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.
49,399 skills from 2,375 repositories · updated 41 minutes ago
49,399 skills
- datamolK-Dense-AI/scientific-agent-skillsPythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.DesignNo warnings★ 56K↓ —Also in 2 other repos
- courtsickn33/agentic-awesome-skillsPut an idea on trial: a prosecutor and a defense Claude argue, 12 juror sub-agents vote independently, and a judge reads the verdict and the changes that would flip it.OtherNo warnings★ 49.1K↓ —
- credible-claimspedrohcgs/claude-code-my-workflowResearch-brief + claim-record discipline for delegated or AI-assisted research work. Use when starting any substantive research task or long autonomous run (write the brief first), and when reporting results that will support a claim in a paper or decision (produce the claim record). Keeps faster execution from being confused with credible evidence.ScienceNo warnings★ 1.7K↓ —
- teach-from-paperpedrohcgs/claude-code-my-workflowTurn a research paper into teaching materials — a lecture outline, the 3-5 results worth presenting (with intuition), a slide skeleton ready for `/create-lecture`, discussion questions, and a problem-set brief. Reads the paper end-to-end and pitches to a stated audience level. Use when user says "turn this paper into a lecture", "teach from this paper", "build slides from this PDF", "make teaching materials from X", "I'm presenting this paper to my class".ScienceNo warnings★ 1.7K↓ —
- polarsK-Dense-AI/scientific-agent-skillsHigh-performance DataFrame library for Python ETL, analytics, and pandas migration. It supports expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.DataNo warnings★ 56K↓ —Also in 2 other repos
- simulation-studypedrohcgs/claude-code-my-workflowScaffold and run a reproducible Monte Carlo simulation study in R — a declared assumption regime, a parameterized DGP, an estimator grid, a seeded replication loop, and a summary of bias, RMSE, empirical SE, coverage, size/power with Monte Carlo standard errors. Use when the user says "run a Monte Carlo simulation", "simulation study", "check the bias/coverage of an estimator", "compare estimators in simulation", "size and power simulation", "Monte Carlo experiment", or wants to demonstrate an estimator's finite-sample properties. Produces a numbered R script in `scripts/R/` and saves per-replication raw results + a summary table to `output/`.ProductivityNo warnings★ 1.7K↓ —
- tilLeoYeAI/agent-master-skillsCapture and manage TIL (Today I Learned) entries on OpenTIL. Use /til <content> to capture, /til to extract insights from conversation, or /til list|publish|edit|search|delete|status|sync|tags|categories|batch to manage entries -- all without leaving the CLI.WritingNo warnings★ 2.2K↓ —
- canvasLeoYeAI/agent-master-skillsDisplay HTML content on connected OpenClaw nodes (Mac app, iOS, Android).OtherNo warnings★ 2.2K↓ —
- scenario-luma-videoscenario-labs/skillsUse when generating or editing video with Luma Ray models on Scenario via MCP: cinematic text-to-video, image-to-video from a start frame, start plus end frame anchors, seamless looping clips, HDR output, restyling footage while preserving motion with edit strengths and face, pose, depth, or trajectory controls, reframing to another aspect ratio by outpainting, or budget prompt edits on real footage. Keywords: Luma, Dream Machine, Ray 3.2, Ray 3, Modify Video, Reframe, T2V, I2V, V2V, loop, HDR.MediaNo warnings★ 1.9K↓ —
- gke-workload-securitygoogle/skillsAudits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running security audits (`audit_cluster.sh`), enforcing Network Policies (default-deny and Dataplane V2 logging), isolating high-risk pods inside GKE Sandbox (`gVisor`), enforcing Pod Security Standards (`restricted` labeling) and pod securityContext, and mounting Secret Manager secrets via CSI (`SecretProviderClass`). Use when auditing workload security posture, isolating namespaces, applying pod security standards, or configuring network policies and secret volume mounts. Don't use for Workload Identity (use gke-workload-identity), cluster-wide control plane security, RBAC hardening, Binary Authorization, Shielded Nodes, or enabling platform-level GKE add-ons (use gke-platform-security instead).OfficialSecurityNo warnings★ 21.8K↓ —
- qiskitK-Dense-AI/scientific-agent-skillsBuilds, simulates, transpiles, and executes quantum circuits with Qiskit and IBM Quantum Runtime. Use for Qiskit 2.x circuits and operators, V2 Sampler or Estimator primitives, target-aware transpilation, local or noisy simulation, IBM QPU execution, Runtime sessions or batches, error mitigation, and Qiskit ecosystem packages.OtherNo warnings★ 56K↓ —Also in 2 other repos
- appfunctionsandroid/skillsAnalyzes Android apps to find user workflows to expose as AppFunctions, such as creating a note, playing media, or sending a message. AI agents, voice commands, and system shortcuts then run them without opening the app UI. Generates Kotlin code with the androidx.appfunctions library, and refines KDoc and the app description so that agents choose and call functions correctly. Use this skill when discovering, implementing, documenting, testing, or upgrading AppFunctions in an Android app, including @AppFunctionDeclaration, @AppFunctionSerializable, @AppFunctionServiceEntryPoint, AppFunctionService, app_metadata.xml, appfn:instructions, adb shell cmd app_function, and legacy @AppFunction or AppFunctionConfiguration.Provider code. Don't use for building agents that call AppFunctions or for remote MCP servers.OfficialTestingNo warnings★ 10.3K↓ —
- pinchLeoYeAI/agent-master-skillsSecure agent-to-agent encrypted messaging via the Pinch protocol. Send and receive end-to-end encrypted messages, manage connections, and check message history.OtherNo warnings★ 2.2K↓ —
- ai-legal-opsKlotzkette/claude-fuer-deutsches-rechtFür digitale Werkzeuge und Legal Ops in der Kanzlei: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.LegalNo warnings★ 1.8K↓ —
- grow-appwondelai/skillsGuided journey from an app people sign up for and then quietly abandon to a sealed retention engine with a habit loop, an activated first run, and one metric the whole team trusts. Orchestrates eight skills phase by phase - hooked-ux, improve-retention, continuous-discovery, lean-ux, inspired-product, lean-analytics, microinteractions, drive-motivation - asking the user questions at every decision point and recording results in the project docs/ folder (PRODUCT.md, METRICS.md, GROW-APP-PLAN.md) so the journey resumes across sessions. Use when the user wants to lift activation and retention, design a habit loop, fix a leaky onboarding funnel, or says 'users sign up then disappear'. Do not use to fix broken UX or performance that no engagement mechanic can paper over - run improve-app first; if there is no app yet, use create-app. For one framework in isolation, invoke that skill directly.DataNo warnings★ 2.6K↓ —Also in 2 other repos
- design-postgres-tablestimescale/pg-aiguideUse this skill for general PostgreSQL table design. **Trigger when user asks to:** - Design PostgreSQL tables, schemas, or data models when creating new tables and when modifying existing ones. - Choose data types, constraints, or indexes for PostgreSQL - Create user tables, order tables, reference tables, or JSONB schemas - Understand PostgreSQL best practices for normalization, constraints, or indexing - Design update-heavy, upsert-heavy, or OLTP-style tables **Keywords:** PostgreSQL schema, table design, data types, PRIMARY KEY, FOREIGN KEY, indexes, B-tree, GIN, JSONB, constraints, normalization, identity columns, partitioning, row-level security Comprehensive reference covering data types, indexing strategies, constraints, JSONB patterns, partitioning, and PostgreSQL-specific best practices.DataNo warnings★ 1.9K↓ —
- slide-excellencepedrohcgs/claude-code-my-workflowMulti-agent comprehensive slide review (visual + pedagogy + proofreading, plus TikZ / parity / substance conditionally). Use when user says "full review", "excellence pass", "comprehensive check", "review everything", "pre-release review", "slide excellence", or before teaching / shipping a deck. Fanout wrapper — for a single lens, use `/visual-audit`, `/pedagogy-review`, or `/proofread` directly.DocumentsNo warnings★ 1.7K↓ —
- hivemind-goalsactiveloopai/hivemindCreate, track and update team goals in Hivemind via the `hivemind` CLI. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any actionable work item — the goal system replaced the legacy `hivemind tasks` CLI and now covers both objectives and tasks.EngineeringNo warnings★ 1.6K↓ —
- pitch-debriefKlotzkette/claude-fuer-deutsches-rechtFür Pitch Debrief: erstellt Entwurf mit Antrag, Beweis und Anlagen; Ergebnis: Schriftsatz mit Begründungs- und Anlagenlogik.OtherNo warnings★ 1.8K↓ —
- typeuibergside/typeuiUse TypeUI with Hermes Agent to access project design skills, brand kits, UI prompts, and layout variations through the TypeUI MCP server when creating or refining user interfaces.DesignNo warnings★ 2.2K↓ —
- hivemind-goalsactiveloopai/hivemindCreate, track and update team goals via the Deeplake virtual filesystem at memory/goal/. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any actionable work item — the goal system replaced the legacy `hivemind tasks` CLI and now covers both objectives and tasks.EngineeringNo warnings★ 1.6K↓ —
- branchenfokusKlotzkette/claude-fuer-deutsches-rechtFür Branchenfokus: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- matlabK-Dense-AI/scientific-agent-skillsBuilds, reviews, migrates, and plans MATLAB or GNU Octave numerical workflows. Use for arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.TestingNo warnings★ 56K↓ —Also in 2 other repos
- timescaledb-hyperfunctionstimescale/pg-aiguideUse this skill when writing analytical SQL over time-series data with the TimescaleDB Toolkit (timescaledb_toolkit extension) hyperfunctions: approximate percentiles, statistical summaries, time-weighted averages, counter/gauge rates, uptime/heartbeat tracking, state durations, OHLC candlesticks, approximate distinct counts, top-N, and downsampling. **Trigger when user asks to:** - Compute percentiles/medians/p95/p99 over large or rolled-up time-series data - Compute rates or deltas from monotonic counters (Prometheus-style) or gauges - Compute time-weighted averages or integrals over irregularly sampled data - Track uptime/downtime from heartbeats, or time spent in each state - Build OHLC/candlestick or VWAP data for financial ticks - Store re-aggregatable summaries in continuous aggregates (two-step aggregation, rollup) - Approximate COUNT DISTINCT, find top-N / most frequent values, or downsample for charts **Keywords:** timescaledb_toolkit, hyperfunctions, percentile_agg, uddsketch, tdigest, approx_percenDataNo warnings★ 1.9K↓ —
scenario-luma-video
scenario-labs/skills
From the author
Use when generating or editing video with Luma Ray models on Scenario via MCP: cinematic text-to-video, image-to-video from a start frame, start plus end frame anchors, seamless looping clips, HDR output, restyling footage while preserving motion with edit strengths and face, pose, depth, or trajectory controls, reframing to another aspect ratio by outpainting, or budget prompt edits on real footage. Keywords: Luma, Dream Machine, Ray 3.2, Ray 3, Modify Video, Reframe, T2V, I2V, V2V, loop, HDR.
Install
npx skills add scenario-labs/skills --skill scenario-luma-video -a claude-code
Installs to .claude/skills/scenario-luma-video/ · Each command fetches the skill straight from GitHub with the open skills CLI.
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