Skill-uri pentru agenți pe care le poți verifica înainte să le instalezi
Skill-uri SKILL.md publice din depozite GitHub cu peste 50 de stele și de la producători, scanate și evaluate. Instalează oricare dintre ele cu o singură comandă în Claude Code, Cursor, Codex, GitHub Copilot sau Gemini CLI.
45.100 de skill-uri din 2.196 de depozite · actualizat acum 1 oră
45.100 de skill-uri
- gsd:ui-phasedavepoon/buildwithclaudeGenerate UI design contract (UI-SPEC.md) for frontend phasesDesignFără avertismente★ 3,7 K↓ —
- gsd:settingsdavepoon/buildwithclaudeConfigure GSD workflow toggles and model profileProductivitateFără avertismente★ 3,7 K↓ —
- gsd:progressdavepoon/buildwithclaudeCheck project progress, show context, and route to next action (execute or plan). Use --forensic to append a 6-check integrity audit after the standard report.SecuritateFără avertismente★ 3,7 K↓ —
- gsd:add-tododavepoon/buildwithclaudeCapture idea or task as todo from current conversation contextProductivitateFără avertismente★ 3,7 K↓ —
- cuboid-carouselheygen-com/hyperframesA chain of bevelled cuboids rides a travelling wave as a content carousel. HyperFrames block, 1920×1080, 6.666666666666667s, 40 variables.OficialAlteleFără avertismente★ 72,7 K↓ —
- remove-deadcodecode-yeongyu/oh-my-openagentRemove unused code from this project with ultrawork mode, LSP-verified safety, atomic commits. Triggers: remove dead code, dead code, cleanup, remove unused.InginerieFără avertismente★ 70,3 K↓ —
- ulw-loopcode-yeongyu/oh-my-openagentA goal-like loop that decomposes work into systematic, evidence-bound ultrawork steps. Use when the user wants a goal loop or durable, checkpointed execution.AlteleFără avertismente★ 70,3 K↓ —
- memory-bridgeAr9av/obsidian-wikiBrowse or compare wiki knowledge by originating AI tool. Use for cross-tool memory questions, tool-specific knowledge, or gap/diff analysis between Codex, Claude, Hermes, and other agents.ProductivitateFără avertismente★ 3,6 K↓ —
- run-acceptance-testshashicorp/agent-skillsGuide for running acceptance tests for a Terraform provider. Use this when asked to run an acceptance test or to run a test with the prefix `TestAcc`, when a test fails with missing environment variables, or when diagnosing a failing or suspiciously passing acceptance test.OficialTestareFără avertismente★ 909↓ —
- verify-paperclippaperclipai/paperclipVerify Paperclip from a source checkout, published npm install, or existing staging or production stack. Select the environment, data state, version, and platform; drive real UI or CLI journeys and capture evidence. Route deployment to the private Cloud skills.DevOpsFără avertismente★ 107,5 K↓ —
- paperclippaperclipai/paperclipInteract with the Paperclip control plane API for task coordination and governance. Use when checking assignments, updating issue status, posting comments, delegating work, managing routines, or calling Paperclip API endpoints.PlanificareFără avertismente★ 107,5 K↓ —
- provider-actionshashicorp/agent-skillsImplement Terraform Provider actions using the Plugin Framework. Use when developing imperative operations that execute at lifecycle events (before/after create, update, destroy).OficialDevOpsFără avertismente★ 909↓ —
- pre-publish-reviewcode-yeongyu/oh-my-openagentNuclear-grade 12-agent pre-publish release gate. Runs /get-unpublished-changes to detect all changes since last npm release, spawns up to 10 ultrabrain agents for deep per-change analysis, invokes /review-work (orchestrator manual QA plus one gate reviewer) for holistic review, and 1 oracle for overall release synthesis. Runs ONLY when the user explicitly asks for a pre-publish review — a plain publish/release request MUST NOT trigger this; /publish ships directly. Triggers: 'pre-publish review', 'review before publish', 'release review', 'pre-release review', 'ready to publish?', 'can I publish?', 'pre-publish', 'safe to publish', 'publishing review', 'pre-publish check'.InginerieFără avertismente★ 70,3 K↓ —Apare și în 1 alt depozit
- gsd:cleanupdavepoon/buildwithclaudeArchive accumulated phase directories from completed milestonesAlteleFără avertismente★ 3,7 K↓ —
- doca-pcc-ztr-rttcc-algoNVIDIA/skillsDOCA-shipped Zero-Touch RoCE RTT congestion control (ZTR RTTCC) reference algorithm on a BlueField-3 DPA: deploy, tune and evaluate doca_pcc_dev_ztr_rttcc_algo through the shipped DOCA PCC sample. Trigger on "my RoCE-v2 flows aren't being throttled", "PCC sample isn't dispatching to my algo", "set-params returns fail", "algorithm loaded but counters are flat", "how do I pick the multipath PCC variant", or "do I need a custom CC algorithm on BF3", even without naming ZTR RTTCC. Your own algorithm through the host library belongs to doca-pcc; the doca_spcx_cc command line to doca-spcx-cc. Covers picking a variant (vanilla / PM / RX-rate / multipath / window-probeless) at DPACC build time, tuning host-set parameters, and DOCA_PCC_DEV_STATUS_FAIL from the algorithm. Refuse and route elsewhere for writing a custom PCC algorithm from scratch, read-only PCC counter inspection, or firmware-only pre-Programmable PCC.DevOpsFără avertismente★ 3,7 K↓ —
- review-workcode-yeongyu/oh-my-openagentPost-implementation gate review: run manual QA on the real surface yourself, then launch ONE gate reviewer (never a panel) to audit goal, constraints, code quality, security, missed context, and QA evidence. Use before a PR handoff or when the user explicitly asks to review completed work.InginerieFără avertismente★ 70,3 K↓ —
- tao-train-pointpillarsNVIDIA/skillsPointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a pillar-based representation, then applies 2D detection — used in autonomous driving and robotics. Use when training, evaluating, exporting, pruning, retraining, or running inference for a TAO PointPillars model. Trigger phrases include "train PointPillars", "LiDAR 3D detection", "point-cloud object detection", "pillar-based 3D detector".MediaFără avertismente★ 3,7 K↓ —
- sentry-cost-tuningjeremylongshore/tons-of-skills-marketplaceOptimize Sentry costs, reduce event volume, and manage quota spend. Use when analyzing Sentry billing, reducing error/transaction volume, configuring sampling rates, or preventing overage charges. Trigger: "reduce sentry costs", "sentry billing optimization", "sentry quota management", "optimize sentry spend", "sentry sampling".AlteleFără avertismente★ 2,9 K↓ —
- jetson-print-bsp-infoNVIDIA/skillsUse when you need to print Jetson BSP info (L4T version, board configs, rootfs state) from a Linux_for_Tegra root on the host PC. This is an example skill.AlteleFără avertismente★ 3,7 K↓ —
- jetson-customize-pcieNVIDIA/skillsPer-controller PCIe enable / disable / lanes / link-speed for a Jetson Thor or Orin custom carrier via ODMDATA + kernel-DT overlay. Do NOT use for UPHY lane allocation or endpoint-mode bring-up.AlteleFără avertismente★ 3,7 K↓ —
- ramp-observabilityjeremylongshore/tons-of-skills-marketplaceInstrument Ramp API clients, webhook consumers, deferred tasks, and accounting syncs with safe service and financial-correctness signals. Use when defining dashboards, alerts, traces, or reconciliation health. Trigger with "monitor Ramp integration" or "Ramp observability".DevOpsFără avertismente★ 2,9 K↓ —
- optimizing-promptsjeremylongshore/tons-of-skills-marketplaceExecute this skill optimizes prompts for large language models (llms) to reduce token usage, lower costs, and improve performance. it analyzes the prompt, identifies areas for simplification and redundancy removal, and rewrites the prompt to be more conci... Use when optimizing performance. Trigger with phrases like 'optimize', 'performance', or 'speed up'.AlteleFără avertismente★ 2,9 K↓ —
- tao-train-oneformerNVIDIA/skillsOneFormer for universal image segmentation. Unifies panoptic, instance, and semantic segmentation with a single architecture using task-conditioned queries. Use when training, evaluating, exporting, quantizing, or running inference for a TAO OneFormer model. Trigger phrases include "train OneFormer", "universal segmentation", "task-conditioned segmentation", "panoptic / instance / semantic in one model".MediaFără avertismente★ 3,7 K↓ —
- tao-train-bevfusionNVIDIA/skillsBEVFusion for multi-sensor 3D object detection. Fuses LiDAR point clouds and camera images in bird's-eye-view (BEV) space, used in autonomous driving for robust 3D perception. Use when training, evaluating, or running inference for a TAO BEVFusion model. Trigger phrases include "train BEVFusion", "LiDAR + camera fusion", "BEV 3D detection", "multi-sensor 3D perception".AlteleFără avertismente★ 3,7 K↓ —
pyopenms
foryourhealth111-pixel/Vibe-Skills
DateActualizat acum 14 ore
De la autor
Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.
Instalare
npx skills add foryourhealth111-pixel/Vibe-Skills --skill pyopenms -a claude-code
Se instalează în .claude/skills/pyopenms/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Descarcă .zip
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Doar instrucțiuniFolosește rețeauaLicență: APACHE-2.0
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 90
Securitate100
Proveniență83
Întreținere100
Licență100
Adopție57
Fișiere (7)
- SKILL.md
- references/data_structures.md
- references/feature_detection.md
- references/file_io.md
- references/identification.md
- references/metabolomics.md
- references/signal_processing.md