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 18 hours ago
48,622 skills
- 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.EngineeringNo warnings★ 3.3K↓ —Also in 1 other repo
- skill-account-diagnosisZJU-REAL/Easel账号诊断/起号体检：读取已完善的画像 Profile + 近期内容数据，诊断垂直度、定位清晰度、限流降权信号、流量池阶段，给出病因→证据→处方式的起号意见与发布建议。当用户说账号诊断/起号体检/为什么没流量/是不是被限流了/账号定位诊断/起号建议/怎么起号时使用OtherNo warnings★ 4.3K↓ —
- agent-analyticsdavepoon/buildwithclaudeAnalytics your AI agent can actually use. Track, analyze, run A/B experiments, and optimize across all your projects via CLI. Includes a growth playbook so your agent knows HOW to grow, not just what to track.DataNo warnings★ 3.7K↓ —
- gsd:resume-workdavepoon/buildwithclaudeResume work from previous session with full context restorationProductivityNo warnings★ 3.7K↓ —
- fix-cimichael-denyer/pstack-claudeFind failing PR checks, inspect logs or external check links, and apply focused fixesOtherNo warnings★ 3.7K↓ —
- property-based-testingtrailofbits/skillsWrites, reviews, and debugs property-based tests — Hypothesis, fast-check, proptest, jqwik, rapid, and Echidna or Medusa for Solidity invariants. Use whenever tests should cover a whole input domain instead of a hand-picked list of examples: encode/decode and serialize/deserialize pairs, parsers, canonicalizers and normalizers, validators, numeric and Decimal types, comparators and sort order, data structures, and smart-contract state invariants. Also use when adding cases to an existing @given, fast-check, or proptest suite, when judging whether existing property tests assert anything real, and when a generator has shrunk a counterexample and you need to tell a wrong property from a genuine bug. Not for coverage-guided binary fuzzing (libFuzzer, AFL), mutation-testing campaigns, static analysis, benchmarking, or end-to-end UI tests.TestingNo warnings★ 7.9K↓ —
- earnings-recaphimself65/finance-skillsAnalyze a company's most recent (or a specified past) earnings report from Yahoo Finance data (yfinance): actual vs estimated EPS, surprise size, revenue and margin trends, and the stock's price reaction. Use this skill whenever the user asks how earnings went — beat or miss, earnings surprise, quarterly results, the post-earnings move, or an earnings call recap — including casual references to a past report such as "AMZN reported last night" or "how did they do". For an upcoming report, use earnings-preview.FinanceNo warnings★ 3.5K↓ —
- constraint-driven-developmentaddyosmani/agent-skillsEstablishes a project's quality bar as a written contract and stops agents quietly lowering it. Interviews the user on which dimensions matter, supplies sane default thresholds when they have no number in mind, records everything in CONSTRAINTS.md, and watches the diff for a weakened bar — new @ts-ignore or eslint-disable suppressions, skipped or deleted tests, assertions stripped out, unimplemented stubs, thresholds edited down. Use when no quality bar is written down, when the user says "set up constraints" or "define our standards", when the user wants dimensions they care about — accessibility, web performance, coverage — set up as enforced constraints, when an agent keeps silencing checks or skipping tests to get to green, when you need a coverage or performance threshold and don't know what number to pick, or when an agent writes more code than anyone will read.TestingNo warnings★ 112.4K↓ —
- earnings-previewhimself65/finance-skillsBuild a pre-earnings briefing for a stock from Yahoo Finance data (yfinance): the upcoming report date and timing, consensus EPS and revenue estimates with their range, the beat/miss track record, analyst ratings and price targets, and what to watch in the print. Use this skill whenever the user is preparing for an upcoming earnings report or asks what the street expects — consensus or whisper numbers, EPS expectations, whether a company will beat, an earnings setup, or an earnings-season preview — and whenever a ticker comes up in the context of upcoming earnings, even without the word "preview". For results that are already out, use earnings-recap.FinanceNo warnings★ 3.5K↓ —
- cursor-ai-chatjeremylongshore/tons-of-skills-marketplaceMaster Cursor AI Chat with @-mentions, inline edit, and conversation patterns. Triggers on "cursor chat", "cursor ai chat", "ask cursor", "cursor conversation", "chat with cursor", "Cmd+L", "inline edit".WritingNo warnings★ 2.9K↓ —
- navan-sdk-patternsjeremylongshore/tons-of-skills-marketplaceDesign an application-owned Navan adapter pinned to the tenant's actual integration contract. Use when wrapping Booking API, Expense API, SFTP, or direct integration behavior. Trigger with "build a Navan client", "wrap Navan API", or "type Navan responses".DesignNo warnings★ 2.9K↓ —
- nemo-rl-auto-researchNVIDIA/skillsAutonomous NeMo-RL research agent workflow for directed hypothesis testing and open-ended discovery. Guides agents through the full experiment lifecycle: understanding recipes and environments, wiring RL or NeMo-gym runs, launching reproducible baselines and iterations, analyzing results, preserving human oversight, and using git plus TSV logs as the research ledger. Do NOT use for: bug fixes, code review, documentation, refactoring, dependency updates, or single-file changes.ScienceNo warnings★ 3.8K↓ —
- gsd:extract-learningsdavepoon/buildwithclaudeExtract decisions, lessons, patterns, and surprises from completed phase artifactsOtherNo warnings★ 3.7K↓ —
- principle-attack-the-premisemichael-denyer/pstack-claudeApply when two or more fixes that share one premise have failed the same gate. Write the premise down and test it directly before you write another fix that assumes it.TestingNo warnings★ 3.7K↓ —
- clade-install-authjeremylongshore/tons-of-skills-marketplaceInstall and configure the Anthropic SDK for Claude API access. Use when setting up Claude integration, configuring API keys, or initializing the Anthropic client in your project. Trigger with phrases like "install anthropic", "setup claude api", "anthropic auth", "configure anthropic API key".EngineeringNo warnings★ 2.9K↓ —
- tao-run-dinov3-ssl-deftNVIDIA/skillsRun iterative DINOv3 SSL DEFT data selection and retraining from an unlabeled pool, using GRIT or multi-task weakness and fixed-encoder retrieval. Use for active-learning-style DINOv3 mining, not plain pretraining/fine-tuning (tao-train-dinov3) or AOI/PAS DEFT.ProductivityNo warnings★ 3.8K↓ —
- hunt-regressionstrailofbits/skillsUse when discovering possible regressions from a pinned change and its callers before reproduction.OtherNo warnings★ 7.9K↓ —
- green-screenZJU-REAL/Easel绿幕抠像 / 换背景 / 合成：把绿幕（或蓝幕/指定色）拍摄的前景人物抠出来，合成到新背景——图片、视频、纯色或前景自身模糊。当用户说 绿幕、抠像、抠图换背景、去绿幕、chromakey、绿幕合成、换背景、蓝幕、把绿幕背景换掉、人物抠出来、绿布 时使用。基于 shared/scripts/chromakey.py（ffmpeg chromakey + despill）。与 video-reframe 区别：reframe 只改画幅不换背景；与 ai-image-gen 区别：那个生成新图，本 SKILL 处理已拍的绿幕素材。MediaNo warnings★ 4.3K↓ —
- audit-context-buildingtrailofbits/skillsUnderstand a codebase before looking for bugs in it - what each function assumes, what it guarantees, and what it depends on elsewhere. Use when starting an audit, threat model, or architecture review on unfamiliar code, and before any vulnerability-hunting pass.ProductivityNo warnings★ 7.9K↓ —
- paid-ads-amazonnowork-studio/notfair-pluginPlan and review Amazon Ads with margin-aware ACoS, product, and search-term guardrails. Use for Amazon advertising, Sponsored Products, Sponsored Brands, Sponsored Display, ASIN targeting, Amazon ACoS, or Amazon Ads performance exports.MarketingNo warnings★ 4.1K↓ —
- doca-sha-offload-engineNVIDIA/skillsUse this skill when wiring the DOCA SHA Offload Engine (an OpenSSL ENGINE) into an existing OpenSSL pipeline to offload one-shot SHA-1, SHA-256, or SHA-512 (EVP_Digest) onto DOCA SHA hardware without rewriting against doca-sha. Covers engine load mechanics (`openssl engine dynamic`, `set_pci_addr` ctrl, `-engine_impl`), the SHA-224 negative test that proves offload engaged, the message-size window where offload beats CPU SHA, and engine-vs-library selection. Trigger even when the user does not say "DOCA SHA Offload Engine" or "OpenSSL ENGINE" — typical implicit phrasings: "speed up openssl SHA on BlueField", "offload SHA without code changes", "is openssl using the accelerator or falling back to software", "prove DOCA SHA actually ran", "openssl dgst hashed but I'm not sure it was offloaded". Refuse and route elsewhere for new SHA pipelines (use doca-sha), MD5 / SHA-3 / SHA-224 / HMAC-SHA offload, incremental hashing via chained `EVP_DigestUpdate`, or OpenSSL PROVIDER authoring.TestingNo warnings★ 3.8K↓ —
- principle-never-block-on-the-humanmichael-denyer/pstack-claudeApply when tempted to ask 'should I do X?' on reversible work.OtherNo warnings★ 3.7K↓ —
- youtube-automationdavepoon/buildwithclaudeAutomate YouTube tasks via Rube MCP (Composio): upload videos, manage playlists, search content, get analytics, and handle comments. Always search tools first for current schemas.DataNo warnings★ 3.7K↓ —
- aflpptrailofbits/skillsSets up and runs AFL++ for multi-core fuzzing of C/C++ projects built with afl-clang-fast or afl-gcc-fast. Covers instrumentation modes, parallel main and secondary campaigns, persistent mode, corpus minimization, and crash triage. Use when scaling fuzzing across cores, fuzzing a mature C/C++ codebase, reading the afl-fuzz status screen, or moving on after libFuzzer has plateaued.OtherNo warnings★ 7.9K↓ —
tao-train-pointpillars
NVIDIA/skills
MediaUpdated 3 days ago
From the author
PointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a pillar-based representation, then applies 2D detection — used in autonomous driving and robotics. Use when training, evaluating, exporting, pruning, retraining, or running inference for a TAO PointPillars model. Trigger phrases include "train PointPillars", "LiDAR 3D detection", "point-cloud object detection", "pillar-based 3D detector".
Install
npx skills add NVIDIA/skills --skill tao-train-pointpillars -a claude-code
Installs to .claude/skills/tao-train-pointpillars/ · 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
Safety checks on SKILL.md
No warnings.
Why 90
Security100
Provenance83
Maintenance100
Licence100
Adoption57
Files (29)
- BENCHMARK.md
- SKILL.md
- config/skillspector-baseline.yaml
- evals/evals.json
- references/skill_info.yaml
- references/spec_template_dataset_convert.yaml
- references/spec_template_deploy_evaluate.yaml
- references/spec_template_deploy_gen_trt_engine.yaml
- references/spec_template_deploy_inference.yaml
- references/spec_template_evaluate.yaml
- references/spec_template_export.yaml
- references/spec_template_gen_trt_engine.yaml
- +17 more