apply-market-size-first-screening

apply-market-size-first-screening is a skill for Claude Code from jeffreytse/grimoire-core. It costs 61 tokens per session (1,417 once invoked), scanned A, original, MIT.

An investment screening method that checks the size and growth potential of a market before examining the team or product in detail. The addressable market is the total group of customers a business could realistically serve.

In plain words
What is it for?
Comparing early-stage investment opportunities and estimating whether a market is large and expanding enough to justify further review.
Why use it?
It avoids spending time on companies whose markets are too small to support a large outcome, even if the product and team are strong.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the grimoire-business plugin — 156 skills shipped together

Good fit Comparing early-stage investment opportunities and estimating whether a market is large and expanding enough to justify further review.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jeffreytse/grimoire-core/apply-market-size-first-screening
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 jeffreytse/grimoire-core --skill apply-market-size-first-screening
Clone the repo
git clone --depth 1 https://github.com/jeffreytse/grimoire-core

Made for: Claude Code.

Or install grimoire-business, the plugin that ships this one along with the rest of its 156 skills.

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 apply-market-size-first-screening

README.md
[![agentmods](https://agentmods.dev/badge/skills/jeffreytse/grimoire-core/apply-market-size-first-screening/github.svg)](https://agentmods.dev/skills/jeffreytse/grimoire-core/apply-market-size-first-screening)
Your own site
<a href="https://agentmods.dev/skills/jeffreytse/grimoire-core/apply-market-size-first-screening"><img src="https://agentmods.dev/badge/skills/jeffreytse/grimoire-core/apply-market-size-first-screening/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 apply-market-size-first-screening

Your own site · 80×15
<a href="https://agentmods.dev/skills/jeffreytse/grimoire-core/apply-market-size-first-screening"><img src="https://agentmods.dev/badge/skills/jeffreytse/grimoire-core/apply-market-size-first-screening.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,417 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 original No closer match found 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 $0.00061 $0.01417
Opus 5.5 $0.00024 $0.00567
Sonnet 5.5 $0.00012 $0.00283
Haiku 4.5 $0.00006 $0.00142

Measured 4d ago against content hash b1ebbb6eba06, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

apply-market-size-first-screening 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 4d 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.

skills/business/entrepreneurship/skills/apply-market-size-first-screening/SKILL.md · 68 lines

How it starts

The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Apply Market-Size-First Screening

Screen for a genuinely large addressable market as the first criterion in evaluating an early-stage investment — before assessing team or product quality — since even excellent execution operating within a small market structurally caps the achievable outcome, while a sufficiently large market can produce an outsized result even from imperfect execution.

Why This Is Best Practice

Adopted by: Don Valentine, founder of Sequoia Capital, is widely documented for a market-first screening philosophy — explicitly prioritizing the size and growth potential of the addressable market over the specific founding team as the primary initial screen — a contrasting emphasis to the more founder-first framing associated with other venture investors, reflecting Sequoia's early investment decisions (including Apple and Atari) made substantially on the basis of large emerging market opportunity. Impact: Valentine's documented reasoning specifically argues that a mediocre team in a genuinely large, growing market can still produce a large outcome simply from market growth carrying the business forward, while even an exceptional team operating in a small or non-growing market faces a structural ceiling on the achievable outcome regardless of execution quality — a distinction that shapes which opportunities are worth pursuing at the earliest, highest-uncertainty stage of evaluation. Why best: At the earliest stage of company evaluation, team quality and product-market fit are both still highly uncertain and difficult to assess with confidence — but the size of the underlying addressable market is comparatively more assessable and more durably determinative of the venture-scale outcome a fund needs from its winners (see apply-ten-bagger-strategy). Screening for market size first filters out opportunities that, even in the best case, cannot produce the outsized outcome venture investing depends on, before investing further evaluation effort in team and product assessment.

Read the full file on GitHub · 68 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. 4d ago Changed b1ebbb6eba06
  2. 1mo ago First seen · 68 lines · 61 tokens per session scan A 71cfe2e647b1

Subscribe to this mod's changes

apply-market-size-first-screening is a skill published in the GitHub repository jeffreytse/grimoire-core (5 stars, last pushed 5d ago), licensed MIT. It adds 61 tokens to every session and 1,417 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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