investor-research

investor-research is a skill for Claude Code, Codex from Maudeunfledged834/startup-founder-skills. It costs 53 tokens per session (1,690 once invoked), scanned A, a copy of investor-research, MIT.

A research guide for finding and prioritizing investors for a fundraising round. It considers factors such as stage, sector, location, typical investment size, and conflicts with existing investments.

In plain words
What is it for?
Use it to build or review a list of venture capital firms and individual investors, decide who to pitch, and investigate a specific fund's investment focus or portfolio.
Why use it?
It helps replace a broad investor search with a list matched to the company and round. It also helps founders understand an investor's focus, portfolio, and decision process before making contact.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to build or review a list of venture capital firms and individual investors, decide who to pitch, and investigate a specific fund's investment focus or portfolio.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/maudeunfledged834/startup-founder-skills/investor-research
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Maudeunfledged834/startup-founder-skills --skill investor-research
Clone the repo
git clone --depth 1 https://github.com/Maudeunfledged834/startup-founder-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for investor-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/maudeunfledged834/startup-founder-skills/investor-research/github.svg)](https://agentmods.dev/skills/maudeunfledged834/startup-founder-skills/investor-research)
Your own site
<a href="https://agentmods.dev/skills/maudeunfledged834/startup-founder-skills/investor-research"><img src="https://agentmods.dev/badge/skills/maudeunfledged834/startup-founder-skills/investor-research/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for investor-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/maudeunfledged834/startup-founder-skills/investor-research"><img src="https://agentmods.dev/badge/skills/maudeunfledged834/startup-founder-skills/investor-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,690 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00053 $0.01690
Opus 5 $0.00026 $0.00845
Sonnet 5 $0.00011 $0.00338
Haiku 4.5 $0.00005 $0.00169

Measured 12d ago against content hash fd64e67dc9ba, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

investor-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to investor-research — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/investor-research/SKILL.md · 105 lines

How it starts

The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Investor Research

When to Use

  • The founder is preparing to fundraise and needs a target investor list.
  • The founder has a list of investors and wants to qualify or prioritize them.
  • The founder asks which VCs or angels are a good fit for their stage, sector, or geography.
  • The founder wants to understand a specific fund's thesis, portfolio, or decision-making process.

Context Required

From startup-context: stage, sector/category, location, current round target (amount), business model, and any existing investor relationships or warm connections.

From the user: geographic preferences (if any), whether they want VC-only, angel-only, or both, any investors already in conversation, and any firms they want to explicitly avoid (e.g., portfolio conflicts they know about).

Workflow

  1. Read startup context — Pull stage, sector, geography, round size, and existing investors from .agents/startup-context.md.
  2. Define investor criteria — Based on context, establish the filtering parameters: stage match, sector focus, typical check size range, geographic relevance, and portfolio conflict exclusions.
  3. Build the raw list — Research investors matching the criteria. For each investor, capture: firm name, partner name, fund stage focus, sector focus, typical check size, recent fund size/vintage, portfolio companies, geographic preference, and a source URL.
  4. Check for conflicts — Flag any firm that has a portfolio company directly competing with the founder's startup. These go on a "conflicts" list, not the target list.
  5. Score and tier — Assign each investor to Tier 1 (strong fit, prioritize), Tier 2 (good fit, pursue), or Tier 3 (acceptable fit, use as backfill) using the scoring framework below.
  6. Identify warm paths — For each Tier 1 investor, suggest how the founder might get a warm intro: mutual connections, portfolio founder intros, accelerator networks, or conference overlap.
  7. Deliver the target list — Output a structured, sortable list with tiers and recommended outreach order.

Read the full file on GitHub · 105 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 105 lines · 53 tokens per session scan A fd64e67dc9ba

Subscribe to this mod's changes

investor-research is a skill published in the GitHub repository Maudeunfledged834/startup-founder-skills (6 stars, last pushed today), licensed MIT. It adds 53 tokens to every session and 1,690 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to investor-research, differing in 0 lines, and is treated as a copy.