Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
49,415 skills from 2,407 repositories · updated 3 hours ago
48,317 skills
- git-worktree-manageralirezarezvani/claude-skillsUse when running several branches or agents in parallel on one repo. Creates worktrees with isolated ports and env via worktree_manager.py and removes stale ones with worktree_cleanup.py.EngineeringNo warnings★ 29.3K↓ —
- ops-inspectorTencentCloudBase/CloudBase-AI-ToolkitAIOps-style CloudBase inspection skill. Use when users need health checks, log diagnosis, alarm interpretation (CPU alert normal?, peak QPS), metrics via queryEnv(action=metrics), fault playbooks for 429 / AI model 429 / function timeout / function 404 / ACCESS_TOKEN_INVALID / zero invocations, or a scheduled patrol that reports only new or worse findings. Triggers on 巡检, 诊断, 告警, 峰值 QPS, 限频, 调用量为 0, 定时巡检, 每天检查, 值守, troubleshooting.OtherNo warnings★ 1.2K↓ —
- performance-profileralirezarezvani/claude-skillsUse for a slow endpoint, memory leak, CPU spike, large bundle or performance budget in Node.js, Python or Go, before optimizing. Measures before and after with performance_profiler.py, flamegraphs and k6 load tests.TestingNo warnings★ 29.3K↓ —
- ai-model-nodejsTencentCloudBase/CloudBase-AI-ToolkitUse this skill for Node.js backend AI via @cloudbase/node-sdk (>=3.16.0) — cloud functions, CloudRun, Express/Koa/NestJS, serverless APIs, scheduled jobs, LLM proxies, agent orchestration. The only SDK supporting image generation (ai.createImageModel + generateImage). Text via ai.createModel with groups cloudbase, the legacy hunyuan-v3 / hunyuan-exp, or custom-*; model ids (e.g. deepseek-v4.1-flash, glm-5.3, kimi-k2.6) go in the `model` field of generateText/streamText. MUST run two-step preflight before code — see body. NOT for browser/Web (use ai-model-web) or Mini Program (use ai-model-wechat).BrowserNo warnings★ 1.2K↓ —Also in 5 other repos
- perfhashgraph-online/awesome-codex-pluginsPerformance optimizer for loops, DB queries, rendering, and batch operations. Catches N+1 queries, missing indexes, and unnecessary re-renders.MediaNo warnings★ 1.5K↓ —
- laravel-tddhashgraph-online/awesome-codex-pluginsTest-driven development for Laravel with PHPUnit and Pest, factories, database testing, fakes, and coverage targets.TestingNo warnings★ 1.5K↓ —
- nanoresearch-writingOpenRaiser/NanoResearchDraft a LaTeX research paper from all previous stage outputsWritingNo warnings★ 1.3K↓ —
- nanoresearch-ideationOpenRaiser/NanoResearchSearch academic literature and generate research hypothesesScienceNo warnings★ 1.3K↓ —
- ml-paper-writingOpenRaiser/NanoResearchWrite publication-ready ML/AI/Systems papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, SOSP. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.ScienceNo warnings★ 1.3K↓ —
- peft-fine-tuningOpenRaiser/NanoResearchParameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.ProductivityNo warnings★ 1.3K↓ —
- ultragoalhuytieu/COG-second-brainRun a large, multi-session goal (e.g. shipping a whole side product) through the full V-model closed loop, one phase at a time, with cross-session state and a final north-star acceptance gate. Ultragoals never downgrade the lane: every phase runs CP-1→CP-6 with adversarial verification. Opt-in: invoke with /ultragoal or by calling something a long-running goal. Ordinary work does not run this.OtherNo warnings★ 1.3K↓ —Also in 1 other repo
- expo-skill-evalexpo/skillsEvaluate Expo skills in this repo end-to-end - trigger accuracy, generated code quality, and runtime screenshots on iOS simulator and Android emulator via Expo Go (web optional). Use when the user wants to eval an Expo skill, test that a skill produces working code, benchmark a skill with device screenshots, or verify a skill's output renders correctly.OfficialTestingNo warnings★ 4.1K↓ —
- cloudbaseTencentCloudBase/CloudBase-AI-ToolkitUse when the user builds, deploys, debugs, or troubleshoots anything on 腾讯云开发 CloudBase / 云开发 / TCB / 微信云开发 — Web, 微信小程序, uni-app, 原生 App. Triggers on: 建站, 页面, 表单, 后台, 原型, 登录, 注册, 鉴权, 数据库, 集合, 建表, 云函数, 云托管, 云存储, 静态托管, 上传, 部署, 上线, 域名, 日志, 报错, 巡检, 大模型, AI 对话, 流式输出, 智能体, 小程序. This is an entry skill: it routes the task to the right CloudBase MCP tool and then pulls the detailed recipe from the CloudBase MCP knowledge base. Do NOT use for non-CloudBase stacks or self-hosted backends.DevOpsNo warnings★ 1.2K↓ —
- casefilehashgraph-online/awesome-codex-pluginsUse when tracking security investigations, bug bounty findings, CTF leads, audit evidence, exploit chains, dead ends, or reports in the Casefile ledger through Codex.SecurityNo warnings★ 1.5K↓ —
- nejm-fitbrycewang-stanford/Awesome-Journal-SkillsUse this first, before any writing, to stress-test whether a clinical study clears NEJM's bar — practice-changing clinical impact, methodological rigor, and generalizability. Decides NEJM vs Lancet/JAMA vs a specialty journal.TestingNo warnings★ 1.4K↓ —
- pnas-fitbrycewang-stanford/Awesome-Journal-SkillsUse before any writing begins to stress-test whether a result clears PNAS's bar — high quality and broad significance to a general scientific readership — and to make the realistic call between PNAS, Science/Nature, and a specialist field journal.TestingNo warnings★ 1.4K↓ —
- atc-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning an ATC (ACM SIGOPS Annual Technical Conference, formerly USENIX ATC) campaign end to end — running the year backward from the early-June deadline through the two review rounds, the rebuttal, conditional-acceptance shepherding, the post-acceptance artifact evaluation, and the ACM Open Access camera-ready for the November Hong Kong conference.ProductivityNo warnings★ 1.4K↓ —
- pnas-databrycewang-stanford/Awesome-Journal-SkillsUse to build PNAS's Data Availability Statement and deposition plan — mandatory deposition of data in an approved repository at submission, accession numbers/DOIs, public + archived code, and materials sharing. "Available on request" is not sufficient for primary data.PlanningNo warnings★ 1.4K↓ —
- ase-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning an ASE (IEEE/ACM Automated Software Engineering) research-track campaign backward from the deadline, through abstract registration, the double-anonymous submission, the early-rejection gate, rebuttal, the criteria-bound revision round, artifact evaluation, and the camera-ready in both IEEE Xplore and the ACM Digital Library.ProductivityNo warnings★ 1.4K↓ —
- sci-fitbrycewang-stanford/Awesome-Journal-SkillsUse before any writing to stress-test whether a result clears Science's (AAAS) desk-reject filter — broad significance and general interest across disciplines. Decides Science vs Science Advances vs a specialist journal before you invest in prose.TestingNo warnings★ 1.4K↓ —
- pnas-trackbrycewang-stanford/Awesome-Journal-SkillsUse to choose the PNAS submission track — Direct Submission (standard, editor-assigned, peer reviewed) vs Contributed Submission (an NAS member communicates their own paper). Covers eligibility, the editor/member role, the discontinued and legacy tracks, and how to pick. Unique to PNAS.ScienceNo warnings★ 1.4K↓ —
- cav-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning a CAV (Computer Aided Verification) project timeline from venue and category selection through submission, the two-stage review with early reject and rebuttal, artifact evaluation by the AEC, and the LNCS open-access camera-ready, with backward-planning offsets for a verification-tool paper and honest handling of the single-annual-deadline cycle.ProductivityNo warnings★ 1.4K↓ —
- acl-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning an ACL project calendar across ACL Rolling Review cycles, covering cycle selection against conference commitment windows, backward planning from an ARR deadline, the review-response-meta-review timeline, commitment decisions, resubmission loops to later cycles, and camera-ready through ACL Anthology publication.ProductivityNo warnings★ 1.4K↓ —
- hri-workflowbrycewang-stanford/Awesome-Journal-SkillsUse to plan an ACM/IEEE HRI campaign backward from the full-paper deadline through the abstract-then-paper two-step, the rebuttal, the program-committee meeting, camera-ready, and the March conference, coordinating the parallel alt.HRI, Late-Breaking Reports, video, and Student Design deadlines.ProductivityNo warnings★ 1.4K↓ —
trend-discovery
ScrapeCreators/social-media-research-skills
OtherUpdated Aug 26, 2026
From the author
Use when the user wants to discover trending social topics, hashtags, sounds, posts, reels, shorts, creators, or formats in a niche. Searches public trend and discovery endpoints, ranks evidence, and turns trends into practical content angles.
Install
npx skills add ScrapeCreators/social-media-research-skills --skill trend-discovery -a claude-code
Installs to .claude/skills/trend-discovery/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Download .zip
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Instructions onlyNo network use seenLicence: MIT
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