Agent 工作流

可复用的 Agent 工作流和编排模式

1330 個 Skills 可用

Skills 列表

wecomcli-create-meeting

wecomcli-create-meeting

2.6Kagent-workflows

企业微信会议创建技能, 支持创建预约会议. 当用户需要\"创建会议\", \"预约会议\", \"约会议\", \"安排会议\"时触发.

wecomteam avatarwecomteam
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ccc

ccc

2.5Kagent-workflows

This skill should be used when code search is needed (whether explicitly requested or as part of completing a task), when indexing the codebase after changes, or when the user asks about ccc, cocoindex-code, or the codebase index. Trigger phrases include 'search the codebase', 'find code related to', 'update the index', 'ccc', 'cocoindex-code'.

cocoindex-io avatarcocoindex-io
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datadog-cli

datadog-cli

2.5Kagent-workflows

Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog observability.

softaworks avatarsoftaworks
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token-optimizer

token-optimizer

2.5Kagent-workflows

Audit a Claude Code or Codex setup for context-window waste, then fix it and measure the savings. Use when context feels tight.

alexgreensh avataralexgreensh
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agents-optimize

agents-optimize

2.5Kagent-workflows

Use when measuring or improving agent quality and performance — set up evaluators, online monitoring, CI/CD quality gates, observability, or cost optimization. Triggers on: "evaluate my agent", "add evaluator", "measure quality", "quality gate", "run evals", "agent too slow", "why is it slow", "reduce latency", "set up observability", "CloudWatch dashboard", "how much does my agent cost", "cost optimization", "logs not showing up", "logs missing", "spans not found", "eval failing", "eval error", "dev traces", "local traces", "agentcore dev traces", "traces to CloudWatch". Not for debugging errors or crashes — use agents-debug. Slow but correct routes here; broken routes to debug.

aws avataraws
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agents-get-started

agents-get-started

2.5Kagent-workflows

Use when a developer wants to create a new agent project or get started with AgentCore. Handles framework selection, project scaffolding, first deploy, and first invocation. Triggers on: "build an agent", "create an agent", "get started", "new project", "agentcore create", "which framework", "Strands vs LangGraph", "hello world agent", "first agent", "create MCP server", "host MCP server", "agentcore dev", "dev server", "what port", "local development". Not for adding capabilities to existing projects — use agents-build or agents-connect. Strands vs LangGraph in a migration context routes to agents-build, not here. Connecting to an existing MCP server routes to agents-connect, not here.

aws avataraws
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short-drama-novel-analyze

short-drama-novel-analyze

2.5Kagent-workflows

把长篇小说、连载网文或多集散稿拆成可追溯的原著分析:章节索引、改编价值快评、逐章功能提取、剧情单元与节奏聚合、人物与设定归并,最后给出改编价值判定与分集候选,交给 $short-drama-develop 立契约。用户说“导入这本小说”“拆这本书”“分析原著”“这本书能不能改短剧”“先看看值不值得拆”“把长篇拆成分集候选”,或直接给出小说文件路径时使用。只做只读的结构化分析,不写剧本、不建资产、不生成媒体,也不替创作者决定改编方案。

zenstory-ai avatarzenstory-ai
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short-drama-edit

short-drama-edit

2.5Kagent-workflows

将已生成的短剧镜头剪成成片,记录入出点、镜序、声音、字幕与交付规格。用于套剪、加字幕、统一响度、调整节奏或导出精修素材;需要补素材或修改故事时转回对应创作阶段。

zenstory-ai avatarzenstory-ai
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short-drama-write

short-drama-write

2.5Kagent-workflows

编写或修订可拍摄的中文短剧、漫剧单集 Markdown 剧本,也负责保留作者原文地规范化现成剧本。用户提出“写/改一集短剧”“把大纲写成剧本”“优化场景/对白”“去模板感”“去 AI 味润色”“续写下一集”或提供剧本要求进入后续制作时使用;不负责资产、分镜、媒体提示词或终审。

zenstory-ai avatarzenstory-ai
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short-drama-storyboard

short-drama-storyboard

2.5Kagent-workflows

把中文短剧剧本和视觉设定写成有戏剧职责、连续性边界与冻结关键帧提示词的分镜 Markdown。用户提出“拆分镜/设计镜头/做镜头表”“场次视觉计划/调度故事板”“比较导演方案”“写首帧/关键帧提示词”或检查轴线、站位、视线、持物连续性时使用;不生成媒体。

zenstory-ai avatarzenstory-ai
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short-drama-review

short-drama-review

2.5Kagent-workflows

审查短剧项目中的原著分析、故事、剧本、视觉设定、图片提示词、分镜、冻结关键帧、视频提示词和已有媒体。用户提出“审稿/检查剧本”“检查资产或连续性”“检查图片/视频提示词”“检查原著分析”“审查模板感”“根据生产观察做项目校准”时使用;只写审查问题、结论和修订要求,不代替 owner 修改来源文件。

zenstory-ai avatarzenstory-ai
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short-drama-develop

short-drama-develop

2.5Kagent-workflows

将中文小说、短剧或漫剧想法、梗概、改编材料、已有系列笔记或多集完整剧本发展成可追溯的改编方案、戏剧方向、创作简报、导演阐述、故事引擎与分集地图,并按题材与制作形态(画风)选择写法。用户提出“导入小说做短剧”“从多集整稿生成/补分集地图”“开发短剧/漫剧”“做故事设定/系列大纲/分集规划”“写导演阐述”“这个题材怎么写”“定画风/制作形态”“把这个点子变成短剧”或需要梳理人物冲突与集间交接时使用;已有单集剧本可直接进入写作、资产或审查流程,不强制补开发文件。

zenstory-ai avatarzenstory-ai
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short-drama-assets

short-drama-assets

2.5Kagent-workflows

从短剧剧本拆出人物/造型、地点/视图、道具/状态和跨场连续性,写成创作者可读的视觉设定。用户说“拆角色/场景/道具”“做资产设定”“判断复用还是新变体”“更新造型/道具状态”,或拿现成剧本直接做视觉资产准备时使用;不写图片提示词,不生成媒体。

zenstory-ai avatarzenstory-ai
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short-drama-image-prompts

short-drama-image-prompts

2.5Kagent-workflows

为短剧人物、造型、地点、道具和状态编写或修改可直接复制的图片提示词 Markdown。用户提到角色设定图、三视图、参考图、场景板、道具图、风格帧、Look Development、状态变体或局部编辑提示词时使用;不生成图片,也不调用供应商。

zenstory-ai avatarzenstory-ai
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internal-dev-workbench

internal-dev-workbench

2.4Kagent-workflows

Spin up a portless + tmux dev session for the Workflow SDK that gives each git worktree isolated `<branch>.<name>.localhost` URLs for the Next.js workbench and the observability UI, plus a Claude statusline that surfaces those URLs. Use only when the user asks for a "portless dev session", a "tmux dev layout for workflow", "worktree-isolated dev URLs", or wants to wire workflow dev URLs into the Claude statusline. Do not activate for the generic "start the dev server" / "run pnpm dev" task.

vercel avatarvercel
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ralph-tui-prd

ralph-tui-prd

2.4Kagent-workflows

Generate a Product Requirements Document (PRD) for ralph-tui task orchestration. Creates PRDs with user stories that can be converted to beads issues or prd.json for automated execution. Triggers on: create a prd, write prd for, plan this feature, requirements for, spec out.

subsy avatarsubsy
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gepetto

gepetto

2.4Kagent-workflows

Creates detailed, sectionized implementation plans through research, stakeholder interviews, and multi-LLM review. Use when planning features that need thorough pre-implementation analysis.

softaworks avatarsoftaworks
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chinese-novelist

chinese-novelist

2.4Kagent-workflows

分章节创作引人入胜的中文小说。支持各种题材(悬疑/言情/奇幻/科幻/历史等),支持10-50章长篇创作,每章3000-5000字,结尾设置悬念钩子。强调深度润色去除AI痕迹,确保文字自然流畅。 当用户要求:写小说、创作故事、分章节写作、连续剧情、章节悬念、长篇小说时使用。

penglonghuang avatarpenglonghuang
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golang-code-style

golang-code-style

2.3Kagent-workflows

Golang code style conventions — line length and breaking, variable declarations, control flow clarity, when comments help vs hurt. Use when writing or reviewing Go code, asking about style or clarity, or establishing project coding standards. Not for naming conventions (→ See `samber/cc-skills-golang@golang-naming` skill), linter configuration (→ See `samber/cc-skills-golang@golang-lint` skill), or doc comments (→ See `samber/cc-skills-golang@golang-documentation` skill).

samber avatarsamber
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golang-error-handling

golang-error-handling

2.3Kagent-workflows

Idiomatic Golang error handling — creation, wrapping with %w, errors.Is/As, errors.Join, custom error types, sentinel errors, panic/recover, the single handling rule, structured logging with slog, HTTP request logging middleware, and samber/oops for production errors. Built to make logs usable at scale with log aggregation 3rd-party tools. Apply when creating, wrapping, inspecting, or logging errors in Go code. For samber/oops specifics → See `samber/cc-skills-golang@golang-samber-oops` skill; for slog handler ecosystem → See `samber/cc-skills-golang@golang-samber-slog` skill.

samber avatarsamber
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golang-performance

golang-performance

2.3Kagent-workflows

Golang performance optimization patterns and methodology - if X bottleneck, then apply Y. Covers allocation reduction, CPU efficiency, memory layout, GC tuning, pooling, caching, and hot-path optimization. Use when profiling or benchmarks have identified a bottleneck and you need the right optimization pattern to fix it. Also use when performing performance code review to suggest improvements or benchmarks that could help identify quick performance gains. Not for measurement methodology (→ See `samber/cc-skills-golang@golang-benchmark` skill) or debugging workflow (→ See `samber/cc-skills-golang@golang-troubleshooting` skill).

samber avatarsamber
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golang-design-patterns

golang-design-patterns

2.3Kagent-workflows

Idiomatic Golang design patterns — functional options, constructors, error flow and cascading, resource management and lifecycle, graceful shutdown, resilience, architecture, dependency injection, data handling, streaming, and more. Apply when explicitly choosing between architectural patterns, implementing functional options, designing constructor APIs, setting up graceful shutdown, applying resilience patterns, or asking which idiomatic Go pattern fits a specific problem.

samber avatarsamber
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golang-naming

golang-naming

2.3Kagent-workflows

Go (Golang) naming conventions — covers packages, constructors, structs, interfaces, constants, enums, errors, booleans, receivers, getters/setters, functional options, acronyms, test functions, and subtest names. Use this skill when writing new Go code, reviewing or refactoring, choosing between naming alternatives (New vs NewTypeName, isConnected vs connected, ErrNotFound vs NotFoundError, StatusReady vs StatusUnknown at iota 0), debating Go package names (utils/helpers anti-patterns), or asking about Go naming best practices. Also trigger when the user mentions MixedCaps vs snake_case, ALL_CAPS constants, Get-prefix on getters, or error string casing. Do NOT use for general Go implementation questions that don't involve naming decisions.

samber avatarsamber
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golang-context

golang-context

2.3Kagent-workflows

Idiomatic context.Context usage in Golang — propagation through API boundaries, cancellation, timeouts and deadlines, request-scoped values, context.WithoutCancel for background work outliving requests. Apply when designing context propagation across layers, debugging leaked or unexpired contexts, choosing between context.Background/TODO/WithoutCancel, or storing values in context. Not for code that merely accepts ctx as first parameter.

samber avatarsamber
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