thesis-matching
Matches inbound deals against investment thesis criteria and fund strategy
Best use case
thesis-matching is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Matches inbound deals against investment thesis criteria and fund strategy
Teams using thesis-matching should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/thesis-matching/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How thesis-matching Compares
| Feature / Agent | thesis-matching | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Matches inbound deals against investment thesis criteria and fund strategy
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Thesis Matching ## Overview The Thesis Matching skill provides systematic matching of inbound investment opportunities against the fund's investment thesis, strategic priorities, and portfolio construction criteria. It enables rapid triage of deal flow while ensuring alignment with fund strategy. ## Capabilities ### Investment Thesis Encoding - Encode multi-dimensional investment thesis criteria - Define sector focus areas and exclusions - Specify stage preferences and check size ranges - Articulate strategic themes and conviction areas ### Deal Matching Analysis - Match incoming deals against thesis dimensions - Score alignment across criteria with weighted importance - Identify thesis exceptions worth considering - Flag anti-thesis or exclusion criteria matches ### Portfolio Construction Fit - Assess portfolio concentration and diversification - Check against sector and stage allocation targets - Evaluate vintage year and deployment pacing - Consider follow-on reserve requirements ### Thesis Evolution Tracking - Track thesis adjustments over fund lifecycle - Document thesis exceptions and rationale - Analyze deal flow patterns vs. thesis alignment - Support thesis refinement for successor funds ## Usage ### Match Deal to Thesis ``` Input: Deal summary, company data, sector classification Process: Compare against thesis criteria, score alignment Output: Thesis match score, alignment details, flags ``` ### Triage Inbound Flow ``` Input: Batch of inbound deals Process: Rapid thesis matching and prioritization Output: Prioritized list, pass recommendations, review queue ``` ### Analyze Portfolio Fit ``` Input: Potential investment, current portfolio Process: Assess concentration, diversification, reserves Output: Portfolio fit analysis, construction implications ``` ### Update Thesis Definition ``` Input: Revised thesis criteria, rationale Process: Update thesis model, recalculate pipeline matches Output: Updated thesis, pipeline re-scoring results ``` ## Thesis Dimensions | Dimension | Typical Criteria | |-----------|------------------| | Sector | Software, Healthcare, Fintech, Consumer, etc. | | Stage | Pre-seed, Seed, Series A, Growth | | Geography | North America, Europe, Global | | Business Model | SaaS, Marketplace, Consumer, Deep Tech | | Check Size | $500K - $2M, $5M - $15M, etc. | | Themes | AI/ML, Climate, Future of Work, etc. | ## Integration Points - **Deal Flow Tracker**: Automatic thesis scoring on deal entry - **Deal Scoring Engine**: Feed thesis match into composite score - **Proactive Deal Sourcing**: Guide sourcing toward thesis areas - **IC Memo Generator**: Include thesis alignment analysis ## Best Practices 1. Clearly document thesis with specific, measurable criteria 2. Define "core thesis" vs. "opportunistic" boundaries 3. Track and document all thesis exceptions 4. Review thesis alignment quarterly with deal flow patterns 5. Evolve thesis thoughtfully as market conditions change
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