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.
49,409 skills from 2,375 repositories · updated 10 hours ago
48,362 skills
- hf-cloud-python-env-setuphuggingface/skillsSet up an isolated Python environment for SageMaker / AWS work, with the right Python version and current boto3. Use this skill whenever Python code will be executed for a SageMaker deployment, training job, or any AWS automation — including when about to run `pip install`, when about to invoke `boto3`, when creating or activating a virtualenv, or when the user asks to "set up the environment". Never use system Python and never `pip install` into it. Always isolate. This skill prevents the most common failure modes: wrong Python version, dependency conflicts, and stale SDKs.OfficialEngineeringNo warnings★ 11.3K↓ —
- data-contractmohitagw15856/pm-claude-skillsDefine a data contract between a producer and consumers of a dataset/event/API. Use when asked to write a data contract, define a schema agreement, set data SLAs, or stop a producer from silently breaking downstream consumers. Produces a contract — schema with types & constraints, semantics, quality SLAs (freshness/completeness/validity), ownership, versioning & breaking-change policy, and a change process.LegalNo warnings★ 1.5K↓ —
- hsb-appNVIDIA/skillsDiscover and run Holoscan Sensor Bridge example applications on a connected devkit. Filters available apps by the user's platform, HSB software version, board type, and sensors. Supports timed execution, failure analysis, code-edit suggestions, and iterative re-runs.WritingNo warnings★ 3.8K↓ —
- design-system-compliancereticlehq/reticleCheck that the UI you actually rendered uses the design system, by reading computed styles in the running app against the project's design tokens. Catches hardcoded hex colors, off-palette backgrounds, invisible or unusable controls, and animations that never ran. Use after building or restyling a component, when a design review is wanted, when a UI looks slightly off but nobody can say why, or when a design system exists and nothing checks whether the code follows it.DesignNo warnings★ 1.3K↓ —
- fizz-convertpashov/skillsConvert English-language properties in PROPERTIES.md (produced by the Fizz skill) into Solidity assertions inside the existing fuzz harness, then flip their checkboxes. Trigger on "fizz-convert", "convert properties", "implement properties from PROPERTIES.md", "convert PROPERTIES.md to Solidity".OtherNo warnings★ 1.3K↓ —
- conext-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning an ACM CoNEXT campaign backward from a deadline, covering the choice between the December and June submission cycles, the mandatory registration step, the one-shot major-revision window, the reproducibility badge opt-in due at submission, PACMNET camera-ready, and presentation — all on CoNEXT's distinctive two-cycles-per-year calendar.ProductivityNo warnings★ 1.4K↓ —
- cikm-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when positioning a CIKM submission against three literatures at once — retrieval, mining, and knowledge management/databases — building the boundary-work paragraph, guarding against misattributing SIGIR/KDD/ICDM classics to CIKM, and handling preprints under the arXiv-declaration and dual-submission rules.ScienceNo warnings★ 1.4K↓ —
- colm-camera-readybrycewang-stanford/Awesome-Journal-SkillsUse when converting a COLM acceptance into the final paper — the August 7 camera-ready deadline in 2026, de-anonymization and the one-page acknowledgments allowance, folding rebuttal commitments into the text, publishing on OpenReview, releasing artifacts publicly, and planning the October conference in San Francisco.ScienceNo warnings★ 1.4K↓ —
- colm-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when positioning a COLM paper inside the fastest-moving literature in ML — triaging arXiv-heavy citations, handling concurrent work fairly, citing model and dataset artifacts correctly, distinguishing COLM's three-edition archive from adjacent venues' archives, and keeping self-citation double-blind safe.ScienceNo warnings★ 1.4K↓ —
- asplos-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning an ASPLOS campaign across the two-deadline cycle — sequencing evidence building, the September 9, 2026 submission gate, author-response windows, the December 21 notification, Major Revision resubmission six weeks later, artifact evaluation, and the April 2027 conference in Crete, with owners per risk.ProductivityNo warnings★ 1.4K↓ —
- cav-review-processbrycewang-stanford/Awesome-Journal-SkillsUse when reasoning about how a CAV (Computer Aided Verification) submission is evaluated, covering the two-stage reviewing process (two reviews then an early-reject filter, then two more reviews with a rebuttal), the partial double-anonymity by category, the accept/reject outcome, the optional non-conditional artifact evaluation, and how CAV differs from TACAS and FMCAD.EngineeringNo warnings★ 1.4K↓ —
- ase-review-processbrycewang-stanford/Awesome-Journal-SkillsUse when reasoning about how an ASE (IEEE/ACM Automated Software Engineering) research submission is evaluated, covering double-anonymous review, the early-rejection stage before rebuttal, the Accept / Revision / Reject outcomes, the criteria-bound revision round, and how ASE's process differs from FSE's PACMSE Major Revision, ICSE's cycles, and ISSTA's rounds.EngineeringNo warnings★ 1.4K↓ —
- vldb-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of a VLDB paper, covering workload and dataset realism at scale, competitor tuning fairness, scalability curves versus single points, tail-latency and throughput reporting, ablations that isolate the mechanism, and the loss-case disclosure PVLDB reviewers look for first.ScienceNo warnings★ 1.4K↓ —
- aaai-camera-readybrycewang-stanford/Awesome-Journal-SkillsUse when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.ScienceNo warnings★ 1.4K↓ —
- wsdm-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of a WSDM paper - offline ranking and recommendation metrics with bias controls, temporal-split protocols for interaction logs, baseline selection from recent WSDM/SIGIR/KDD editions, ablations that isolate the mechanism, efficiency reporting, and online-evidence framing.ScienceNo warnings★ 1.4K↓ —
- sosp-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of a SOSP paper — mapping every claim to an experiment, choosing baselines a systems PC will accept as fair, mixing microbenchmarks with end-to-end and failure runs, reporting tails and overheads honestly, and isolating the mechanism the design credits.DesignNo warnings★ 1.4K↓ —
- socc-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing ACM SoCC evaluations, covering real or realistic deployments over simulation, production or representative workloads and traces, tail-latency and cost as first-class metrics, fair tuned baselines, scale and multi-tenancy behavior, reproducible measurement pipelines, and matching evidence to the shape of each cloud claim.DevOpsNo warnings★ 1.4K↓ —
- stoc-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when judging whether computation belongs in a STOC (ACM Symposium on Theory of Computing) paper at all — STOC accepts on theorems, with no empirical-evaluation expectation — and when it does, scoping it as certified proof computation, constructive search, or clearly labeled illustration rather than benchmarking.MediaNo warnings★ 1.4K↓ —
- pods-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the analytical "evidence" of an ACM PODS paper — worst-case and average-case analyses, matching upper and lower bounds, dichotomy completeness, correct complexity assumptions, and the occasional empirical validation when a theory paper claims practicality — matching the rigor to the shape of each theoretical claim.ScienceNo warnings★ 1.4K↓ —
- popl-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing the empirical component of a POPL paper — deciding whether evidence should be a mechanization, a prototype, case studies, or benchmarks; reporting proof effort and case-study coverage honestly; and keeping performance numbers in a supporting role so the formal claim stays the paper's center of gravity.ScienceNo warnings★ 1.4K↓ —
- pldi-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing a PLDI evaluation — choosing defensible benchmark suites and baseline compiler configurations, measuring runtime, compile time, and memory with warmup and variance discipline, running ablations that isolate the claimed mechanism, and scoping claims to the platforms measured.ProductivityNo warnings★ 1.4K↓ —
- rss-supplementarybrycewang-stanford/Awesome-Journal-SkillsJournal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的 Claude Code/Codex 期刊技能包，从选题、识别策略到表格规范与审稿回复全流程，助你快速发论文。PlanningNo warnings★ 1.4K↓ —
- kdd-writing-stylebrycewang-stanford/Awesome-Journal-SkillsUse when revising a KDD paper into the venue's register, where the first page names a data regime, a mechanism, and scale evidence, efficiency adjectives trace to design decisions, and two-column sigconf pages punish sprawl. Covers Research vs ADS voice, dataset-size discipline, assertive contribution bullets, and 8-page compression.WritingNo warnings★ 1.4K↓ —
- ipsn-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing IPSN-lineage evaluations, covering real testbeds and deployments, ground-truth instrumentation, energy/latency/footprint measurement on real hardware, on-device/TinyML profiling, estimation-theoretic baselines and bounds, and matching evidence to the shape of each sensing claim across the IP and SPOTS tracks.DevOpsNo warnings★ 1.4K↓ —
generate-ppmplugin
microsoft/power-platform-skills
EngineeringUpdated 21 hours ago
From the author
Build and verify a third-party `.ppmplugin` end to end. This recommended entry point detects Android and iOS source, confirms target platforms, then invokes the manifest, platform build, assemble, and audit stages in order. Advanced users can invoke a stage directly for focused reruns or debugging. Produces a native-only bundle (`manifest.json` plus an Android DEX and/or iOS framework) and stops on any failed stage rather than emitting an unverified partial build. Run after the native module exists.
Install
npx skills add microsoft/power-platform-skills --skill generate-ppmplugin -a claude-code
Installs to .claude/skills/generate-ppmplugin/ · 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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