Traction scoreGitHub stars can be faked, so popularity alone can be misleading. Traction Score looks for broader signs of recent attention, adoption, and active maintenance.
This skill applies a structured bottleneck analysis method to evaluate technology and advanced-manufacturing investments. It assists researchers in conducting theme scans, comparing candidates, and testing company theses by translating broad labels into specific claims that can be verified against current disclosures.
WHO IT'S FOR
Investment researchers
performing supply-chain bottleneck analysis on stocks
Equity analysts
challenging company theses against current disclosures
Retail investors
scanning themes for high-priority research candidates
AI agent builders
integrating specialized investment research workflows into agents
Compatible AgentsThe repository documents support for these agents. The skills may also work with other agents that can load SKILL.md files, but they may need some setup or small changes.
Current web-search, browsing, or filing access supplied by the host agent
Use serenity-skill to challenge the claim that [company name] is a “[supplier label].” Test the claim against current disclosures, distinguish development, sampling, qualification, production, orders, and recognized revenue, and give a bounded preliminary judgment with dated evidence and the main condition that would change it.
Two company names replacing [company A] and [company B]
Requested market if it is not A-shares
Current web-search, browsing, filing, or market-data access supplied by the host agent
Use serenity-skill to compare [company A] and [company B] using a comparable reporting period. Summarize each company's supply-chain position, earnings exposure, evidence quality, valuation pressure, and failure conditions, then identify which one deserves further research first.