SkillsAdd

ifuryst/aifi · Archived

company-research-workflow

Orchestrate a full AIFi company research workflow from a user request such as "understand Intel recently" into target resolution, evidence archiving, news, filings, earnings, financials, market signals, competitive landscape, and investment thesis synthesis.

First seen Aug 8, 2026

Installation

$ npx skills add ifuryst/aifi --skill company-research-workflow
View on skills.sh ↗ GitHub repository ↗

Summary

  • Orchestrate a full AIFi company research workflow from a user request such as "understand Intel recently" into target resolution, evidence archiving, news, filings, earnings, financials, market signals, competitive landscape, and investment thesis synthesis.
  • Use when multiple AIFi research skills must be combined into one application-like workflow.

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Also in this package

Other skills from ifuryst/aifi · top by installs.

npx skills add ifuryst/aifi
chart-visualization 3 company-news-research 2 valuation-scenario-analysis 2 resend-email-cli 2 research-target-resolver 2 research-evidence-archive 2 portfolio-exposure-review 2 market-signal-analysis 2 investment-thesis-synthesis 2 investment-risk-diligence 2

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 22
License LICENSE
Default branch main
Open issues 0
Status Archived

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,209 B
  • docs SUMMARY.md 383 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 2 installs

SKILL.md

Company Research Workflow

Use this skill when the user asks for a complete company-level investment research run. It composes narrower skills and keeps the persistent archive as the shared memory layer.

Workflow

  1. Run research-target-resolver.
  2. Run research-evidence-archive to create or load the target archive.
  3. Decide which collection skills are needed for the user's question.
  4. Run independent collection skills in parallel when possible:

company-news-research, company-filing-research, earnings-call-analysis, financial-snapshot-analysis, market-signal-analysis, competitive-landscape-analysis, investment-risk-diligence, and valuation-scenario-analysis when valuation, margin of safety, or price-implied expectations matter.

  1. Save all source notes and raw files through research-evidence-archive.
  2. Run investment-thesis-synthesis only after evidence coverage is visible.
  3. Run portfolio-exposure-review when the user asks about sizing, adding,

trimming, holding, watchlists, or portfolio fit.

  1. Return the final artifact paths, major findings, gaps, and suggested next

research runs.

Read references/intel-example-workflow.md for the default Intel-like scenario.

Skill Selection

  • User asks "what happened recently": prioritize target, archive, news, filings,

earnings, market, then thesis.

  • User asks "is the business improving": prioritize filings, earnings,

financials, competitors, risks, then thesis.

  • User asks "why did the stock move": prioritize news, earnings, market, then

filings if the event is disclosure-driven.

  • User asks "how does it compare": prioritize target, financials, competitors,

market, then thesis.

  • User asks "what is it worth" or "is it priced in": prioritize target,

financials, filings, peers, market, risks, valuation scenarios, then thesis.

  • User asks "what can go wrong": prioritize target, filings, earnings, news,

financials, market, risk diligence, then thesis.

  • User asks "how much should I own" or "does this fit my portfolio": prioritize

target, thesis, valuation, risks, market, portfolio context, then portfolio exposure review.

Output

Return:

  • skills executed
  • archive paths touched
  • evidence coverage table
  • risk diligence path when created
  • valuation scenario path when created
  • final memo or decision-frame path
  • portfolio review path when created
  • unresolved gaps
  • recommended follow-up skills

Quality Gate

Before finishing:

  • do not synthesize before evidence coverage is known
  • store reusable materials in research/ instead of leaving them only in chat
  • label current-data retrieval failures
  • keep user-facing conclusions tied to archived evidence
  • avoid autonomous trading, broker actions, or certainty about future returns