Investor Materials
SkillDocs & knowledgeCreate and update pitch decks, one-pagers, investor memos, accelerator applications, financial models, and fundraising materials. Use when the user needs investor-facing documents, projections, use-of-funds tables, milestone plans, or materials that must stay internally consistent across multiple fundraising assets.
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 Investor Materials skill
What this skill tells your AI
The instructions your AI receives, as published by tan-yong-sheng/ai-vision-mcp in .claude/skills/investor-materials/SKILL.md and read by ahel’s review.
Build investor-facing materials that are consistent, credible, and easy to defend.
When to Activate
- creating or revising a pitch deck
- writing an investor memo or one-pager
- building a financial model, milestone plan, or use-of-funds table
- answering accelerator or incubator application questions
- aligning multiple fundraising docs around one source of truth
Golden Rule
All investor materials must agree with each other.
Create or confirm a single source of truth before writing:
- traction metrics
- pricing and revenue assumptions
- raise size and instrument
- use of funds
- team bios and titles
- milestones and timelines
If conflicting numbers appear, stop and resolve them before drafting.
Core Workflow
- inventory the canonical facts
- identify missing assumptions
- choose the asset type
- draft the asset with explicit logic
- cross-check every number against the source of truth
Asset Guidance
Pitch Deck
Recommended flow:
- company + wedge
- problem
- solution
- product / demo
- market
- business model
- traction
- team
- competition / differentiation
- ask
- use of funds / milestones
- appendix
If the user wants a web-native deck, pair this skill with frontend-slides.
One-Pager / Memo
- state what the company does in one clean sentence
- show why now
- include traction and proof points early
- make the ask precise
- keep claims easy to verify
Financial Model
Include:
- explicit assumptions
- bear / base / bull cases when useful
- clean layer-by-layer revenue logic
- milestone-linked spending
- sensitivity analysis where the decision hinges on assumptions
Accelerator Applications
- answer the exact question asked
- prioritize traction, insight, and team advantage
- avoid puffery
- keep internal metrics consistent with the deck and model
Red Flags to Avoid
- unverifiable claims
- fuzzy market sizing without assumptions
- inconsistent team roles or titles
- revenue math that does not sum cleanly
- inflated certainty where assumptions are fragile
Quality Gate
Before delivering:
- every number matches the current source of truth
- use of funds and revenue layers sum correctly
- assumptions are visible, not buried
- the story is clear without hype language
- the final asset is defensible in a partner meeting
Signals
- GitHub stars
- 78
- Forks
- 16
- Last commit
- Apr 2026
Advanced
- Catalog kind
- skill
- Gateway key
investor-materials-tan-yong-sheng- Source
- github.com/tan-yong-sheng/ai-vision-mcp