Agent skill

Investor Research

by shawnpang in shawnpang/startup-founder-skills

When the user wants to identify, evaluate, or prioritize potential investors for a fundraising round.

MITAuto-check passedBusiness, Finance & HR

Install Investor Research

skills CLI
$ npx skills add shawnpang/startup-founder-skills --skill investor-research -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install shawnpang/startup-founder-skills investor-research --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/shawnpang/startup-founder-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/investor-research .claude/skills/investor-research && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
investor-research
GitHub stars
343
Token cost
~1.9k tokens
SKILL.md length
1,060 words
Files
1
Skills in repo
50
Repo updated
First seen
Licence
MIT

At a glance

When the user wants to identify, evaluate, or prioritize potential investors for a fundraising round.

  • Works in 7 steps: Read startup context — Pull stage,… → Define investor criteria — Based on… → Build the raw list — Research investors… → …
  • Wants to identify
  • SKILL.md covers When to Use, Context Required, Workflow and Output Format, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Investor Research is an agent skill from shawnpang/startup-founder-skills. When the user wants to identify, evaluate, or prioritize potential investors for a fundraising round. Also activates when the user asks "who should I pitch?", "find me investors", "build an investor list", or mentions VC/angel targeting.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Business, Finance & HR, covering Fundraising and pitch decks. The repository describes itself as: AI agent skills for tech startup founders — fundraising, sales, product, recruiting, engineering, legal, ops, and growth. Works with Claude Code, Cursor, Codex, and any Agent… The licence is MIT.

When your agent uses it

  • Wants to identify
  • Prioritize potential investors for a fundraising round
  • Asks who should I pitch?
  • Find me investors

Example prompts

  • “who should I pitch?”
  • “find me investors”
  • “build an investor list”
  • “/investor-research”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  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…
  3. Build the raw list — Research investors matching the criteria. For each investor, capture: firm name, partner name, fund stage focus…
  4. Check for conflicts — Flag any firm that has a portfolio company directly competing with the founder's startup. These go on a "conflicts"…
  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…
  6. Identify warm paths — For each Tier 1 investor, suggest how the founder might get a warm intro: mutual connections, portfolio founder…
  7. Deliver the target list — Output a structured, sortable list with tiers and recommended outreach order.

What it can do on your machine

Read from SKILL.md and the folder at commit 4ad31b4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Investor Research loads about 1.9k tokens when it runs. Until then it costs about 64 tokens; SKILL.md has 1,060 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~64
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from shawnpang/startup-founder-skills at commit 4ad31b4, republished under its MIT licence (© shawnpang). 1,060 words, ~1,938 tokens.

Download SKILL.mdSave it as .claude/skills/investor-research/SKILL.md (or your agent's skills folder).
name
investor-research
description
When the user wants to identify, evaluate, or prioritize potential investors for a fundraising round. Also activates when the user asks "who should I pitch?", "find me investors", "build an investor list", or mentions VC/angel targeting.
related
pitch-deck, fundraising-email
reads
startup-context

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.

Output Format

A markdown table with the following columns, grouped by tier:

## Tier 1 — High Priority

| Firm | Partner | Stage Focus | Sector Fit | Check Size | Recent Fund | Conflict? | Warm Path | Notes |
|------|---------|-------------|------------|------------|-------------|-----------|-----------|-------|

Followed by a "Conflicts" section listing excluded firms and why.

Followed by a "Research Gaps" section listing anything that could not be verified and needs the founder's input.

Frameworks & Best Practices

Investor Qualification Criteria (The 7-Point Filter)
  1. Stage fit — Does the firm invest at the founder's current stage? A Series B fund will not lead a seed round. This is the first filter and it is binary: pass or fail.
  2. Sector focus — Does the firm have a stated thesis or track record in the founder's sector? Look at their last 10 investments, not just their website copy.
  3. Check size match — Does the firm's typical check size align with what the founder needs? A $2B fund rarely writes $500K checks. A $50M fund rarely leads $20M rounds.
  4. Portfolio conflicts — Does the firm already have a company in the same space? This is the most common reason pitches are dead-on-arrival. Check every portfolio company, including quiet ones.
  5. Fund vintage — Is the firm actively deploying from a recent fund? A fund raised 4+ years ago is likely in harvest mode and not writing new checks. Prefer firms that closed a fund within the last 18 months.
  6. Geographic relevance — Some firms only invest locally. Others require board seats that demand proximity. Remote-friendly firms have expanded, but geography still matters for many funds.
  7. Partner-level interest — Is there a specific partner whose background, interests, or public writing aligns with the startup? Pitching the right partner at the right firm matters as much as pitching the right firm.
Tiering Framework
  • Tier 1: Matches on 6-7 of the criteria above. The firm has invested in adjacent companies, the partner has spoken publicly about the space, and a warm intro path exists. Pursue first.
  • Tier 2: Matches on 4-5 criteria. Good fit on stage and sector but may lack a warm path or have a slightly mismatched check size. Pursue in the second wave.
  • Tier 3: Matches on 3 criteria. Acceptable as backfill if the round needs more participants. Do not spend significant time here until Tier 1 and 2 are exhausted.
Show full SKILL.md (402 more words)Show less
Sourcing Investor Information
  • Crunchbase / PitchBook: Fund size, recent investments, portfolio companies.
  • Firm website: Stated thesis, partner bios, blog posts that reveal focus areas.
  • Twitter/X and Substack: Many partners publish their current interests publicly. Recent posts are a better signal than old "About" pages.
  • SEC filings: Fund size from Form D filings when not publicly disclosed.
  • Portfolio founder back-channels: The single best diligence on an investor is talking to founders they have backed — both successes and companies that struggled.
Common Mistakes to Avoid
  • Spraying 200 cold emails — Fundraising is a funnel. 30 well-targeted, well-introduced conversations beat 200 cold ones.
  • Ignoring portfolio conflicts — Founders waste weeks pitching firms that will never invest because of a conflict.
  • Pitching the wrong partner — At multi-partner firms, the wrong partner will say "interesting, let me introduce you to my colleague" at best, or just pass.
  • Targeting only brand-name firms — Tier 2 and emerging funds are often faster to decide, more founder-friendly, and more willing to lead at earlier stages.
  • Not tracking your pipeline — Use a simple spreadsheet or CRM: investor name, status (researching / intro requested / meeting scheduled / pitched / passed / term sheet), and next action.
Angel Investor Considerations
  • Angels decide faster (days, not weeks) but write smaller checks ($25K-$250K typically).
  • Look for angels with operational experience in your sector — they add value beyond capital.
  • Angel syndicates (AngelList, etc.) can aggregate small checks into a meaningful allocation.
  • Be cautious about taking angel money from potential acquirers or competitors without understanding the signaling implications.
  • pitch-deck — tailor the deck narrative based on what specific investors care about
  • fundraising-email — write targeted outreach once the investor list is built

Examples

Example prompt: "We're raising a $2.5M seed round for a developer tools company based in SF. Help me build an investor list."

Good output snippet (one Tier 1 entry):

| Boldstart Ventures | Ed Sim | Pre-seed/Seed | Developer tools, infrastructure | $1-3M | $160M Fund IV (2023) | None | Ed is active on Twitter re: dev tools; check if any portfolio founders overlap with your network | Led seed in [similar company]; blog post on "Why developer experience is the next platform shift" |

Example prompt: "I have a list of 15 VCs I want to pitch. Can you help me prioritize?"

Good output approach: Run each firm through the 7-point filter against the founder's startup context. Re-tier the list. Flag any portfolio conflicts the founder may have missed. Identify the 5 to pitch first and suggest the outreach sequence.

© shawnpang, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/investor-research of shawnpang/startup-founder-skills.

Open the folder on GitHubat commit 4ad31b4

Compare with similar skills

Investor Research next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Investor Research compared with similar skills
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Yc Applypedronauck/skills634—~1.3kAutomated safety check: PassNone
Storyline Buildersruthir28/enterprise-ai-skills1481 repos~1.9kAutomated safety check: PassMIT
Startup Pitchferdinandobons/startup-skill1.2k—~6.4kAutomated safety check: PassMIT
Dd SourcingAbilityai/trinity636—~664Automated safety check: PassApache-2.0

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Questions about Investor Research

What does Investor Research do?

When the user wants to identify, evaluate, or prioritize potential investors for a fundraising round. Investor Research is an agent skill from shawnpang/startup-founder-skills. When the user wants to identify, evaluate, or prioritize potential investors for a fundraising round.

When should I use Investor Research?

Investor Research fits situations like: wants to identify; prioritize potential investors for a fundraising round; asks who should I pitch?; find me investors.

How do I install Investor Research in Claude Code?

Run `npx skills add shawnpang/startup-founder-skills --skill investor-research -a claude-code`. Or copy the skill folder (skills/investor-research in shawnpang/startup-founder-skills) into .claude/skills/investor-research in your project. Claude Code loads it when a task matches its description.

How do I install Investor Research in Codex?

Run `npx skills add shawnpang/startup-founder-skills --skill investor-research -a codex`. Or copy the skill folder (skills/investor-research in shawnpang/startup-founder-skills) into .agents/skills/investor-research in your project. Codex loads it when a task matches its description.

Can I use Investor Research in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add shawnpang/startup-founder-skills --skill investor-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/investor-research, .gemini/skills/investor-research, .github/skills/investor-research and .opencode/skills/investor-research in your project.

What does Investor Research need to run?

SKILL.md names no scripts, command-line tools or credentials: Investor Research is instructions for the agent only.

Does Investor Research access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Investor Research safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Investor Research use?

Investor Research is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Investor Research use?

About 1.9k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Investor Research?

Skills that share tags, products or a category with Investor Research: Virtuals Protocol Acp (Virtual-Protocol/openclaw-acp, 168 stars), Yc Apply (pedronauck/skills, 634 stars), Storyline Builder (sruthir28/enterprise-ai-skills, 148 stars) and Startup Pitch (ferdinandobons/startup-skill, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Investor Research?

shawnpang (a GitHub user) maintains it in shawnpang/startup-founder-skills, which has 343 GitHub stars. The repository holds 50 skills in this directory. The repository was last updated on March 16, 2026.

Source: shawnpang/startup-founder-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.