What does oss-search do?
Open-source intent searcher: describe requirements → automatically decompose capabilities → perform multi-source search across GitHub/npm/PyPI → score and rate → output a selection report. Can be used as a Claude Skill.
Open-source intent searcher: describe requirements → automatically decompose capabilities → perform multi-source search across GitHub/npm/PyPI → score and rate → output a selection report. Can be used as a Claude Skill.
The oss-search skill is an open-source intent searcher that automates the process of discovering and evaluating open-source libraries and tools. When you describe your requirements in natural language, the skill automatically decomposes them into capabilities and conducts a multi-source search across GitHub, npm, and PyPI. It then scores and rates the results, providing a comprehensive selection report. This is particularly useful for developers and AI agents who need to quickly find the best open-source solutions without manually scouring multiple repositories. It supports popular platforms and can be used as a Claude Skill, making it a powerful tool for project planning and technology selection.
npx skills add dacai369/oss-searchInstalled? Explore more Research & Data Analysis skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Open-source intent searcher: describe requirements → automatically decompose capabilities → perform multi-source search across GitHub/npm/PyPI → score and rate → output a selection report. Can be used as a Claude Skill.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.