states, setup checklists, activation milestones, time to value, and retention-linked measurement. Use when users sign up but fail to reach first value or the product needs a new first-session flow. NOT FOR: registration optimization (use suede-signup), lifecycle email sequences (use suede-emails), or monetization prompts (use suede-paywalls).
Next-action selector for this pack: reads current repo, terminal, plan, or handoff state, scores 2-4 candidate moves against goal alignment, unblocking, evidence, urgency, and leverage, and returns one recommended action plus a short, self-contained copy/paste prompt — expanding into a full operator prompt or granular steps only on request. Use when the user asks 'what's next', 'what should I do next', 'recommend the next move', 'give me the prompt', 'expand prompt', or 'make it granular', especially after a review, audit, plan, or stalled task. NOT FOR: executing the recommended action without the user's separate authorization, or coordinating a multi-lane build across specialists (use suede-agent-teams).
Package creative projects into an evidence-scoped rights handoff with normalized works, recordings, releases, parties, identifiers, claims, licenses, consent, provenance, privacy, and validation.
>- Review a proposed Agent Skill for structural validity and content quality before publishing. Runs the skill-validator CLI to check for structural issues, scores the skill with an LLM judge, and interprets results to advise SMEs on what to address. Use when a user wants to review, validate, or quality-check an Agent Skill.
Use when a dev is new to the project, asks for an overview, or wants to get oriented quickly. Fills graph gaps then runs a guided codebase interview.
Use when asked to audit a module, check its health, or assess whether it should be refactored. Runs structural query, risk check, and test generation automatically.
> This skill will add jspecify dependency, configure Maven or Gradle build to automatically use jspecify for checking Nullability issues.
Use this skill when the user wants to author, design, scope, or refine an Agent Skill (a SKILL.md file). Trigger phrases include "build a new skill", "design an agent skill", "scope a SKILL.md", "how should I structure this skill", "write a skill for X", "my skill isn't working well", or any request to improve an existing SKILL.md. Walks the user through an empirical, test-first process — probe the agent for real failures, design only for genuine knowledge gaps, iterate against runnable examples, and verify across models.
Use this skill when the user wants to 'login/log in/sign in', 'authenticate', 'authorize', 'connect OKX account', 'set up credentials', 'first time setup', 'configure okx', '登录', '授权', '认证', '连接账户', '首次配置'. Also when any OKX CLI command fails with an auth error: 'Run okx auth login first', 'Session expired', 'not authenticated', 'requires_auth', '401 Unauthorized', 'token expired/not found', 'StorageNotFoundError', '会话过期', '未认证', '需要登录'. Also when the user asks about login status or the login was interrupted. Also when the user wants to install/update/check/remove the okx-auth binary — 'install/update/remove auth', 'download okx-auth', '安装/更新/卸载认证', 'auth binary status', 'Failed to spawn okx-auth'. Also use before using okx-cex-trade/portfolio/earn/bot for the first time. Do NOT use for market data queries (use okx-cex-market).
Manages OKX Simple Earn (flexible savings/lending), Flash Earn, On-chain Earn (staking/DeFi), Dual Investment (DCD/双币赢), and AutoEarn (自动赚币) via the okx CLI. Use this skill whenever the user wants to check earn balances, browse flash-earn projects, subscribe or redeem earn products, view or set lending rates, monitor on-chain staking orders, interact with dual investment structured products, or manage auto-earn — even if phrased casually as 活期赚币, 定期赚币, 闪赚, 赚币, 申购, 赎回, 链上赚币, 质押, 理财, 双币赢, 双币理财, 双币申购, 高卖, 低买, dual investment, DCD, flash earn, buy low, sell high structured product, earn with target price, 目标价, 自动赚币, auto earn, auto-earn, 自动借出, 自动质押, auto lend, auto staking, USDG earn, USDG 赚币, 闲置资金自动理财, fixed earn, fixed deposit, term deposit, 定期理财, 定期. Also use when the user asks about idle funds and whether to earn on them.
Use this skill when the user asks to: 'find a trading skill', 'search for skills', 'install a skill', 'add a skill', 'download a skill', 'browse skill marketplace', 'what skills are available', 'update a skill', 'check for skill updates', 'remove a skill', 'uninstall a skill', 'list installed skills', 'show my skills', 'skill categories', 'verify skill signature', 'verify installed skill', 're-verify a skill', 'check skill integrity', or any request to discover, install, update, verify, or manage AI trading skills from the OKX Skills Marketplace. This skill covers searching, browsing categories, installing via CLI, downloading zip packages, checking for updates, removing installed skills, and verifying Ed25519 signatures of installed skills. Requires API credentials for marketplace API access. Do NOT use for placing orders (use okx-cex-trade), market data (use okx-cex-market), or bot management (use okx-cex-bot).
> Use when debugging Frappe errors, using bench console for live inspection, analyzing tracebacks, or reading Frappe log files. Prevents wasted debugging time from ignoring log context, misreading tracebacks, and not using bench console effectively. Covers bench console, frappe.logger, error log DocType, traceback analysis, common error patterns, log file locations, pdb/debugger integration, VS Code DAP, profiling, Frappe Recorder, mariadb diagnostics.
cheat-on-skill 的核心。为用户选定的某个候选岗位生成个性化学习策略：差距分析 → 分阶段学习路径（资源+里程碑）→ 作品集清单 → 求职时间线 → 止损线。强调 AI 加速学习、诚实周期、可验证里程碑。触发词："我选XX做学习计划"/"这个岗位怎么学"/"给我学习路径"/"skill plan"/"制定转型策略"。前置：该岗位最好已在 skill-scan 的 candidate_roles 里、判定为可学。
cheat-on-skill 的首次 onboarding。盘点用户能力（现有技能/可迁移底子/学历经验/每周可学时间/能坚持几个月/学习能力自评/地区/目标薪资/转型紧迫度），判定起点档位，创建 .skill-state.json 状态文件，是 skill-scan / skill-plan 的前置。触发词："能力盘点"/"我想转AI相关工作"/"找AI时代高薪工作"/"skill init"/"职业转型初始化"。**当用户想找/规划 AI 时代工作但 .skill-state.json 不存在时，先路由到此。**