finance-pro-playbooks

Guides investment research, valuation modeling, and deal-material workflows with professional data-sourcing rules.

Updated Aug 28, 2026
One-click install
npx skills add https://github.com/AnderHonorato/Mem-rias-IA---Infinity --skill finance-pro-playbooks-anderhonorato
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: finance-pro-playbooks
Source: https://github.com/AnderHonorato/Mem-rias-IA---Infinity/tree/main/Manus/Skills/finance-pro-playbooks
Command: npx skills add https://github.com/AnderHonorato/Mem-rias-IA---Infinity --skill finance-pro-playbooks-anderhonorato

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? General AI assistants produce finance deliverables that miss professional standards: wrong data sources, fiscal-period confusion, mixed GAAP/non-GAAP figures, and inconsistent formatting. This Skill encodes the workflows, data-source hierarchies, and silent industry defaults that experienced IB/PE/VC analysts apply, so outputs like DCF models, LBO structures, earnings updates, teasers, and CIMs meet institutional quality bars. ## Core Features & Use Cases - Task Routing Map: Matches any finance request (earnings analysis, DCF/comps/precedent valuation, LBO and debt structuring, due diligence, deal teasers, IC memos) to a dedicated playbook in references/ with step-by-step workflows, defaults, and pre-delivery checklists. - Data-Sourcing Discipline: Enforces a source hierarchy (filings > professional databases > media), a reference-date protocol, fiscal-time rules, and defenses against data traps like survivorship bias and adjusted-price mismatches. - Deliverable Standards: Applies finance-specific Excel and document formatting rules that supersede generic spreadsheet skills. - Use Case: Ask for an LBO model with an earnout for a target company, and the Skill builds an Entity Card, routes to the LBO and earnout playbooks, fetches data through the source pipeline, and delivers a formatted model with a full basis/time/assumptions disclosure. ## Quick Start Analyze the latest earnings of a public company and build an earnings update following the finance playbooks.

Frequently Asked Questions about finance-pro-playbooks

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a DCF or LBO model with correct assumptions?

Route the request through the valuation or LBO playbook, which supplies silent industry defaults such as forecast horizon and discounting convention. Every hardcoded input must trace to a cited source, and the delivery disclosure states which defaults were applied so you can override them.

What data sources should I use for financial analysis?

Follow the source hierarchy: primary filings and regulator disclosures first, then professional databases, then authoritative financial media. Connected providers take priority over built-in financial APIs, which take priority over public web fallbacks, and web-sourced figures must be cross-checked.

Can this skill handle private company screening and analysis?

Yes, it includes playbooks for private company screening, adverse media checks, and deal materials for private targets. However, earnings updates are restricted to listed companies because private firms lack public filings and tradeable prices.

Why does fiscal period labeling matter in company analysis?

Filing dates differ from fiscal periods, and companies like NVIDIA or Apple have non-calendar fiscal year ends. Mislabeling quarters propagates errors through YoY comparisons and tables, so the skill anchors all periods to the Entity Card's fiscal year-end month.

When should I not use this finance workflow skill?

Do not use it for quant trading system development, legal dispute calculations, or personal tax filing, as these are explicitly out of scope. Lightweight historical evaluation inside a research task remains in scope under the backtesting minimums.