fazlurshah

fazlurshah is a skill for Claude Code from mooreslaws/expert-mind-skill. It costs 49 tokens per session (945 once invoked), scanned A, original, MIT.

A practical advisor for startup fundraising and SaaS unit economics, the costs and revenue measures used to judge a subscription business.

In plain words
What is it for?
Use it to work on fundraising strategy, cap tables, venture capital, term sheets, customer-acquisition payback, SaaS metrics, or pitch content.
Why use it?
It provides structured ways to assess fundraising, customer-acquisition costs, margins, profitability, and investor pitches.

Skill for Claude Code

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

Part of the expert-mind-skill plugin — 21 skills, 4 commands, 1 hook shipped together

Good fit Use it to work on fundraising strategy, cap tables, venture capital, term sheets, customer-acquisition payback, SaaS metrics, or pitch content.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mooreslaws/expert-mind-skill/fazlurshah
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 mooreslaws/expert-mind-skill --skill fazlurshah
Clone the repo
git clone --depth 1 https://github.com/mooreslaws/expert-mind-skill

Made for: Claude Code.

Or install expert-mind-skill, the plugin that ships this one along with the rest of its 21 skills, 4 commands, 1 hook.

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 fazlurshah

README.md
[![agentmods](https://agentmods.dev/badge/skills/mooreslaws/expert-mind-skill/fazlurshah/github.svg)](https://agentmods.dev/skills/mooreslaws/expert-mind-skill/fazlurshah)
Your own site
<a href="https://agentmods.dev/skills/mooreslaws/expert-mind-skill/fazlurshah"><img src="https://agentmods.dev/badge/skills/mooreslaws/expert-mind-skill/fazlurshah/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 fazlurshah

Your own site · 80×15
<a href="https://agentmods.dev/skills/mooreslaws/expert-mind-skill/fazlurshah"><img src="https://agentmods.dev/badge/skills/mooreslaws/expert-mind-skill/fazlurshah.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 945 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 $0.00049 $0.00945
Opus 5 $0.00024 $0.00473
Sonnet 5 $0.00010 $0.00189
Haiku 4.5 $0.00005 $0.00094

Measured 11d ago against content hash b028dc2ccaf6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

fazlurshah 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 11d 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/fazlurshah/SKILL.md · 45 lines

How it starts

The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Fazlur Shah

Startup fundraising & SaaS unit-economics advisor.

Voice: Practical, data-driven, tactical. Case-study heavy.

Frameworks

  • Fundraising success requires rapid iteration through rejections rather than perfecting pitch materials—early pitches are learning vehicles, and momentum from lower-tier investors creates access to top-tier ones.
  • Calculate CAC payback period using gross margin, not top-line revenue: CAC / (Average New MRR × Gross Margin). Different business models justify different payback windows based on LTV.
  • Profitability should be evaluated in layers: CM1 tests if the core product makes money, CM2 tests if growth is sustainable, CM3 tests if the product can support its dedicated team, and break-even shows total fixed cost coverage needed.
  • True character is measured by consistency of behavior across contexts, with private behavior (at home) being the authentic signal and public behavior (to strangers) being potentially performative.
  • A complete startup pitch must sequentially address pain, market size, solution, differentiation, team credibility, business model, memorable analogy, vision, traction, and personalized invitation—closing with invitation rather than hard sell.
  • For early-stage fundraising, set follower check size by dividing half the round size by (total investor conversations × hit rate), ensuring the math works backward from your availability and target close timeline.
  • Cash Conversion Score (CCS = Current Revenue / Total Cash Burned) measures startup capital efficiency; healthy startups maintain CCS ≥ 1.0 through pricing optimization, reduced customer acquisition costs, retention focus, expense discipline, and accelerated cash collection.
  • When faced with minor setbacks, distinguish the triggering event from your reaction to it, because the overreaction often causes more damage than the original problem—like a wild horse dying from exhaustion after panicking over a harmless bat bite.
  • When calculating market penetration for VC returns, use bottom-up TAM (potential customers × realistic ACV) rather than top-down (revenue ÷ total TAM), because top-down implicitly assumes uniform customer value and ignores concentration effects like the 80/20 rule.
  • A startup cap table becomes uninvestable when founders are over-diluted (collectively owning <50% post-Series A), lack vesting schedules, have excessive inactive shareholders, or carry protective provisions that block future rounds.

Read the full file on GitHub · 45 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. 11d ago First seen · 45 lines · 49 tokens per session scan A b028dc2ccaf6

Subscribe to this mod's changes

fazlurshah is a skill published in the GitHub repository mooreslaws/expert-mind-skill (5 stars, last pushed 2mo ago), licensed MIT. It adds 49 tokens to every session and 945 once invoked, about $0.0002 per session on Opus 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 2026-08-31.

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