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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.
49,417 skills from 2,407 repositories · updated 25 minutes ago
49,415 skills
- webperfUpdatednucliweb/webperf-snippetsWeb performance measurement and debugging toolkit. Use when the user asks about web performance, wants to audit a page, or says "analyze performance", "debug lcp", "check ttfb", "measure core web vitals", "audit images", or similar.EngineeringNo warnings★ 1.5K↓ —Also in 1 other repo
- colt-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when positioning a COLT (Conference on Learning Theory) submission against prior bounds and models — building the known-versus-new comparison across COLT/ALT lineage, STOC/FOCS, NeurIPS-and-ICML theory tracks, statistics journals, and arXiv concurrency, while respecting anonymity and the parallel-submission rules.ScienceNo warnings★ 1.4K↓ —
- azure-usagefcakyon/claude-codex-settingsThis skill should be used when user asks to "query Azure resources", "list storage accounts", "manage Key Vault secrets", "work with Cosmos DB", "check AKS clusters", "use Azure MCP", or interact with any Azure service.DevOpsNo warnings★ 1.2K↓ —
- test-auditfcakyon/claude-codex-settingsThis skill should be used when the user asks to "write a test", "review these tests", "audit tests", "prune low-value tests", or "find duplicate tests", and whenever writing, changing, reviewing, or sweeping tests. Gates new tests and audits low-value, implementation-coupled, or duplicative tests and the test-only production seams they demand.TestingNo warnings★ 1.2K↓ —
- creating-claude-rulesAgentWorkforce/relayUse when creating or fixing .claude/rules/ files - provides correct paths frontmatter (not globs), glob patterns, and avoids Cursor-specific fields like alwaysApplyPlanningNo warnings★ 1.1K↓ —
- dogfoodfcakyon/claude-codex-settingsSystematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.TestingNo warnings★ 1.2K↓ —
- write-outreachgooseworks-ai/goose-skillsCold outreach a person sends to business buyers: email and LinkedIn sequences, a first line per prospect, reply and objection answers, and a read of replies. Use when the marketer says "write a cold email sequence", "what do I send to this list", "write LinkedIn messages for these leads", "how do I reply to this prospect" or "handle this objection", "reply to this demo request", "win back or reconnect with accounts that churned or went quiet", or "why is nobody replying to my outreach". Drafts only; the marketer sends from their own tool. Not for finding the people — use research-audience; not for emails to subscribers or users, or consumer win-back — use email-lifecycle.WritingNo warnings★ 1.3K↓ —
- md-reviewalirezarezvani/claude-skillsUse when converting a markdown code review with diff blocks and severity callouts into a two-column HTML review. Parses diffs with diff_parser.py and annotations with annotation_extractor.py; requires a named reviewer.EngineeringNo warnings★ 29.3K↓ —
- oma-imagefirst-fluke/oh-my-agentGenerate raster images or reference-guided variations through the OMA image CLI. Use for image assets or explicit vendor comparisons; pixel editing uses an editor.MediaNo warnings★ 1.4K↓ —
- mind-workflowbrycewang-stanford/Awesome-Journal-SkillsUse as the entry point for any Mind (philosophy journal) article. Routes to the right Mind sub-skill based on where you are in the lifecycle and whether the piece is an article, discussion note, book review, or critical notice. Mind is analytic philosophy — argument, not data — so the router's first job is to confirm there is a sharp thesis and a sound argument. It dispatches; it does not draft content.ProductivityNo warnings★ 1.4K↓ —
- learn-my-brandgooseworks-ai/goose-skillsLearn my brand once and stop asking me every time. Use when someone says learn my brand, set up my brand, here's our brand book, remember how we talk, what can we claim, can we say this, approve our claims, sign off our voice, our price or product changed, the client approved the claims, pick up where we left off, or check our claims are still current. Reads what GooseWorks already found about the brand, asks only the gaps as drafts to confirm, audits every claim (including ones research marked approved) and gets the ones that matter signed off with proof, scope and review date, turns the voice into rules the owner confirms, checks logo, colours and fonts, and saves it all as it goes so every other job loads it instead of asking. Ends with an unknowns list and a read-back. Not for who our customers are and what they say (use research-audience) or writing positioning from scratch (not covered yet).ScienceNo warnings★ 1.3K↓ —
- nsdi-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of an NSDI submission — choosing traces, testbeds, and deployment evidence, sizing scale and failure-injection experiments, picking baselines that fight back, and reporting tail behavior so networked-systems reviewers can see where the design wins, loses, and breaks.DevOpsNo warnings★ 1.4K↓ —
- 02-ref-hallucination-arenaagentscope-ai/OpenJudgeBenchmark LLM reference recommendation capabilities by verifying every cited paper against Crossref, PubMed, arXiv, and DBLP. Measures hallucination rate, per-field accuracy (title/author/year/DOI), discipline breakdown, and year constraint compliance. Supports tool-augmented (ReAct + web search) mode. Use when the user asks to evaluate, benchmark, or compare models on academic reference hallucination, literature recommendation quality, or citation accuracy.ScienceNo warnings★ 1.1K↓ —
- research-competitors-edge-casesgooseworks-ai/goose-skillsStep of the research-competitors playbook: rules for run edge cases such as no browser, stalled workers, earlier reports and late reads. Run research-competitors instead; not for direct use.ScienceNo warnings★ 1.3K↓ —
- rendering-strategieskostja94/marketing-skillsWhen the user wants to choose or optimize rendering strategy for SEO. Also use when the user mentions "SSR," "SSG," "CSR," "ISR," "static rendering," "dynamic rendering," "server-side rendering," "client-side rendering," "JavaScript rendering," "pre-rendering," "prerender," "content in initial HTML," or "crawler visibility." For crawl issues, use site-crawlability.MediaNo warnings★ 1.1K↓ —
- ap-intakeSpielewoy/autoprompt-skillReport the compatibility redirect to `C0`; this retired role cannot perform new work.OtherNo warnings★ 1.2K↓ —
- ap-scope-coordinatorSpielewoy/autoprompt-skillReport the compatibility redirect to `ap-run-coordinator`; this retired role cannot perform new work.OtherNo warnings★ 1.2K↓ —
- documenthashgraph-online/awesome-codex-pluginsRecord a decision, document existing code, or file a supplied research material. Modes: document decision (ADR, RFC, or rule), document code (spec, doc, guide, or scenario for existing behavior), document research (only when a finished report or one external material is already in hand). Use for 'we decided', 'record this decision', 'document why we chose X', 'make it our standard', 'draft an RFC', 'should we switch to Y' proposals, 'resolve the RFC', 'we accepted the proposal', 'document the auth module', 'capture how the payment system works', reference material, how-to instructions, or a user flow with examples over an existing spec. Name the type inside the subject to skip the type question. Planning a feature or an intended user journey → /archcore:plan. Checking docs against code or docs health → /archcore:review.ScienceNo warnings★ 1.5K↓ —
- evalhashgraph-online/awesome-codex-pluginsQuality and performance evaluation with baseline comparison. Sub-modes: correctness, performance, quality, regression. Outputs PASS/WARN/FAIL per dimension. Use for pre-ship evaluation or regression checks.OtherNo warnings★ 1.5K↓ —
- shiphashgraph-online/awesome-codex-pluginsShip phase. Runs isolated integration test in a fresh worktree, creates a PR with full spec + audit report in the body, watches CI, and auto-fixes failures.TestingNo warnings★ 1.5K↓ —
- email-lifecycle-lifecycle-auditgooseworks-ai/goose-skillsStep of the email-lifecycle playbook: audits list, consent, live flows, recent sends and sending setup, marking every item verified, from-you or unknown. Run email-lifecycle instead; not for direct use.ProductivityNo warnings★ 1.3K↓ —
- second-brain-transcriptundefined-ui/second-brain-osClean a raw transcript before ingestion: punctuate, paragraph, label speakers, fix mistranscribed technical terms, and split long recordings by topic. Use this skill when the user drops an auto-generated transcript, subtitle file, podcast or lecture transcript, meeting recording text, or asks to process a video or audio source. Do NOT use for text that is already prose, for summarising a transcript, or for the ingestion itself.MediaNo warnings★ 1.4K↓ —
- review-prfcakyon/claude-codex-settingsThis skill should be used when user asks to "review a PR", "review pull request", "review this pr", "code review this PR", "check PREngineeringNo warnings★ 1.2K↓ —
- podc-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when building the evidence for an ACM PODC paper — where "evidence" is a proof, not a benchmark. Covers matching upper and lower bounds, tightness arguments, model and assumption stress-tests, adversary-strength calibration, and the honest, clearly-optional role of any simulation in a distributed-computing-theory paper.TestingNo warnings★ 1.4K↓ —
mlsys-workflow
brycewang-stanford/Awesome-Journal-Skills
ProductivityUpdated Sep 27, 2026
From the author
Use when planning an MLSys submission cycle end to end, from venue-fit and track choice through evaluation freeze, the October deadline, the four-day January response, notification, camera-ready, the March artifact-evaluation submission, and the May conference, with backward planning built around scarce GPU time and team ownership.
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mlsys-workflow -a claude-code
Installs to .claude/skills/mlsys-workflow/ · 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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