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実際に使われている Agent Skills
公開リポジトリの検証済み Skills を比較し、機能、内容、導入状況、出典を確認してから追加できます。
- 掲載範囲
- 検証済み
- Skills
- 15,601
- リポジトリ
- 2523
- 最終同期
- 2026/10/12
mbfinottithought-leadership-ads
Plan a campaign that promotes an executive's or founder's existing organic posts as paid person-fronted ads - post selection, sequencing, audience and exclusions, permission and governance, budget, and measurement. Use whenever the user mentions thought leader ads, promoting a founder's or CEO's post, sponsoring an employee's or a creator's post, executive content amplification, running ads from a personal profile, or B2B trust ads - even if they never say 'thought leadership'. Covers B2B trust-
- 導入数
- 722
- GitHub Stars
- 1
- 更新日
- 9月14日
mbfinotticonversational-ad-copy
Adapt ad messaging for conversational and AI-answer ad surfaces - the one-shot, context-aware ad occupying a single response slot inside an AI assistant reply or answer-engine result, where the copy is either rendered verbatim or rewritten by a model from the landing page and feed. Covers recommendation register, self-contained slot copy, situation-description targeting, grounding and disclosure discipline, and reading performance without creative-level reporting. Use whenever the user mentions
- 導入数
- 721
- GitHub Stars
- 1
- 更新日
- 9月14日
mbfinottiad-campaign-consolidation
Evaluate a fragmented paid-ads account and recommend which campaigns and ad sets to merge, which splits to preserve, and how to migrate without resetting learning across the account - it plans the consolidation, it never executes it. Use whenever the user mentions too many campaigns or ad sets, merging or restructuring an ad account, ad sets stuck in learning or learning limited, budget spread too thin, account simplification, or campaigns competing with each other - even if they never say 'cons
- 導入数
- 720
- GitHub Stars
- 1
- 更新日
- 9月14日
mbfinottiad-copy-variants
Turn one core value proposition into genuinely distinct ad copy variants - headline, primary text, description, and CTA combinations - each labelled with angle, awareness stage, formula, and version so test results stay attributable. A real variant is a new angle, never a reworded line. Use whenever the user asks to write ad copy, needs headline or CTA variations, wants copy to A/B test, has ads that all sound the same, or needs a search ad headline set or an ML asset pool - even if they never s
- 導入数
- 714
- GitHub Stars
- 1
- 更新日
- 9月14日
addyosmaniperformance-optimization
Optimizes application performance across frontend, backend, queries, and databases. Use when performance requirements exist, when you suspect performance regressions, when Core Web Vitals or load times need improvement, when N+1 query patterns need fixing, or when profiling reveals bottlenecks.
- 導入数
- 708
- GitHub Stars
- 10.5万
- 更新日
- 10月10日
stark-ai-decursor-memory-curator
Audit and safely curate Cursor rules and provided memory-bank context. Use when reviewing stale, conflicting, sensitive, or misplaced Cursor instructions, not generic repository docs.
- 導入数
- 701
- GitHub Stars
- 6
- 更新日
- 10月1日
addyosmanishipping-and-launch
Prepares production launches. Use when preparing to deploy to production, or when asking what needs to be in place before shipping. Use when you need a pre-launch checklist, when setting up monitoring, when planning a staged rollout, or when you need a rollback strategy.
- 導入数
- 697
- GitHub Stars
- 10.5万
- 更新日
- 10月10日
addyosmaniapi-and-interface-design
Guides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.
- 導入数
- 693
- GitHub Stars
- 10.5万
- 更新日
- 10月10日
addyosmanispec-driven-development
Creates specs before coding. Use when starting a new project, feature, or significant change and no specification exists yet. Use when drafting a PRD or requirements document with objectives and scope, or when requirements are unclear, ambiguous, or only exist as a vague idea. Use when a single requirement spans several independently testable capabilities and needs decomposing into a capability map of modules before specifying.
- 導入数
- 688
- GitHub Stars
- 10.5万
- 更新日
- 10月10日
amplitudeadd-analytics-instrumentation
End-to-end analytics instrumentation workflow for a PR, branch, file, directory, or feature. Reads the code, discovers what events should be tracked, and produces a concrete instrumentation plan — all in one shot. Use this skill whenever a user wants to add analytics to a PR, asks "instrument this PR", "add tracking to this branch", "what analytics does this file need", "instrument the checkout flow", "run the full instrumentation workflow", or any request that implies going from code changes to
- 導入数
- 685
- GitHub Stars
- 43
- 更新日
- 10月9日
amplitudediff-intake
Reads a PR or branch diff and produces a structured YAML change brief for downstream analytics instrumentation skills. Use this as the first step whenever a user shares a PR link, branch comparison, or raw diff and wants to understand what changed, what needs tracking, or how to instrument a feature. Trigger on phrases like "review this PR", "what changed in this branch", "help me instrument this diff", "check analytics coverage for this change", or any request to start the analytics review work
- 導入数
- 685
- GitHub Stars
- 43
- 更新日
- 10月9日
amplitudediscover-event-surfaces
Given a changebrief YAML (output from diff-intake), generates an exhaustive list of candidate analytics events to instrument. Takes the perspective of an engineer with a PM mindset — surfaces everything worth considering so a PM can decide what actually matters. Use this as step 2 of the analytics instrumentation workflow, immediately after diff-intake produces a changebrief. Trigger whenever a user has a changebrief YAML and wants to know what analytics events to add, or asks "what should I tra
- 導入数
- 685
- GitHub Stars
- 43
- 更新日
- 10月9日
amplitudediscover-analytics-patterns
Discovers how analytics tracking calls are actually written in this codebase — the concrete SDK calls, function signatures, and import patterns used to send events. Use this skill whenever you need to understand the existing analytics instrumentation patterns before adding new tracking, when someone asks "how do we track events here?", "show me the analytics setup", "what's the analytics pattern in this codebase?", or any time the instrument-events or discover-event-surfaces skills are about to
- 導入数
- 684
- GitHub Stars
- 43
- 更新日
- 10月9日
amplitudeinstrument-events
Given eventcandidates YAML (output from discover-event-surfaces), generates a concrete instrumentation plan for priority-3 (critical) events. Acts as a Software Architect: discovers existing analytics patterns in the codebase, reads the hinted files to determine what variables are in scope, designs minimal chart-useful properties, and identifies the exact insertion point for each tracking call. Outputs a structured JSON trackingPlan. Use this as step 3 of the analytics instrumentation workflow,
- 導入数
- 684
- GitHub Stars
- 43
- 更新日
- 10月9日
amplitudetaxonomy
Source of truth for event taxonomy generation, data auditing, and governance best practices in Amplitude. Use when an agent needs to create, validate, audit, score, or recommend improvements to event tracking plans, naming conventions, property standards, data quality, or deprecation workflows. Covers naming rules, property standards, scoring frameworks, safe metadata operations, deprecation procedures, and AI readiness guidance.
- 導入数
- 684
- GitHub Stars
- 43
- 更新日
- 10月9日
stark-ai-dedrawio-diagrams
Create, edit, review, or export editable draw.io diagrams. Use when the user needs .drawio architecture, flow, sequence, network, or other technical diagrams; not data plots or artistic images.
- 導入数
- 683
- GitHub Stars
- 6
- 更新日
- 10月1日
stark-ai-dearchitecture-compass
Set up ADR governance, audit architecture and drift, or plan and execute bounded ADR-guided refactors. Use when work needs binding architecture decisions, provider-to-local mapping, architecture PR review, and durable runtime or source-boundary changes.
- 導入数
- 680
- GitHub Stars
- 6
- 更新日
- 10月1日
stark-ai-decodex-memory-curator
Audit and safely curate Codex memory, including stale claims, cross-repo leakage, sensitive entries, and memory configuration. Use when reviewing or cleaning Codex memory, not generic repository docs.
- 導入数
- 678
- GitHub Stars
- 6
- 更新日
- 10月1日
addyosmaniplanning-and-task-breakdown
Breaks work into ordered tasks. Use when you have a spec or clear requirements and need to break work into implementable tasks. Use when a task feels too large to start, when you need to estimate scope, or when parallel work is possible.
- 導入数
- 675
- GitHub Stars
- 10.5万
- 更新日
- 10月10日
addyosmanidebugging-and-error-recovery
Guides systematic root-cause debugging. Use when tests fail, builds break, something that worked yesterday broke, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need to figure out what broke and why — a systematic approach to finding and fixing the root cause rather than guessing.
- 導入数
- 674
- GitHub Stars
- 10.5万
- 更新日
- 10月10日
stark-ai-dejev-capability-advisor
Recommend available skills or MCP tools using TypeSafe Jev, or explicitly choose one next skill. Use when the user requests capability advice, candidate inspection, selection evaluation, or reusable host integration. Native client selection remains the default and fallback.
- 導入数
- 668
- GitHub Stars
- 6
- 更新日
- 10月1日
addyosmanicontext-engineering
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
- 導入数
- 666
- GitHub Stars
- 10.5万
- 更新日
- 10月10日
addyosmanicode-simplification
Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.
- 導入数
- 665
- GitHub Stars
- 10.5万
- 更新日
- 10月10日
stark-ai-declaude-spec-interviewer
Turn ambiguous coding requests into verified Claude Code implementation specs. Use when the user wants requirements, an implementation plan, or a spec before coding; include source checks, needed ADRs, and agreed delivery. Do not use for already specified direct implementation or memory cleanup.
- 導入数
- 665
- GitHub Stars
- 6
- 更新日
- 10月1日