Finance Investment Screening
SkillCommerce & financeScreen businesses or opportunities through explicit valuation, quality, balance-sheet, and confidence gates before deeper diligence.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Finance Investment Screening skill
What this skill tells your AI
The instructions your AI receives, as published by contextgo/contextgo in src/process/resources/skills/finance-analyst-pack/skills/finance-investment-screening/SKILL.md and read by ahel’s review.
Use this skill when the right output is a disciplined filter, not a full memo for every candidate.
Use when
- The user wants to screen several ideas or opportunities.
- You need to decide what deserves deeper diligence.
- Data quality varies across candidates and confidence must be part of the screen.
Do not use when
- The user already wants a full deep-dive memo on one candidate.
- No meaningful screening criteria can be defined.
- The available inputs are too thin even for directional gating.
Screening rules
- Define the gates before screening the names.
- A candidate can fail for valuation, quality, leverage, or confidence reasons.
- Missing data is a real screening factor, not a footnote.
- Classification should be simple and decision-oriented.
Workflow
1. Define the gates
Typical gates:
- valuation attractiveness
- business quality
- balance-sheet resilience
- execution or cycle risk
- confidence or data quality
2. Run the first-pass filter
For each candidate, classify whether it looks:
- attractive
- watchlist
- caution
3. Explain the blocking factor
If a candidate does not clear the bar, say whether the blocker is:
- too expensive
- weak quality
- fragile balance sheet
- low confidence due to missing data
4. Rank next-step priority
State:
- which candidate deserves deeper diligence first
- which should remain on a watchlist
- which should be deprioritized
Output format
Return:
1. Screening criteria
- gates used
- threshold logic
2. Candidate screen
- candidate
- classification
- main pass/fail reason
- confidence level
3. Priority order
- who deserves deeper work first
- what exact data would change borderline cases
Use together with
finance-comparable-valuationfinance-dcf-valuationfinance-thesis-stress-test
Signals
- GitHub stars
- 54
- Forks
- 5
- Last commit
- May 2026
Advanced
- Catalog kind
- skill
- Gateway key
finance-investment-screening- Source
- github.com/contextgo/contextgo