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.
48,622 skills from 2,355 repositories · updated 1 hour ago
48,622 skills
- gsd:map-codebasedavepoon/buildwithclaudeAnalyze codebase with parallel mapper agents to produce .planning/codebase/ documentsPlanningNo warnings★ 3.7K↓ —
- speak-install-authjeremylongshore/tons-of-skills-marketplaceSet up Speak language learning API integration and authentication. Use when configuring Speak API access, setting up OAuth with OpenAI Realtime API for speech, or initializing a language tutoring application. Trigger with phrases like "install speak", "setup speak", "speak auth", "configure speak API", "speak language learning setup".EngineeringNo warnings★ 2.9K↓ —
- distilldavepoon/buildwithclaudeSynthesize wiki pages from related memories. One endpoint, one flow: daemon clusters and synthesizes what it can; agent finishes whatever the daemon couldn't (no LLM or cluster too big). Invoked as `/distill [target]`.OtherNo warnings★ 3.7K↓ —
- sentry-hello-worldjeremylongshore/tons-of-skills-marketplaceCapture your first test error with Sentry and verify it appears in the dashboard. Use when testing a new Sentry integration, verifying error capture works after install-auth, or learning how to enrich events with user context, tags, and breadcrumbs. Trigger with phrases like "test sentry", "sentry hello world", "verify sentry", "first sentry error", "sentry capture test".TestingNo warnings★ 2.9K↓ —
- 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".OtherNo warnings★ 2.9K↓ —
- 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.PlanningNo warnings★ 3.7K↓ —
- onboarddavepoon/buildwithclaudeSet up CIAgent regression testing for the AI agent in this repo — write a runner, record golden baselines, generate a test spec, and verify it. Use when the user asks to add tests, evals, or regression testing for their AI agent, or to set up CIAgent.TestingNo warnings★ 3.7K↓ —
- aeonforyourhealth111-pixel/Vibe-SkillsThis skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.PlanningNo warnings★ 3.8K↓ —Also in 1 other repo
- nvflare-diagnose-jobNVIDIA/skillsUse when the user asks why a reported NVFLARE job failure signal occurred: the job failed, stalled, timed out, lost clients, ended with EXECUTION_EXCEPTION, or produced suspicious errors. Diagnose in simulation, POC, or production by collecting bounded evidence and mapping failure patterns to recovery actions.OtherNo warnings★ 3.8K↓ —
- codonfm-scoreNVIDIA/skillsValidate, prepare, or run public CodonFM Encodon masked-codon variant scoring and review compatibility of its scoring workflows. Use only when the user explicitly requests CodonFM or Encodon, or that context is already established in the conversation. Do not select this skill for a generic variant-scoring request without that context; ask for the variant and intended analysis first.EngineeringNo warnings★ 3.8K↓ —
- navan-cost-tuningjeremylongshore/tons-of-skills-marketplaceAnalyze Navan travel, expense, integration, and operating costs without freezing mutable prices. Use when setting budgets or evaluating workflow tradeoffs. Trigger with "reduce Navan cost", "Navan budget", or "control travel spend".ProductivityNo warnings★ 2.9K↓ —
- 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.ProductivityNo warnings★ 3.8K↓ —
- doca-argusNVIDIA/skillsUse this skill when the user is deploying or operating the DOCA Argus Service — the packaged BlueField-side runtime-security container that watches the BlueField and attached host for suspicious activity, integrity violations, and operational anomalies, and forwards findings to a SIEM (Splunk / ELK / Sentinel / syslog). Covers the four-axis config (detection policy, forwarding, sampling, host coverage), running the NGC container on BlueField Arm, and wiring the forwarder. Trigger even without "DOCA Argus" by name — typical implicit phrasings: "container green but no findings arrive", "false-positive flood in Splunk", or "runtime security on a fleet of BlueField-3s". Refuse and route elsewhere for installing DOCA, SIEM-side ingest stanzas, pre-baked detection-rule packs, and metrics observability (DOCA Telemetry). Argus is NVIDIA's currently- promoted runtime-security framework, superseding the older App Shield library; name it first for new runtime-security work.SecurityNo warnings★ 3.8K↓ —
- shapforyourhealth111-pixel/Vibe-SkillsModel interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.EngineeringNo warnings★ 3.8K↓ —Also in 1 other repo
- localaipicksNewdavepoon/buildwithclaudeFind open-weight AI models that run on the user's own hardware with Local AI Picks, with weight file sizes, memory needs, sources and test status. Use when the user asks which local LLM, coding, speech, image, video, music, translation or OCR model fits their Mac, GPU or RAM, or wants to compare open-weight models before downloading. No key needed.TestingNo warnings★ 3.7K↓ —
- miro-debug-bundlejeremylongshore/tons-of-skills-marketplaceDesign and implement a repository-side Miro diagnostic-bundle workflow with bounded metadata and automatic redaction. Use when escalating a Miro failure. Trigger with "build Miro debug bundle".EngineeringNo warnings★ 2.9K↓ —
- finta-debug-bundlejeremylongshore/tons-of-skills-marketplaceCollect Finta diagnostic information for support. Trigger with phrases like "finta debug", "finta support".EngineeringNo warnings★ 2.9K↓ —
- kiro-steeringgotalab/cc-sddMaintain {{KIRO_DIR}}/steering/ as persistent project memory (bootstrap/sync). Use when initializing or updating steering documents.ProductivityNo warnings★ 3.7K↓ —
- codonfm-setupNVIDIA/skillsSet up the public CodonFM v1 repository and download public Encodon checkpoints. Use for requests to build or launch the CodonFM development container, configure local data/checkpoint mounts, verify GPU access, or download public Encodon 80M, 600M, 1B, or Cdwt-1B weights. Do not use for Decodon, Encodon 5B/10B, missense-aggregation, or codon-optimization setup because those implementations are not in the public repository.OtherNo warnings★ 3.8K↓ —
- cargo-fuzztrailofbits/skillsSets up and runs cargo-fuzz, the standard fuzzing tool for Cargo-based Rust projects. Covers cargo fuzz init, the nightly toolchain requirement, fuzz_target! harnesses, Arbitrary-derived structured inputs, sanitizer options, cargo fuzz coverage, and reproducing a crash artifact. Use when fuzzing a Rust crate, writing a fuzz_target!, exercising unsafe blocks or FFI in Rust, or triaging a cargo fuzz crash.WritingNo warnings★ 7.9K↓ —
- 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.DesignNo warnings★ 3.8K↓ —
- figma-install-authjeremylongshore/tons-of-skills-marketplaceSet up Figma REST API authentication with personal access tokens or OAuth 2.0. Use when connecting to the Figma API, generating tokens, configuring scopes, or setting up OAuth flows for Figma integrations. Trigger with phrases like "install figma", "setup figma API", "figma auth", "figma personal access token", "figma OAuth".DesignNo warnings★ 2.9K↓ —
- pathmlforyourhealth111-pixel/Vibe-SkillsComputational pathology toolkit for analyzing whole-slide images (WSI) and multiparametric imaging data. Use this skill when working with histopathology slides, H&E stained images, multiplex immunofluorescence (CODEX, Vectra), spatial proteomics, nucleus detection/segmentation, tissue graph construction, or training ML models on pathology data. Supports 160+ slide formats including Aperio SVS, NDPI, DICOM, OME-TIFF for digital pathology workflows.DocumentsNo warnings★ 3.8K↓ —
- tao-finetune-kumo-anomalyNVIDIA/skillsKumo-Anomaly — diffusion-based anomaly detection and fine-tuning for multivariate time series. Use when the user asks to "fine-tune Kumo-Anomaly", "run Kumo-Anomaly inference", "detect anomalies with diffusion", "time series anomaly detection", "finetune Kumo-Anomaly", "use perform_anomaly_analysis_with_diffusion", "automl Kumo-Anomaly", "hyperparameter search Kumo-Anomaly", "hyperparameter optimization" or mentions "curriculum_medium.yaml", "final_model.pth", "kumo-anomaly", "sdk/anomaly_analysis", or "TSDiffuser_Generic".OtherNo warnings★ 3.8K↓ —
gtars
foryourhealth111-pixel/Vibe-Skills
ScienceUpdated 2 days ago
From the author
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
Install
npx skills add foryourhealth111-pixel/Vibe-Skills --skill gtars -a claude-code
Installs to .claude/skills/gtars/ · 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 onlyUses the networkLicence: APACHE-2.0
Safety checks on SKILL.md
No warnings.
Why 90
Security100
Provenance83
Maintenance100
Licence100
Adoption57
Files (7)
- SKILL.md
- references/cli.md
- references/coverage.md
- references/overlap.md
- references/python-api.md
- references/refget.md
- references/tokenizers.md