FP&A prompts & agent repo
What happened
A cluster of posts shared AI prompt sets—'5 prompts that will change how you study accounting' and Perplexity-style prompts mimicking high-end advisors—plus a public GitHub repo of agent skills for financial analysis and trading. The content packages practical prompts and agent blueprints to convert raw financial data into crisp recommendations. (x.com) (x.com) (x.com)
Why it matters
A public repository titled "finance-skills-11" surfaces in the thread as a packaged collection of agent skills aimed specifically at financial analysis and trading, with a DEMOS.md and setup notes in its README. (github.com) The finance-skills-11 README includes an explicit “not financial advice” disclaimer and recommends installation as a Claude Code plugin, indicating the author intended the code for experimentation rather than production trading. (github.com) Parallel collections advertise “plug-and-play” skill modules that wire agents to real‑time news, price feeds, sentiment, and basic market-prediction utilities—RKiding’s Awesome-finance-skills describes exactly those capabilities in its repo blurb. (github.com) A separate research project, TradingAgents, documents a multi-agent framework that assigns roles (fundamental analyst, sentiment analyst, technical analyst, trader, risk manager) and reports experimental results on collaborative decision-making. (github.com) Examples of concrete modules across these repos include financial-data collectors that pull statements and metrics, automated ratio calculators (gross/operating/net margin, current ratio, debt/equity), risk tools like VaR and Sharpe, and templated recommendation generators that output buy/hold/sell guidance. (lobehub.com) Several of the published skill collections and indexes are explicitly labeled educational or research-grade and include demos/screenshots rather than production SLAs, signaling the need for FP&A-style validation, data governance, and mapping agent outputs to executive KPIs (revenue, margin, working capital) before use in C-suite decision documents. (github.com)
Key numbers
- A cluster of posts shared AI prompt sets—'5 prompts that will change how you study accounting' and Perplexity-style prompts mimicking high-end advisors—plus a public GitHub repo of agent skills for financial analysis and trading.
- (x.com) (x.com) (x.com) A public repository titled "finance-skills-11" surfaces in the thread as a packaged collection of agent skills aimed specifically at financial analysis and trading, with a DEMOS.md and setup notes in its README.
- (github.com) The finance-skills-11 README includes an explicit “not financial advice” disclaimer and recommends installation as a Claude Code plugin, indicating the author intended the code for experimentation rather than production trading.
What happens next
- (github.com) A cluster of posts shared AI prompt sets—'5 prompts that will change how you study accounting' and Perplexity-style prompts mimicking high-end advisors—plus a public GitHub repo of agent skills for financial analysis and trading.
Quick answers
What happened in FP&A prompts & agent repo?
A cluster of posts shared AI prompt sets—'5 prompts that will change how you study accounting' and Perplexity-style prompts mimicking high-end advisors—plus a public GitHub repo of agent skills for financial analysis and trading. The content packages practical prompts and agent blueprints to convert raw financial data into crisp recommendations. (x.com) (x.com) (x.com)
Why does FP&A prompts & agent repo matter?
A public repository titled "finance-skills-11" surfaces in the thread as a packaged collection of agent skills aimed specifically at financial analysis and trading, with a DEMOS.md and setup notes in its README. (github.com) The finance-skills-11 README includes an explicit “not financial advice” disclaimer and recommends installation as a Claude Code plugin, indicating the author intended the code for experimentation rather than production trading. (github.com) Parallel collections advertise “plug-and-play” skill modules that wire agents to real‑time news, price feeds, sentiment, and basic market-prediction utilities—RKiding’s Awesome-finance-skills describes exactly those capabilities in its repo blurb. (github.com) A separate research project, TradingAgents, documents a multi-agent framework that assigns roles (fundamental analyst, sentiment analyst, technical analyst, trader, risk manager) and reports experimental results on collaborative decision-making. (github.com) Examples of concrete modules across these repos include financial-data collectors that pull statements and metrics, automated ratio calculators (gross/operating/net margin, current ratio, debt/equity), risk tools like VaR and Sharpe, and templated recommendation generators that output buy/hold/sell guidance. (lobehub.com) Several of the published skill collections and indexes are explicitly labeled educational or research-grade and include demos/screenshots rather than production SLAs, signaling the need for FP&A-style validation, data governance, and mapping agent outputs to executive KPIs (revenue, margin, working capital) before use in C-suite decision documents. (github.com)
