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.
49.409 skill-uri din 2.375 de depozite · actualizat acum 6 ore
49.407 skill-uri
- kiro-validate-implgotalab/cc-sddValidate feature-level integration after all tasks are implemented. Checks cross-task consistency, full test suite, and overall spec coverage.TestareFără avertismente★ 3,8 K↓ —
- rag-perfNVIDIA/skillsPerformance benchmarking for a deployed NVIDIA RAG Blueprint server: profiling pass + aiperf load test driven by a single YAML config. Not for accuracy / RAGAS scoring (use rag-eval) or for deploying / repairing services (use rag-blueprint).TestareFără avertismente★ 3,8 K↓ —
- fathom-rate-limitsjeremylongshore/tons-of-skills-marketplaceHandle Fathom API rate limits (60 requests/minute per user). Trigger with phrases like "fathom rate limit", "fathom 429", "fathom throttle".InginerieFără avertismente★ 2,9 K↓ —
- mode-creatorthedotmack/claude-memInteractively create, install, activate, and verify custom claude-mem modes, including domain-specific observation types, concept tags, optional Telegram alerts, bot setup, worker restart, and startup-context verification. Use this whenever someone asks to customize what claude-mem remembers, create or change a mode, track domain-specific notes, add observation types or tags, or send Telegram notifications for particular memories—even if they do not use the word "mode."PlanificareFără avertismente★ 111,4 K↓ —
- physicsnemo-shard-tensorNVIDIA/skillsOfficial NVIDIA-authored guidance for PhysicsNeMo ShardTensor domain parallelism — integrate domain parallelism into training/inference scripts (new or existing) with DDP or FSDP2, write and register shard patches to enable new layers/ops, and bootstrap multi-GPU correctness tests. Use when working with ShardTensor, scatter_tensor, domain parallelism, sequence/spatial sharding, ring attention, DeviceMesh + DDP/FSDP2 hybrid parallelism, or physicsnemo.domain_parallel. Do NOT use for generic PyTorch DDP/FSDP setup without domain parallelism, picking a PhysicsNeMo model or example (use physicsnemo-discover), or non-distributed training questions.TestareFără avertismente★ 3,8 K↓ —
- gsd:ingest-docsdavepoon/buildwithclaudeScan a repo for mixed ADRs, PRDs, SPECs, and DOCs and bootstrap or merge the full .planning/ setup from them. Classifies each doc in parallel, synthesizes a consolidated context with a conflicts report, and routes to new-project or merge-milestone depending on whether .planning/ already exists.PlanificareFără avertismente★ 3,7 K↓ —
- exa-known-pitfallsjeremylongshore/tons-of-skills-marketplaceAudit an Exa integration for stale search types, unsafe secrets, ignored partial failures, unbounded content work, weak citations, and orphaned asynchronous resources. Use when operating or reviewing this Exa boundary. Trigger with "Exa known pitfalls", "review Exa known pitfalls", or "fix Exa known pitfalls".InginerieFără avertismente★ 2,9 K↓ —
- navan-debug-bundlejeremylongshore/tons-of-skills-marketplaceAssemble a content-free Navan integration support bundle for operators or vendor escalation. Use when triage needs reproducible evidence. Trigger with "collect Navan diagnostics", "Navan support bundle", or "sanitize Navan logs".InginerieFără avertismente★ 2,9 K↓ —
- adaptyvforyourhealth111-pixel/Vibe-SkillsCloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.TestareFără avertismente★ 3,8 K↓ —Apare și în 2 alte depozite
- competitor-analystjeremylongshore/tons-of-skills-marketplaceCompetitive analysis and market positioning partner for Product Managers. Use when the user needs to analyze competitors, map positioning, or identify feature gaps. Trigger with "competitor", "competitive analysis", "market map", "feature comparison", "how does X compare", or "positioning".AlteleFără avertismente★ 2,9 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★ 70,7 K↓ —
- ml-data-leakage-guardforyourhealth111-pixel/Vibe-SkillsDetects and prevents data leakage in machine learning and mathematical modeling. Use after ML tasks involving data cleaning, feature engineering, data augmentation, algorithm development, normalization, missing value imputation, dimensionality reduction, feature selection, or time series modeling. Checks if features/statistics would be available at prediction time.ProductivitateFără avertismente★ 3,8 K↓ —
- clerk-sdk-patternsjeremylongshore/tons-of-skills-marketplaceCommon Clerk SDK patterns and best practices. Use when implementing authentication flows, accessing user data, or integrating Clerk SDK methods in your application. Trigger with phrases like "clerk SDK", "clerk patterns", "clerk best practices", "clerk API usage".InginerieFără avertismente★ 2,9 K↓ —
- ui-animationnexu-io/open-designImplement, review, and measure UI motion. Reconstruct easing, springs and gestures from a recording using bundled frame extraction, tracking and curve-fitting tools when available.DesignFără avertismente★ 105,7 K↓ —
- pyopenmsforyourhealth111-pixel/Vibe-SkillsPython 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.DateFără avertismente★ 3,8 K↓ —Apare și în 1 alt depozit
- terraform-policyhashicorp/agent-skillsWrite, test, or convert Terraform Policy files (.policy.hcl, .policytest.hcl, Sentinel→tfpolicy). Triggers: policy.hcl, policytest, convert sentinel, tfpolicy, write a policy.OficialDevOpsFără avertismente★ 911↓ —
- setup-bennybacknotprop/pstackConfigure Benny and prepare its triage and repro automations. Use when installing Benny or changing its Slack, tracker, repository, routing, control, model, or budget settings.AlteleFără avertismente★ 3,5 K↓ —
- principle-explain-the-numberbacknotprop/pstackApply before you measure, and before you trust, report, or act on a number you measured: a speedup, a regression, a throughput, a latency, or an eval result. Find what limits it, and rule out that it measured something other than the work you think.AlteleFără avertismente★ 3,5 K↓ —
- teachmichael-denyer/pstack-claudeExplain a body of work plainly so a person actually understands it. Runs the `how` and `why` skills and weaves what they find into one clear explanation. Use for 'teach me this', 'help me really understand X', 'explain this change or subsystem to me'.AlteleFără avertismente★ 3,9 K↓ —
- principle-model-the-domainbacknotprop/pstackApply when writing stateful logic, or when code branches a lot or repeats a shape assumption across files.RedactareFără avertismente★ 3,5 K↓ —Apare și în 1 alt depozit
- principle-experience-firstbacknotprop/pstackApply when product, UX, or feature-scope tradeoffs come up. Choose user delight over implementation convenience; ship fewer polished features over more rough ones.DesignFără avertismente★ 3,5 K↓ —Apare și în 3 alte depozite
- designing-experimentsforyourhealth111-pixel/Vibe-SkillsDesign experiments and quasi-experiments before analysis. Use when choosing study design, treatment/control structure, outcomes, assumptions, validation plans after scientific experiment failure, or which of DiD, ITS, synthetic control, or regression discontinuity fits the research question. For fitting models or estimating effects on existing data, use performing-causal-analysis instead.DesignFără avertismente★ 3,8 K↓ —
- typescript-best-practicesbacknotprop/pstackTypeScript best practices. Use when reading or editing any .ts or .tsx file.InginerieFără avertismente★ 3,5 K↓ —
- principle-fix-root-causesbacknotprop/pstackApply when debugging. Trace each symptom back to the first place the system went wrong and fix it there. A guard is a fix only when the state it handles is legitimate.InginerieFără avertismente★ 3,5 K↓ —Apare și în 1 alt depozit
nemo-fabric-integrate
NVIDIA/skills
DevOpsActualizat ieri
De la autor
Use this skill when integrating NVIDIA NeMo Fabric into a consumer application, service, evaluation harness, or platform through the typed Python SDK — translating the consumer's own application, job, or deployment config into an in-memory FabricConfig, choosing the single-invocation convenience API or an explicitly started runtime, validating with plan and doctor, and consuming normalized results, artifacts, and telemetry.
Instalare
npx skills add NVIDIA/skills --skill nemo-fabric-integrate -a claude-code
Se instalează în .claude/skills/nemo-fabric-integrate/ · 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 (8)
- BENCHMARK.md
- SKILL.md
- evals/evals.json
- references/config-mapping.md
- references/results-and-errors.md
- references/sdk-api-inventory.md
- skill-card.md
- skill.oms.sig