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Claude Skills by tools-only
github.com/tools-only19,166 skills18 installs6,168 views
- 1160 Installation Dc52a127**Version:** 1.0.0 **Last Updated:** October 10, 2025 **Installation Time:** 3-5 minutes ---Votes: 0GitHub stars: 9
- 1161 Cursor 6da2c00c**Last Updated:** February 5, 2026 **Status:** Production Ready **Difficulty:** Easy ⭐ ---Votes: 0GitHub stars: 9
- 1165 Cosmos Config 97dfb376This reference covers detailed Cosmos configuration for **dbt Core** projects.Votes: 0GitHub stars: 9
- 1165 Cosmos Config C40b937aThis reference covers detailed Cosmos configuration for **dbt Core** projects.Votes: 0GitHub stars: 9
- 1171 Claude Code Plugin 7cb50867The mcpbr Claude Code plugin makes Claude an expert at running benchmarks correctly. When you work with mcpbr in Claude Code, the plugin automatically provides specialized knowledge about commands, configuration, and best practices.Votes: 0GitHub stars: 9
- 1172 Apps 0e930b1cAPPS evaluates AI agents on 10,000 coding problems collected from open-access programming platforms, spanning introductory, interview, and competition difficulty levels.Votes: 0GitHub stars: 9
- 1172 Apps 2f27e535APPS evaluates AI agents on 10,000 coding problems collected from open-access programming platforms, spanning introductory, interview, and competition difficulty levels.Votes: 0GitHub stars: 9
- 1173 Bigcodebench 0e0a843aBigCodeBench evaluates AI agents on 1,140 practical coding tasks requiring function composition from 139 libraries across 7 domains, testing real-world library usage skills.Votes: 0GitHub stars: 9
- 1173 Bigcodebench D477bf0aBigCodeBench evaluates AI agents on 1,140 practical coding tasks requiring function composition from 139 libraries across 7 domains, testing real-world library usage skills.Votes: 0GitHub stars: 9
- 1174 Codereval 22430338CoderEval evaluates AI agents on pragmatic code generation from real-world open-source projects, testing the ability to implement functions with real project dependencies and context.Votes: 0GitHub stars: 9
- 1174 Codereval D598dc20CoderEval evaluates AI agents on pragmatic code generation from real-world open-source projects, testing the ability to implement functions with real project dependencies and context.Votes: 0GitHub stars: 9
- 1175 Cybergym 67bbfbf0CyberGym is a cybersecurity benchmark from UC Berkeley where agents generate Proof-of-Concept exploits for real C/C++ vulnerabilities across four difficulty levels.Votes: 0GitHub stars: 9
- 1175 Cybergym 97b8fca7CyberGym is a cybersecurity benchmark from UC Berkeley where agents generate Proof-of-Concept exploits for real C/C++ vulnerabilities across four difficulty levels.Votes: 0GitHub stars: 9
- 1175 Cybergym A1332d53CyberGym is a cybersecurity benchmark from UC Berkeley where agents generate Proof-of-Concept exploits for real C/C++ vulnerabilities across four difficulty levels.Votes: 0GitHub stars: 9
- 1176 Humaneval A56f5f43HumanEval evaluates AI agents on 164 Python programming problems from OpenAI, testing code generation from function signatures and docstrings with unit test verification.Votes: 0GitHub stars: 9
- 1176 Humaneval A8f592afHumanEval evaluates AI agents on 164 Python programming problems from OpenAI, testing code generation from function signatures and docstrings with unit test verification.Votes: 0GitHub stars: 9
- 1176 Humaneval B5e97b72HumanEval benchmark for mcpbr - 164 Python programming problems from OpenAI for evaluating code generation capabilities.Votes: 0GitHub stars: 9
- 1177 Math 7a91935dMATH benchmark for mcpbr - 12,500 competition mathematics problems from AMC, AIME, and other competitions across 7 subjects and 5 difficulty levels.Votes: 0GitHub stars: 9
- 1177 Math B6718919MATH benchmark for mcpbr - 12,500 competition mathematics problems from AMC, AIME, and other competitions across 7 subjects and 5 difficulty levels.Votes: 0GitHub stars: 9
- 1178 Mcptoolbench 1a836d59MCPToolBench++ benchmark for evaluating MCP tool discovery, selection, invocation, and result interpretation.Votes: 0GitHub stars: 9
- 1178 Mcptoolbench 23c2e0c1MCPToolBench++ evaluates AI agents on MCP tool discovery, selection, invocation, and result interpretation across 45+ categories with accuracy-threshold-based evaluation.Votes: 0GitHub stars: 9
- 1178 Mcptoolbench 39d6031bMCPToolBench++ evaluates AI agents on MCP tool discovery, selection, invocation, and result interpretation across 45+ categories with accuracy-threshold-based evaluation.Votes: 0GitHub stars: 9
- 1179 Repoqa 86f790e5RepoQA evaluates long-context code understanding by testing whether agents can find and identify specific functions within large repository codebases.Votes: 0GitHub stars: 9
- 1179 Repoqa B830f77cRepoQA evaluates long-context code understanding by testing whether agents can find and identify specific functions within large repository codebases.Votes: 0GitHub stars: 9
- 118 Onboarding 9f9ca6e1This guide provides instructions for setting up the Prompt-Driven Development (PDD) toolkit. It includes a quick start for users and a comprehensive guide for developers contributing to the project.Votes: 0GitHub stars: 9
- 118 Onboarding E59a6011This guide provides instructions for setting up the Prompt-Driven Development (PDD) toolkit. It includes a quick start for users and a comprehensive guide for developers contributing to the project.Votes: 0GitHub stars: 9
- 1180 Swe Bench B67bf4b4SWE-bench evaluates AI agents on real-world GitHub bug fixes, testing their ability to generate patches that resolve actual software issues from popular Python repositories.Votes: 0GitHub stars: 9
- 1180 Swe Bench E7347b99SWE-bench evaluates AI agents on real-world GitHub bug fixes, testing their ability to generate patches that resolve actual software issues from popular Python repositories.Votes: 0GitHub stars: 9
- 1181 Grayswan Edcebe54Use [Gray Swan Cygnal](https://docs.grayswan.ai/cygnal/monitor-requests) to continuously monitor conversations for policy violations, indirect prompt injection (IPI), jailbreak attempts, and other safety risks. Cygnal returns a `violation` score between `0` and `1` (higher means more likely to violate policy), plus metadata such as violated rule indices, mutation detection, and IPI flags. LiteLLM can automatically block or monitor requests based on this signal. ---Votes: 0GitHub stars: 9
- 1182 Profiling D8b52eddThis guide covers tools and techniques for profiling ContextForge performance under load. Use these methods to identify bottlenecks, optimize queries, and diagnose production issues. ---Votes: 0GitHub stars: 9
- 119 Fn 15 96t 35b676a9> **Implementation ready.** This spec contains all details needed for autonomous implementation.Votes: 0GitHub stars: 9
- 1190 Interview Ed1c35a4Interview user to clarify plan details and resolve ambiguitiesVotes: 0GitHub stars: 9
- 1192 Accessibility C05844e4All interactive elements need descriptive labels.Votes: 0GitHub stars: 9
- 1193 Anti Patterns 28cafe3fComprehensive catalog of common Apex anti-patterns, code smells, and how to fix them. ---Votes: 0GitHub stars: 9
- 1193 Anti Patterns 34543947A catalog of common SOQL mistakes and their solutions. Avoiding these patterns will help you stay within governor limits, improve query performance, and write more maintainable code. > **Sources**: [Apex Hours](https://www.apexhours.com/soql-best-practices/), [Beyond the Cloud](https://blog.beyondthecloud.dev/), [Medium - Bulkification Patterns](https://medium.com/@saurabh.samirs/salesforce-apex-triggers-5-bulkification-patterns-to-avoid-soql-dml-limits-f4e9c8bbfb3a) ---Votes: 0GitHub stars: 9
- 1193 Anti Patterns 694e39f4Comprehensive catalog of common Apex anti-patterns, code smells, and how to fix them. ---Votes: 0GitHub stars: 9
- 1193 Anti Patterns 731aeb39Common anti-patterns to detect in code diffs. Use alongside se-principles.md for balanced analysis -- principles show what's good, anti-patterns show what to watch for.Votes: 0GitHub stars: 9
- 1193 Anti Patterns B91ad4d9Common mistakes and pitfalls to avoid when implementing GitOps, with guidance on proper practices.Votes: 0GitHub stars: 9
- 1193 Anti Patterns D6509e23**Recognizing and avoiding common mistakes** ---Votes: 0GitHub stars: 9
- 120 Fn 20 Svm 49143ca3Blocked on native custom subagent support in Codex.Votes: 0GitHub stars: 9
- 121 Fn 22 53k 32bdd55fAdd review gate that runs when all epic tasks complete, BEFORE epic closes. Compares actual implementation against spec to find requirement gaps.Votes: 0GitHub stars: 9
- 1212 Review Package Analyzer F806c2eaAnalyze codebase and current work to identify files for a review package. Use when creating packages for external LLM review.Votes: 0GitHub stars: 9
- 1213 Commit And Push 356ae692Commit staged changes and push to the remote branchVotes: 0GitHub stars: 9
- 1214 New Project 4e56bcdfCreate a new project in the ai-sandbox monorepoVotes: 0GitHub stars: 9
- 1215 Verify 63feca65Run lint and typecheck to verify code quality before committingVotes: 0GitHub stars: 9
- 1216 Audit Checklist B2fae14aUse this checklist when reviewing motion design in any UI code. ---Votes: 0GitHub stars: 9
- 1216 Audit Checklist F5a32af5Comprehensive checklist for auditing Uniswap v4 hooks before deployment.Votes: 0GitHub stars: 9
- 1217 Direct Manipulation A Step Beyond Programming Languages C31bb6cbDirect Manipulation: A Step Beyond Programming Languages Ben Shneiderman, University of Maryland Direct manipulation systems offer the satisfying experience of operating on visible objects. The computer becomes transparent, and users can concentrate on their tasks. Leibniz sought to make the form of a symbol reflect its content. “In signs,” he wrote, “one sees an advantage for discovery that is greatest when they express the exact nature of a thing briefly and, as it were, picture it; then, i...Votes: 0GitHub stars: 9
- 1218 Macos Design Guide A5ac3be8Complete reference for designing and implementing native macOS apps.Votes: 0GitHub stars: 9
- 1219 Data Patterns 538c8e24Choose the right data fetching pattern for each use case.Votes: 0GitHub stars: 9