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.
45,604 skills from 2,205 repositories · updated 2 hours ago
44,573 skills
- pdfopenai/skillsUse when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.OfficialDocumentsNo warnings★ 28.3K↓ —Also in 3 other repos
- category-filtering-and-difficulty-analysisOpenSenseNova/SenseNova-Skills对Excel数据进行自定义分类统计、交叉分析与可视化，并基于多维度指标（如文本长度、术语密度、正则匹配等）进行综合评分与分级，适用于多类别数据分布统计及文本内容难度/质量评估场景。DocumentsNo warnings★ 5.9K↓ —
- ppt-analysisOpenSenseNova/SenseNova-SkillsPPT (.pptx/.ppt) 全量解析。覆盖：所有 slide 文本/表格/图表提取、嵌入图片 caption、纯图片 slide 渲染识别、数据标签提取。DocumentsNo warnings★ 5.9K↓ —
- reconciler-logicgrafana/skillsImplement reconcilers and watchers for grafana-app-sdk apps — write `TypedReconciler[*MyKind]` reconcile functions, apply generation-based skip patterns, do conflict-safe status updates via `resource.UpdateObject`, configure `BasicReconcileOptions` (namespace, label/field filters, finalizer management), use `Watcher` for event-style handling, reconcile `UnmanagedKinds` (resources your app doesn't own), and register the whole thing in `app.go`. Use when writing a reconciler, implementing the reconcile loop, adding async business logic, handling create/update/delete events, processing resource state changes, scheduling periodic resyncs with `RequeueAfter`, picking between Watcher and Reconciler, or wiring a controller into `app.go` — even when the user says "process this resource", "handle X events", or "write a controller" without saying "reconciler".OfficialWritingNo warnings★ 290↓ —
- k6-test-maintenancegrafana/skillsMaintain and improve existing k6 test scripts. Covers threshold tightening based on trend data, version migration between k6 releases, auto-fixing tests when the underlying service changes, refactoring for cleanliness, and auditing scripts against current best practices from docs. Use when the user asks to fix a failing k6 test, tighten thresholds, migrate a script to a new k6 version, refactor a test, update a script after a service change, or improve a script with best practices. Trigger on phrases like "fix my k6 test", "tighten my thresholds", "migrate to k6 v2", "update my test script", "refactor this k6 test", "my test is failing after a deploy", "apply best practices to my script", "modernize my k6 test", or "the service changed and my test broke". Also trigger when another skill (k6-trend-analysis or k6-cloud-investigate-test) hands off with a recommendation to edit a script. Maintains existing scripts; to author a new test use the k6 skill, or k6-browser-test for a browser test.OfficialTestingNo warnings★ 290↓ —
- commit-koepoko77-ai/im-not-aiAI(Claude 등)가 제안한 한글 커밋 메시지의 사무적·번역투 어휘("~을 수행함", "~을 진행함", "~적 개선을 실시함" 등)를 실제 개발자가 쓰는 자연스러운 한국어 커밋 메시지로 다듬는 스킬. humanize-korean과 달리 산문 문단이 아니라 1~2줄짜리 커밋 메시지 register에 특화되어 진단·청킹 없이 단일 콜로 즉시 처리한다. 트리거 — "커밋 메시지 자연스럽게", "커밋 메시지 다듬어줘", "이 커밋 메시지 AI 티 나", "commit message 한국어로 자연스럽게", "커밋 메시지 어색해", "커밋 메시지 사람처럼".EngineeringNo warnings★ 6.2K↓ —
- sn-da-large-file-analysisOpenSenseNova/SenseNova-Skills万行以上 Excel 数据集的高性能分析引擎。提供 openpyxl read_only 流式读取（iter_rows 支持 10 万行以上）、Parquet 转换加速、内存优化、分块处理和大文件写入模式。**遇到以下任一情况就主动使用本 skill**：①数据行数 ≥ 10k（由 sn-da-excel-workflow 的行数评估步骤触发）；②用户出现触发词：大文件 / 大数据量 / 性能优化 / 内存不足 / OOM / 百万行 / 十万行 / 流式读取 / Parquet / 分块处理 / large file / big data / streaming read / chunked processing；③直接使用 pd.read_excel() 导致超时或内存溢出；④用户明确要求对大规模数据集进行高性能处理。仅不用于：小于 10k 行的常规 Excel 分析（使用 sn-da-excel-workflow 即可）。DocumentsNo warnings★ 5.9K↓ —
- dynamic-percentage-and-large-file-analysisOpenSenseNova/SenseNova-Skills根据文件行数动态切换大文件处理策略（Parquet转换），通过逐行扫描或列匹配提取关键指标并计算占比、均值等统计量，最终输出结构化Excel报告及可视化图表。DocumentsNo warnings★ 5.9K↓ —
- melonjs-renderablesUpdatedmelonjs/melonJSUse this skill when subclassing Renderable, writing a custom draw() method, handling pointer or click events on game objects, applying post effects and shaders, or controlling draw order. Covers the pos-relative draw contract, isKinematic and input, addPostEffect vs the deprecated shader property, and z-ordering. Triggers on: Tween, easing, animate, Renderable, extends Renderable, draw(, update(, isKinematic, pointerEvent, registerPointerEvent, onClick, addPostEffect, removePostEffect, ShaderEffect, addChild, z-order, anchorPoint, floating.MediaNo warnings★ 6.4K↓ —
- sn-report-format-discoveryOpenSenseNova/SenseNova-Skills用于用户希望推荐研究成品形式，或最终形式无法从需求中直接判断时。把需求解析为一个简短的 format 字符串，不创建格式文件或 schema。OtherNo warnings★ 5.9K↓ —
- humanize-scanepoko77-ai/im-not-ai한글 글에 AI 티가 얼마나 있는지 재고, 실제로 고치면 어떻게 되는지 표본으로 보여주는 정찰 스킬. 실측 판별력 상위 6개만 본다. 워크스페이스·진단·게이트·서브에이전트 없이 이 대화 안에서 끝낸다(파일 0개, 서브에이전트 0회). 손볼 게 많다고 나오면 전수 윤문은 humanize-korean(=/humanize)으로 넘긴다. 트리거 — "이 글 AI 같아?", "AI 티 있나 봐줘", "스캔해줘", "윤문 돌릴 값어치 있나", "AI 티 점수", "quick humanize", "/humanize-scan".WritingNo warnings★ 6.2K↓ —
- designlang-tokensManavarya09/design-extractUse when styling UI for posthog.com — references the extracted design system tokens instead of inventing colors, spacing, or typography.DesignNo warnings★ 4.4K↓ —
- dowhybrycewang-stanford/Auto-Empirical-Research-SkillsCausal inference framework for answering "does X cause Y?" beyond correlation. DoWhy (Microsoft Research) provides the identify-estimate-refute loop: define a causal graph (DAG), identify the causal effect using backdoor/frontdoor/instrumental variable criteria, estimate treatment effects with multiple estimators, and validate results with automated refutation tests. Use when: distinguishing causation from correlation, estimating treatment effects (ATE, ATT, CATE), designing and analyzing A/B tests with confounders, using instrumental variables, performing counterfactual reasoning ("what would have happened if..."), validating causal claims with sensitivity analysis, working with observational data where randomization is impossible, or any analysis where the question is "what is the CAUSAL effect of X on Y" rather than just "how do X and Y relate?"TestingNo warnings★ 4.8K↓ —
- diffdockaipoch/open-sciencePredict small-molecule binding poses with DiffDock-L (Corso et al. 2023/2024, github.com/gcorso/DiffDock) — blind diffusion docking that places a ligand into a protein pocket without a predefined search box and ranks the samples with a learned confidence model. Reach for this skill to dock a SMILES or SDF against a PDB, to generate ranked 3D poses for a small fragment library, or to get a starting pose for downstream rescoring. DiffDock predicts geometry, not affinity.ScienceNo warnings★ 5.4K↓ —
- customizeaipoch/open-scienceUse when the user wants to create or manage a Specialist agent or create, revise, publish, or delete a Skill through the conversational `/Customize` entry. Routes Skill work to the internal skill-creator and handles Specialist work through the JavaScript host.agents SDK.PlanningNo warnings★ 5.4K↓ —
- synthetic-monitoring-checksgrafana/skillsAuthor Grafana Cloud Synthetic Monitoring checks, with deep coverage of k6 scripted and browser checks: SM's single-VU/single-iteration execution model, assertions that actually fail probe_success (expect() and fail() vs bare check()), secrets, deterministic scripts, robust browser locators, local validation with k6 run, deployment via UI/API/Terraform, verifying probe_success, and rollback. Also helps choose the simplest sufficient check type (HTTP/ping/DNS/TCP, MultiHTTP, scripted, browser). Use when writing a synthetic check, monitoring a login/checkout/signup flow in production, converting a k6 script or an OpenAPI spec into a check, authoring a browser check, validating a user journey, or asking "is my site up from multiple regions". NOT for load, stress, or performance testing — SM runs one iteration per execution; for load tests use the grafana-k6 plugin or Grafana Cloud k6. For the broad Grafana Cloud Testing overview (SM + k6 Cloud + Faro), use the testing skill.OfficialTestingNo warnings★ 290↓ —
- thinktw93/WazaTurns rough ideas into approved, decision-complete plans before coding. Use when planning architecture, judging whether to build, or writing a handoff. Not for bug fixes or small edits.WritingNo warnings★ 7.4K↓ —Also in 1 other repo
- sn-updateOpenSenseNova/SenseNova-SkillsUpdate SenseNova Skills (the sn-* bundle) inside an OpenClaw or hermes-agent install. ALWAYS use this skill when the user says any of: "update SenseNova skills", "update SN skills", "更新 sensenova skills", "更新 sn skills", "刷新 sn-*", "升级 sn-* skills", or names a specific sn-* skill to update (e.g. "更新 sn-ppt-standard", "refresh sn-image-base"). Default scope is the whole sn-* bundle; if the user names specific skills, update ONLY those.MediaNo warnings★ 5.9K↓ —
- replica-reconJakeschincariol/replica-skillReverse-engineers any app into a recon map: screen inventory, user flows, component list, inferred data model and a feature matrix, from public pages, screenshots, app store listings, help docs and the user's own account. The first step of the Replica pack. Use when the user says "clone this app", "reverse engineer X", "how does X work", "map out X", "what screens does X have", "I want to build my own version of X", "copy this app", or pastes an app's URL or App Store link and wants to rebuild it.OtherNo warnings★ 5.4K↓ —
- slr-prismabrycewang-stanford/Auto-Empirical-Research-SkillsGuide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.DocumentsNo warnings★ 4.8K↓ —
- deepchat-sdd-cleanupThinkInAIXYZ/deepchatUse only when a developer explicitly asks to clean, prune, tidy, or organize DeepChat SDD documentation after implementation and validation. Scans docs/features, docs/issues, and docs/architecture; prefers multi-agent review when available; removes completed issue docs when a linked GitHub issue is closed or implementation and validation evidence proves the bug no longer exists, drops stale plans and legacy task files from completed feature or architecture goals, and deletes obsolete feature or architecture docs.PlanningNo warnings★ 6.4K↓ —
- sn-team-harnessOpenSenseNova/SenseNova-SkillsUse when a user asks what SenseNova Team Harness is, wants an introduction or overview, is getting started, or is deciding whether it fits — a self-hosted workspace where people and local AI agents collaborate on conversations, projects, work items, and artifacts. Covers its core concepts (Workspace, Project, Conversation, Agent, WorkItem, Resource, Artifact, Local Computer), main capabilities, how to run it, and the basic usage flow.OtherNo warnings★ 5.9K↓ —
- html-injection-testingzebbern/claude-code-guideThis skill should be used when the user asks to "test for HTML injection", "inject HTML into web pages", "perform HTML injection attacks", "deface web applications", or "test content injection vulnerabilities". It provides comprehensive HTML injection attack techniques and testing methodologies.TestingNo warnings★ 4.7K↓ —
- marginaleffectsbrycewang-stanford/Auto-Empirical-Research-SkillsManual for the marginaleffects R and Python package, and guide to the book "Model to Meaning". Use when users ask about predictions, comparisons, slopes, marginal effects, average treatment effects (ATE/ATT/CATE), hypothesis testing, contrasts, counterfactuals, risk ratios, odds ratios, causal inference with G-computation, or need help with marginaleffects functions like predictions(), comparisons(), slopes(), hypotheses(), datagrid(), avg_predictions(), avg_comparisons(), avg_slopes(), or plot functions.TestingNo warnings★ 4.8K↓ —
create-plan
composio-community/awesome-codex-skills
PlanningUpdated Jul 26, 2026
From the author
Create a concise plan. Use when a user explicitly asks for a plan related to a coding task.
Install
npx skills add composio-community/awesome-codex-skills --skill create-plan -a claude-code
Installs to .claude/skills/create-plan/ · 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 91
Security100
Provenance91
Maintenance85
Licence100
Adoption66
Files (2)
- LICENSE.txt
- SKILL.md