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.
48,168 skills from 2,325 repositories · updated 3 hours ago
48,168 skills
- stock-liquidityhimself65/finance-skillsAnalyze how liquid a stock is using Yahoo Finance data (yfinance): bid-ask spreads, volume and dollar volume (ADTV), top-of-book and options depth, square-root market impact and slippage estimates, turnover ratio, and Amihud illiquidity, rolled into a liquidity grade. Use this skill whenever the user asks about liquidity or trading costs — how easily a position can be entered or exited, what a large order would do to the price, spread or execution-cost estimates, order book depth, volume patterns, or liquidity comparisons — especially for small caps, penny stocks, and thinly traded names.FinanceNo warnings★ 3.5K↓ —
- 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↓ —
- tao-run-inference-serviceNVIDIA/skillsStart, query, and stop a network-specific TAO inference microservice ({network_arch}-inference-microservice) by delegating container execution to the appropriate platform skill. Handles container image resolution, job-payload JSON construction, and the service registry. Use when the user wants to run inference on a TAO model checkpoint using a microservice container, deploy a TAO inference endpoint, or stop a running inference container.DevOpsNo warnings★ 3.8K↓ —
- maintain-formal-verification-skillmichael-denyer/pstack-claudeBring a project's formal verification back in line with the code after the code changes: find the commits that touched verified code, update the model, harness, or properties to describe the code as it is now, rerun, and say whether each failure is drift in the verification or a bug in the code. Use for /maintain-formal-verification-skill, "is the model still true to the code", or after merges and refactors that touched verified code without rechecking it.EngineeringNo warnings★ 3.7K↓ —
- tao-train-mask-auto-labelNVIDIA/skillsMAL (Mask Auto-Label) for weakly-supervised segmentation. Produces segmentation masks from minimal annotations (point or box annotations) using a ViT-MAE backbone. Use when training, evaluating, or running inference for a TAO MAL model. Trigger phrases include "train MAL", "Mask Auto-Label", "weakly-supervised segmentation", "box-prompted segmentation", "minimal-annotation mask prediction".OtherNo warnings★ 3.8K↓ —
- kiro-spec-initgotalab/cc-sddInitialize a new specification with detailed project descriptionPlanningNo warnings★ 3.7K↓ —
- 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↓ —
- create-planforyourhealth111-pixel/Vibe-SkillsCreate a concise plan. Use when a user explicitly asks for a plan related to a coding task.PlanningNo warnings★ 3.8K↓ —
- physicsnemo-discoverNVIDIA/skillsOfficial NVIDIA-authored guidance for navigating PhysicsNeMo — pick the model, datapipe, or example for a SciML/AI4Science task (surrogates, forecasting, downscaling, physics-informed, inverse, generative). Points at existing files via live repo search; never writes code. Do NOT use for installation or environment setup, training-loop or other code authoring/scaffolding, contributor/CI/packaging questions, repo-specific questions in physicsnemo-sym/-cfd/-curator, or general (non-physics) ML/PyTorch.ScienceNo warnings★ 3.8K↓ —
- umap-learnforyourhealth111-pixel/Vibe-SkillsUMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.OtherNo warnings★ 3.8K↓ —Also in 1 other repo
- 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↓ —
- doca-dtsNewNVIDIA/skillsDeploy and configure the NVIDIA DOCA Telemetry Service (DTS) as it is actually run: (A) BlueField (built-in static pod), (B) Host (docker) on x86_64 / aarch64, or (C) DPF (DPUService / helm chart) — plus the shared configuration layer (`dts_config.ini`, providers, exporters, level labels) that all three share. The user's DEPLOYMENT TYPE decides everything; pick it first. Trigger even without "DTS" for "prometheus on the DPU shows nothing on 9100", "telemetry container exits right after start", "add ethtool counters to the telemetry DPUService", "how do I upgrade the built-in telemetry on BlueField", or "level labels per rack/pod". Refuse and route elsewhere for installing DOCA itself, the `doca_telemetry` / `doca_telemetry_exporter` library API, installing the DPF cluster, Grafana / Prometheus server setup or dashboard / PromQL authoring, and BFB / BSP imaging — those belong to other skills or to external products.DevOpsNo warnings★ 3.8K↓ —
- cdf-augmentationNVIDIA/skillsUse when authoring or validating Cosmos Data Factory (CDF) augmentation YAML configs, or running remote Cosmos Transfer (including Cosmos3 WSM controls), Cosmos Predict, image-edit, or image-to-video inference.MediaNo warnings★ 3.8K↓ —
- 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↓ —
- kiro-steeringgotalab/cc-sddManage {{KIRO_DIR}}/steering/ as persistent project knowledgeOtherNo warnings★ 3.7K↓ —Also in 5 other repos
- jetson-link-docsNVIDIA/skillsBind pre-downloaded Jetson reference docs (developer guide, design guide, pinmux, schematics) into the active profile documents block. Use after staging docs on disk; not for downloading.DesignNo warnings★ 3.8K↓ —
- verifying-external-behaviorkajisho5/ffmpeg-skillConfirms what a third-party library, remote API, build backend, or scraped document actually does before writing code that depends on it — throwaway probes that run in seconds, permissive clients that forward wrong arguments instead of rejecting them, per-endpoint docs that don't generalize, response shapes that make a "fast path" always-false, fakes that encode your assumption rather than the service's behavior, and dry-runs that skip the step that fails. Use when integrating a new dependency or endpoint, writing a tolerated-status or error branch, choosing a client argument name, testing against a fake, or reviewing code that asserts an upstream contract.TestingNo warnings★ 4.1K↓ —
- exa-hello-worldjeremylongshore/tons-of-skills-marketplaceProve a new Exa Search integration with a bounded synthetic query and content-free assertions. Use when operating or reviewing this Exa boundary. Trigger with "Exa hello world", "review Exa hello world", or "fix Exa hello world".EngineeringNo warnings★ 2.9K↓ —
- kiro-implgotalab/cc-sddImplement approved tasks in Cascade using TDD and inline review. Runs all pending tasks or selected tasks in the main context.TestingNo warnings★ 3.7K↓ —
- kiro-steeringgotalab/cc-sddManage {{KIRO_DIR}}/steering/ as persistent project knowledgeOtherNo warnings★ 3.7K↓ —
- email-quality-auditoraaron-he-zhu/aaron-marketing-skillsUse when the user asks to "audit an email program" or "is this campaign safe to send"; runs a typed 20-item SEND profile with authentication, consent, opt-out, and claim veto checks on own evidence. Not for building deliverability setup — use deliverability-qa; not for designing lifecycle flows — use email-sequence-designer. 邮件质量审计/EQS评分/发送前放行ProductivityNo warnings★ 3K↓ —
- kiro-steering-customgotalab/cc-sddCreate custom steering documents for specialized project contexts. Use when creating domain-specific steering files.PlanningNo warnings★ 3.7K↓ —
- launch-tier-planneraaron-he-zhu/aaron-marketing-skillsUse when the user asks to "plan my launch tier", "how big should this launch be", or "build a launch risk register with kill criteria"; produces a tier decision (Tier 1 flagship all-channel / Tier 2 targeted / Tier 3 changelog-level), a launch-type declaration (new-product / feature / relaunch / partnership with co-marketing split), an effort calibration matrix (tier to channel intensity and asset scope), D0/W1/M1 KPI targets (labeled Estimated), a risk register (likelihood x blast-radius, owners, mitigations, kill criteria / rollback thresholds), and a T-8w to T+4w timeline skeleton. Not for picking the launch date or window — use launch-window-planner; not for creator-channel launch campaigns — use campaign-planner. 发布分级/发布类型/风险登记册/kill criteriaPlanningNo warnings★ 3K↓ —
- kiro-implgotalab/cc-sddImplement approved tasks using TDD with subagent dispatch. Runs all pending tasks autonomously or selected tasks manually.TestingNo warnings★ 3.7K↓ —Also in 3 other repos
launch-window-planner
aaron-he-zhu/aaron-marketing-skills
PlanningUpdated 7 hours ago
From the author
Use when the user asks to "pick a launch date", "plan the launch window", or "set the embargo and lift time"; produces a candidate-window comparison table (conflict / tailwind / risk per window) built from industry-event cycles and the competitor launch calendar, a launch-week vs rolling-release format call, store-review buffer padding (labeled Estimated), and an embargo window definition (lift moment + timezone) submitted to the launch registry as a candidate. Not for judging the cultural moment itself — use trend-spotter; not for launch-day execution — use launch-day-conductor. 发布择时/发布窗口/竞品日历/禁运期窗口/审核缓冲
Install
npx skills add aaron-he-zhu/aaron-marketing-skills --skill launch-window-planner -a claude-code
Installs to .claude/skills/launch-window-planner/ · 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.
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