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.
49,456 skills from 2,407 repositories · updated 27 minutes ago
49,456 skills
- add-new-opc-skillReScienceLab/opc-skillsChecklist and automation guide for adding a new skill to the OPC Skills project. Ensures all required files, metadata, logos, and listings are created before release. Use when adding a new skill, publishing a skill, or preparing a skill for release.OtherNo warnings★ 1.9K↓ —
- deep-researchfeiskyer/claude-code-settingsMulti-agent research orchestration: split a research goal into parallel sub-goals, run each via headless `claude -p` subprocesses, aggregate results into a polished report file. Use for systematic web/document research, competitive or industry analysis, batch link/dataset processing, and long-form evidence synthesis. Triggers: "深度调研", "deep research", "wide research", "多 Agent 调研", "系统调研".ScienceNo warnings★ 1.7K↓ —
- einstieg-routingKlotzkette/claude-fuer-deutsches-rechtFür Einstieg und Routing: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Prozessrecht.OtherNo warnings★ 1.8K↓ —
- made-to-stickwondelai/skillsCraft messages that are understood, remembered, and drive action using the SUCCESs checklist (Simple, Unexpected, Concrete, Credible, Emotional, Stories). Use when the user mentions "make it memorable", "no one remembers our pitch", "tagline", "value proposition", "why the message isnt landing", "curse of knowledge", or "concrete language". Also trigger when writing a pitch deck, simplifying a complex product explanation, or making a presentation more compelling. Covers the six SUCCESs traits and the curse of knowledge. For narrative brand frameworks, see storybrand-messaging. For viral sharing, see contagious.DocumentsNo warnings★ 2.6K↓ —Also in 2 other repos
- grow-businesswondelai/skillsGuided journey from a business with lucky months to a repeatable growth engine that produces a forecast. Orchestrates nine skills phase by phase - one-page-marketing, hundred-million-offers, predictable-revenue, contagious, influence-psychology, crossing-the-chasm, cold-start-problem, lean-analytics, negotiation - asking the user questions at every decision point and recording results in the project docs/ folder (MARKETING.md, OFFER.md, METRICS.md, GROW-BUSINESS-PLAN.md) so the journey resumes across sessions. Use when the user wants to build a marketing and sales system, manufacture predictable pipeline, engineer word-of-mouth and referrals, or says 'revenue is real but lumpy and I need growth that repeats'. If the offer, retention, or operations underneath are broken, run improve-business first; with no paying customers yet, start with create-business; when the product itself must carry the growth loops, use grow-app. For one framework in isolation, invoke that skill directly.DataNo warnings★ 2.6K↓ —Also in 2 other repos
- gke-ai-troubleshooting-tpu-vbar-oomgoogle/skillsDiagnoses and prevents vbar_control_agent segfaults, out-of-memory (OOM) errors, and TPU device initialization failures on TPU v6e nodes in GKE caused by race conditions during TPU device resets or high-frequency metrics polling. Use when troubleshooting vbar_control_agent crashes, memory cgroup OOMs in serial console logs, tpu-device-plugin metrics checksum corruption errors, or custom TPU metrics collection conflicts on GKE TPU v6e nodes. Don't use for general non-TPU container OOM troubleshooting or standard GKE node lifecycle operations.OfficialProductivityNo warnings★ 22.2K↓ —
- respond-to-refereespedrohcgs/claude-code-my-workflowGenerate a structured response-to-referees document from a referee report and the revised manuscript. Maps each referee comment to the specific revision, classifies coverage (addressed / partially / deferred / disagreement), and drafts polite but firm responses. Use during the R&R (revise-and-resubmit) stage of paper revision.ScienceNo warnings★ 1.7K↓ —
- deep-auditpedrohcgs/claude-code-my-workflowComprehensive adversarial audit of a theory, proof, math/econ paper, codebase, or set of claims — decompose into components, fan out independent skeptics that must return CONCRETE defects, adjudicate every finding with a separate judge, fix all confirmed defects, then re-verify. Use when correctness must be bulletproof and single-pass or round-by-round review is too slow and too shallow. Invoke for "audit this rigorously", "find ALL the bugs/gaps", "make this rock solid", "converge faster on correctness".ScienceNo warnings★ 1.7K↓ —
- differential-auditpedrohcgs/claude-code-my-workflowCompare two implementations of the same thing — a port (R↔Python↔Stata), a reimplementation, a replication package, a refactor, or a new version against the old — so that agreement means something. Freeze inputs first, inventory every expected output, test the comparator itself, compare every channel (not just the headline number), and give each divergence a stable ID and a smallest witness. Use for cross-language parity, replication, upgrade/regression gates, or whenever "the numbers match" is about to license a claim.TestingNo warnings★ 1.7K↓ —
- scaffold-exercisespedrohcgs/claude-code-my-workflowScaffold a graded problem set with sections, problems, worked solutions, and short "why this matters" explainers across analytical, empirical, and coding types. Use when user says "make a problem set on X", "scaffold exercises for this lecture", "create practice problems", "generate homework with a solution key", "build a graded assignment on topic Y". Emits a clean student set plus a separate solution key — NOT for grading submissions or auto-checking student answers.EngineeringNo warnings★ 1.7K↓ —
- 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↓ —
- 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↓ —
- hunt-lfielementalsouls/Claude-BugHunterHunt Local File Inclusion (LFI), Remote File Inclusion (RFI), and Path Traversal — /etc/passwd read, log poisoning → RCE, PHP filter-chain RCE (no upload needed), php:// / data:// / zip:// / phar:// wrappers, RFI via allow_url_include, directory traversal read/write/delete. Covers OOB/blind LFI confirmation and false-positive discipline. Use when hunting file-include or path-traversal bugs on any target.WritingNo warnings★ 5.4K↓ —
- gke-alert-configurationgoogle/skillsConfigures alerting policies in Terraform for Google Kubernetes Engine (GKE) clusters, workloads, and services using PromQL and Google Cloud Managed Service for Prometheus. Use when writing, analyzing, validating, or deploying Terraform alerting policies to monitor GKE service latency, traffic, error rates using Multi-Window Multi-Burn-Rate SLO alerts, memory saturation, and cluster health such as CrashLoopBackOff and Node NotReady conditions. Don't use for non-GKE compute runtimes such as standalone Compute Engine VMs or standalone Cloud Run services without GKE.OfficialDevOpsNo warnings★ 22.2K↓ —
- scenario-chatgpt-pet-updatescenario-labs/skillsUse when changing an existing ChatGPT pet or Codex pet sprite sheet with Scenario: fixing a broken row, frame, jump or edge, regenerating one animation state, adding the sixteen look directions to a 1536x1872 v1 sheet, giving the pet a new outfit, color or accessory, renaming it in its pet.json, or checking a pet sheet and previewing it as an animated GIF.MediaNo warnings★ 2.8K↓ —
- stata-replicationpedrohcgs/claude-code-my-workflowEnd-to-end Stata replication pipeline — scaffolds numbered `.do` files in `scripts/stata/`, executes them via the `stata-mcp` MCP server, captures logs and outputs to `output/`, and produces publication-ready tables (esttab) and figures (graph export). Mirrors `/data-analysis` for R-first projects. Use when user says "stata replication", "set up Stata pipeline", "scaffold the .do files", "run Stata analysis", "AEA replication package in Stata", or when a project's analysis language is Stata not R.DataNo warnings★ 1.7K↓ —
- create-lecturepedrohcgs/claude-code-my-workflowCreate a new Beamer lecture `.tex` from source papers and materials, with notation consistency checks and the project's preamble wired in. Use when user says "create a lecture on X", "new lecture from these papers", "start a deck on topic Y", "scaffold a new Beamer file", "build me a lecture from these PDFs". Scaffolds the full deck — NOT for compiling existing `.tex` (use `/compile-latex`).DocumentsNo warnings★ 1.7K↓ —
- testing-setupandroid/skillsAnalyze and create a testing strategy for Android apps - install testing libraries, set up test infrastructure, create harnesses for unit tests, UI tests, screenshot tests, and end-to-end tests.OfficialTestingNo warnings★ 10.4K↓ —
- grant-proposalpedrohcgs/claude-code-my-workflowScaffold a research grant proposal (NSF, NIH, ERC, or foundation) by composing existing primitives — pulls identification strategy from an `/interview-me` spec, delegates the data-management plan to `/data-management-plan` and the facilities statement to `/capture-environment`, and emits a funder-requirements checklist. Use when user says "draft a grant", "write a proposal", "NSF proposal", "NIH aims", "ERC application", "foundation grant", "specific aims", or "scaffold a grant proposal". NOT a submission tool — produces a draft the user uploads to the sponsor's portal themselves.ScienceNo warnings★ 1.7K↓ —
- voice-profilepedrohcgs/claude-code-my-workflowExtract a written voice profile from your own prior papers, then use it to keep new drafts sounding like you. Reads a corpus one document at a time via subagents, produces a reusable profile on disk (lexicon, sentence rhythm, how you open and close, hedging habits, deliberate quirks), and audits a draft against it. Use when the user says "make this sound like me", "match my voice", "profile my writing", "why does this draft not sound like my papers", or before drafting prose that will carry their name. The positive counterpart to /humanize, which only detects AI tells.WritingNo warnings★ 1.7K↓ —
- power-analysispedrohcgs/claude-code-my-workflowCompute statistical power, required sample size, and minimum detectable effect (MDE) for a study design, then write a registry-ready power section. Handles two-arm RCTs (with clustering / ICC and unequal allocation), multiple-arm corrections, and a simulation-based power option for non-standard designs (DiD/event-study, IV, panel). Use when user says "power analysis", "power calculation", "MDE", "minimum detectable effect", "how big a sample do I need", "is my study powered", "power for an RCT", or when /preregister needs a power section for an experiment. Produces a power/MDE table, power curves, and a methods paragraph to paste into a preregistration.DesignNo warnings★ 1.7K↓ —
- verify-claimspedrohcgs/claude-code-my-workflowRun Chain-of-Verification (CoVe) on a draft or a block of text with factual claims. Spawns the `claim-verifier` agent in a fresh context (never a conversation fork) so it never sees the draft — then reports which claims are supported, contradicted, or unverifiable. Use when user says "verify these citations", "check the claims in X", "did I hallucinate anything", "fact-check this draft", "run CoVe on this", or after any text generation that asserts facts about papers, datasets, or numerical results. NOT for style/grammar review (use `/proofread`) or substance review (use `/review-paper`).ScienceNo warnings★ 1.7K↓ —
- scenario-minimax-videoscenario-labs/skillsUse when generating or editing video with MiniMax Hailuo models on Scenario via MCP: text-to-video, image-to-video, first and last frame anchors, reference images, videos, or audio, native stereo audio, bracketed camera commands, extending a clip, inserting a new scene into one, or recasting the people in it from photos. Keywords: MiniMax, Hailuo 3.0, H3, H3 Max, Turbo, Extend Video, Insert Video, Recast, Hailuo 2.3, T2V, I2V, V2V, 2K.MediaNo warnings★ 2.8K↓ —
- devils-advocatepedrohcgs/claude-code-my-workflowAdversarial 5-7 question challenge to a deck's pedagogical choices — ordering, prerequisites, cognitive load, motivation. Use when user says "devil's advocate", "poke holes in this deck", "push back on my slides", "stress-test the design", "what would a skeptical student ask?". Read-only; surfaces questions to force rethinking. Lighter than `/pedagogy-review`.TestingNo warnings★ 1.7K↓ —
mietsenkungsverlangen
Klotzkette/claude-fuer-deutsches-recht
OtherUpdated 20 hours ago
From the author
Für Mietsenkungsverlangen (Mietpreisbremse, WiStrG 1954, Wucher): ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.
Install
npx skills add Klotzkette/claude-fuer-deutsches-recht --skill mietsenkungsverlangen -a claude-code
Installs to .claude/skills/mietsenkungsverlangen/ · 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 onlyNo network use seenLicence: APACHE-2.0
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