32 boosters for "discovery" — open source, verified from GitHub, ready to install
A senior pre-sales engineering agent that handles technical discovery, demo engineering, and POC scoping to win technical decisions and close deals. Ideal for B2B SaaS teams, sales leaders, and product managers who need to bridge technical capabilities with business outcomes.
Discovery Coach trains sales teams on advanced buyer discovery techniques—question design, needs mapping, and gap quantification—to uncover real buying motivation and win deals at the discovery stage. Sales leaders, account executives, and SDRs benefit from structured methodology coaching.
A comprehensive Product Manager agent that guides users through the entire product lifecycle—from discovery and strategy to launch and measurement—by synthesizing business goals, user needs, and technical constraints. Ideal for founders, product leaders, and teams looking to validate ideas, build roadmaps, and make data-driven shipping decisions.
Heuristic scoring (no AI key configured).
This skill parses natural language shopping queries to extract structured product requirements like attributes, price limits, and specifications for e-commerce agents. It benefits developers building AI-powered shopping assistants and agents that need intelligent query understanding.
This is the universal AI skills library — 204 production-ready skill packages across 13 professional domains with 559 Python automation tools and 12 sample CI/CD workflows. It works with every major AI coding assistant. This is NOT a traditional application. It's a library of self-contained skill pa
A systematic debugging skill for web applications that leverages Chrome DevTools and Playwright MCPs to troubleshoot APIs, authentication flows, and UI issues. Developers working with web apps will benefit from its structured debugging approach and intelligent context discovery.
"name": "sciagent-skills", "description": "Life sciences computational skills for scientific AI agents — 60+ skills covering genomics, proteomics, drug discovery, biostatistics, scientific computing, and scientific writing", "name": "jaechang-hits"
Use this skill as the end-to-end coordinator for GA4 + GTM tracking delivery. Do not assume the user wants the full workflow. <!-- analytics-tracking-automation auto-update bootstrap:start -->
Use this skill for analysis-only work and fresh workflow bootstrap. In this repository, use the repo-root wrapper: launches a real Chromium via Playwright to fetch the target site over HTTP. Run it in an environment that permits outbound network and local browser execution; environments that restric
Opportunity-Solution Trees help product teams structure discovery work and connect customer needs to solutions using Teresa Torres's framework. Useful for product managers, researchers, and developers deciding what to build and validating assumptions.
Use this skill for analysis-only work and fresh workflow bootstrap. In this repository, use the repo-root wrapper: Run outside sandboxed environments by default. Do not first attempt the Playwright crawl inside the sandbox and then retry after it is intercepted.
This is a TypeScript project — AI content pipeline using Claude Agent SDK + MCP. Use strict TypeScript, follow ESLint rules, prefer async/await.
"name": "claudikins-tool-executor", "description": "Configurable MCP wrapper that consolidates your tools into just 3, using semantic search for on-demand discovery and sandboxed TypeScript execution. Ships with 7 example servers (96 tools) - reduces context consumption by 97% (48k tokens down to 1.
"name": "codebase-context", "description": "Pre-maps your codebase architecture, conventions, and team memory so AI agents navigate with precision instead of exploring. Local-first MCP server with AST-backed hybrid search.", "main": "./dist/lib.js",
"name": "productskills", "name": "Tair Asim", "url": "https://github.com/assimovt"
"description": "Cognitive brainstorming protocol for Claude Code. Structures thinking through GROUND (problem discovery) -> EXPLORE (divergent) -> DECIDE (convergent) -> STRESS (stress-test) -> SHIP (artifacts) phases. Includes domain skills for technical architecture and conceptual work.", "name":
"name": "revenue-os", "description": "Revenue Operating System - From code to customers to cash. A comprehensive monetization toolkit for developers.", "name": "Vladyslav Podoliako",
Search academic papers via the Semantic Scholar API using a structured 4-phase workflow. Parse the user's intent and choose a search strategy: Write ONE Python script. Example:
"name": "prfaq-dev", "description": "Amazon Working Backwards PR/FAQ process — generate professional LaTeX documents for product discovery and decision-making", "name": "Punt Labs",
"name": "medical-mcps", "version": "0.1.17", "description": "Comprehensive biological and medical research data integration server providing unified access to 13+ specialized databases including Reactome (pathways), KEGG (pathways/diseases), UniProt (proteins), ChEMBL (drug discovery), PubMed (liter
"name": "genomic-agent-discovery", "description": "AI agents that collaborate to analyze your DNA. 20+ MCP tools, 16 databases, real-time dashboard. Runs locally.", "main": "src/cli.mjs",
"name": "claude-evolve", "description": "Evolutionary code discovery using Claude Code models", "repository": "https://github.com/samuelzxu/claude-evolve",
