Skills
开放的 AI 智能体 Skills 注册表,收录结构化提示词和工作流,并提供推荐模型、示例提示词与兼容工具。
Skills
100
类别
9
兼容工具
7
贡献者
2
Builds structured competitive analyses from public information. Maps competitors across positioning, pricing, features, target segments, and go-to-market motion; produces feature-comparison matrices and SWOT summaries; and highlights differentiation gaps and opportunities. Emphasizes citing sources and separating verified facts from inference.
Turns analysis results into a clear narrative for a specific audience. Selects the key message, orders findings for impact, recommends the right chart for each point, writes plain-language takeaways, and frames actionable recommendations. Helps analysts move from raw numbers to a memo or slide narrative executives can act on.
Generates and refactors dbt models for analytics engineering. Writes staging, intermediate, and mart models following layered conventions, adds schema.yml tests and descriptions, applies incremental and materialization strategies, and structures sources and refs correctly. Produces SQL plus YAML that fits dbt best practices and is ready to run.
Turns customer results into a persuasive, credible case study. Structures the story as challenge, solution, and measurable results, weaves in quotes and concrete metrics, keeps claims verifiable, and ends with a clear call to action. Produces a publish-ready draft plus a one-paragraph summary and pull-quote suggestions.
Builds discovery and usability interview guides that surface real insight. Translates research questions into open, non-leading prompts, sequences warm-up to deep-dive topics, adds follow-up probes, and applies techniques like the "five whys" and past-behavior questions. Outputs a timed guide with a consent intro and a synthesis template for notes.
Produces operational runbooks for services and common incidents. Documents prerequisites, step-by-step diagnosis and remediation, exact commands, verification checks, rollback steps, and escalation paths. Structures each runbook so an on-call engineer can follow it under pressure, and keeps destructive steps clearly flagged with safeguards.
Inspects messy tabular data and produces a repeatable cleaning plan plus code. Detects and fixes common issues: inconsistent types, duplicate rows, missing values, malformed dates, mixed encodings, whitespace and casing problems, and outliers. Outputs pandas or Polars code, a summary of changes, and a validation checklist.
Produces structured test plans for features and releases. Defines scope and objectives, derives test cases from requirements and acceptance criteria, covers functional, edge, negative, performance, and accessibility cases, sets entry/exit criteria, and maps risk to test priority. Outputs a clear plan with a traceability matrix linking tests to requirements.
Scans code, configuration, and git history for leaked credentials such as API keys, tokens, private keys, and connection strings. Classifies findings by severity and false-positive likelihood, and provides safe remediation steps including rotation, history scrubbing, and pre-commit prevention.
Designs and scaffolds ergonomic command-line tools with subcommands, flags, config files, shell completions, and helpful error output. Covers argument parsing conventions, exit codes, stdin/stdout piping, colored output, progress indicators, and cross-platform packaging. Produces maintainable CLIs that follow POSIX conventions and feel great to use.
Adds production-grade observability to a codebase by instrumenting it with structured logs, metrics, and distributed traces. Recommends span boundaries, cardinality-safe labels, and OpenTelemetry conventions, then generates the wiring code and dashboards needed to make a service debuggable in production.
Turns a script, concept, or product idea into a shot-by-shot storyboard. Breaks the narrative into scenes and panels with framing, camera movement, action, and dialogue notes, and generates image-model prompts for each panel so teams can visualize a video, ad, or explainer before production.
Generates and validates Software Bills of Materials in CycloneDX or SPDX formats. Covers dependency inventory, transitive resolution, license and vulnerability annotation, VEX statements, container image SBOMs, and CI integration for supply-chain compliance. Helps teams meet regulatory requirements and track what is actually shipped.
Analyzes cloud spend and produces a FinOps optimization plan. Covers rightsizing, autoscaling, spot/reserved/savings plans, storage tiering, idle resource cleanup, data transfer reduction, and tagging for cost allocation. Prioritizes actions by savings and risk, and defines guardrails and budgets to prevent regressions.
Writes reusable, well-structured Terraform modules with clean input/output interfaces, sensible defaults, validation rules, and examples. Covers module composition, variable typing and validation, remote state and backends, provider version pinning, and testing with terraform validate/plan and tools like Terratest. Emphasizes least-privilege IAM and safe defaults.
Models complex application logic as explicit finite state machines and statecharts. Identifies states, events, guards, and side effects; prevents impossible states; and generates implementations (e.g., XState-style) with diagrams. Ideal for wizards, checkout flows, connection lifecycles, and any feature where implicit boolean flags cause bugs.
Advises on how to evolve APIs without breaking clients. Compares versioning strategies (URI, header, media-type), classifies changes as breaking or non-breaking, and produces deprecation timelines, migration guides, and compatibility shims so teams can ship changes safely.
Builds cross-browser extensions on Manifest V3 with background service workers, content scripts, popup and options UIs, and message passing. Covers permissions scoping, storage sync, context menus, and store submission requirements for Chrome, Edge, and Firefox. Emphasizes least-privilege permissions and secure content-script isolation.
Builds robust webhook producers and consumers. Covers signature verification, idempotency keys, retry with exponential backoff, dead-letter handling, event ordering, and replay endpoints, and generates handler code plus tests so integrations survive duplicates and outages.
Writes end-to-end UI tests with Playwright or Cypress that mirror real user journeys. Covers resilient selectors (roles/test-ids), network stubbing, auth setup, fixtures, waiting strategies that avoid flakiness, visual and accessibility assertions, and CI integration. Produces maintainable specs and a page-object structure.
Diagnoses and fixes flaky tests by analyzing test code and CI failure history for common sources of nondeterminism such as time and timezone dependence, order dependence, shared mutable state, race conditions, and unmocked network calls. Proposes targeted fixes and quarantine strategies to keep the suite trustworthy.
Skills 与 MCP 服务器
有什么区别?Skills定义“做什么”
Skill 将说明、示例提示词和推荐模型组织在一起,让智能体稳定地完成任务。Skills 增加的是知识,而不是新的连接。
MCP 服务器定义“如何连接”
MCP 服务器通过连接数据库、API 和文件等真实系统,为智能体增加新能力。MCP 提供连接和操作,而不是任务说明。
简单来说:当模型需要把某项任务做好时选择 Skill;当模型需要访问工具或系统时选择 MCP 服务器。两者可以组合使用,Skill 可以依赖 MCP 服务器提供的工具。
创建了实用的 Skill?
提交 SKILL.md,加入由社区维护的开源注册表。