What makes founder-wisdom notable?

1K downloads. Trust evidence available

How should founder-wisdom be evaluated before use?

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agentCLAWHUBUnverified

founder-wisdom

Surfaces hard-won axioms from experienced startup founders and operators across hiring, fundraising, product, sales, finance, governance, strategy, management, and crisis. Use whenever someone is wrestling with a startup, scale-up, or early-stage company decision — hiring or firing, picking a co-founder, whether to raise at all, bootstrapping and staying independent, non-dilutive capital, selling the company, moats and positioning, how AI changes the way a startup team works, sells, and hires, who stays accountable when an agent does the work, or any "I'm a founder and I'm not sure what to do" moment. Trigger without an explicit ask for "advice" — "should I…", "is it normal that…", "we're thinking about…", and "how do experienced founders handle…" are in scope, as is helping someone else with founder-stage decisions (advisor, coach, mentor, investor). Also trigger on "who said X" questions about the startup canon. Skill: founder-wisdom Owner: chris-graffagnino Summary: Surfaces hard-won axioms from experienced startup founders and operators across hiring, fundraising, product, sales, finance, governance, strategy, management, and crisis. Use whenever someone is wrestling with a startup, scale-up, or early-stage company decision — hiring or firing, picking a co-founder, whether to raise at all, bootstrapping and staying indepen

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.0k

Updated

Oct 11, 2026

Version

1.9.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1K downloads reported by the source. Last updated 10/11/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1K downloadsadoption · observed Oct 11, 2026
Latest release: 1.9.0release · observed Aug 12, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17c6gqkr1fr2464fn3r0d5ddd83f6c2:founder-wisdom

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-chris-graffagnino-founder-wisdom/snapshot"

Run-check

$0.02 USD

1 measured facts are behind this paywall: success rate and latency, uptime and estimated cost, when not to use it, how to call it, benchmark scores.

Agents pay $0.02 in USDC. A card payment is $0.50, the smallest a card allows.

Documentation

CLAWHUB

145,198 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: founder-wisdom
description: Surfaces hard-won axioms from experienced startup founders and operators across hiring, fundraising, product, sales, finance, governance, strategy, management, and crisis. Use whenever someone is wrestling with a startup, scale-up, or early-stage company decision — hiring or firing, picking a co-founder, whether to raise at all, bootstrapping and staying independent, non-dilutive capital, selling the company, moats and positioning, how AI changes the way a startup team works, sells, and hires, who stays accountable when an agent does the work, or any "I'm a founder and I'm not sure what to do" moment. Trigger without an explicit ask for "advice" — "should I…", "is it normal that…", "we're thinking about…", and "how do experienced founders handle…" are in scope, as is helping someone else with founder-stage decisions (advisor, coach, mentor, investor). Also trigger on "who said X" questions about the startup canon.
metadata:
version: "1.9.0"
---

# Founder Wisdom

A reference skill for surfacing the axioms experienced startup founders know in their bones — the pattern-matched wisdom that first-timers usually learn by running into walls.

## What this skill is for

Founders and operators face decisions where the right answer isn't obvious from first principles — it's obvious from pattern. "Fire fast" sounds glib until you've watched three companies die because a CEO took six months to remove a bad VP. "Cash is oxygen" sounds like a cliché until you've seen a Series B company hit zero with a $30M ARR pipeline.

This skill captures those patterns as axioms, organized by domain, with the context that makes each one useful. It is opinionated and pattern-matched, not neutral or comprehensive. Treat it as a conversation partner that knows the canonical wisdom — not as an oracle.

## Two modes of operation

The skill operates in **direct mode** by default and **Socratic mode** when the conversational signal calls for it. Most uses will be direct.

### Direct mode (default)

When someone asks a clear question — "what should I know about firing my first executive?" or "how do experienced founders handle a down round?" — surface the relevant axioms directly. Lead with the axiom, then the reasoning, then the qualifier. Example:

> **Hire slow, fire fast.** Almost every founder fires too slowly — by the time you're asking "should I let them go?", the answer is yes and was yes two months ago. The exception: never fire in anger, and never on a Friday.

Pull 3–7 axioms maximum per response. Seven is a hard ceiling, not a target — count the bolded lead-ins before you send, and if there are eight, cut to the ones carrying the answer rather than trimming each one shorter. More than that and you're dumping a list instead of giving advice. If a domain has 20 relevant axioms, pick the 5 that most fit the specific situation.

**Bold marks an axiom and nothing else.** Not a step in a procedure, not a sub-point under an axiom you al

evals/README.md

# Evals

`SKILL.md` is prose that steers a model. Prose drifts. This directory holds a small,
hand-checkable set of scenarios that pin down what the skill is supposed to do:
whether it triggers, which reference files it reads, which mode it picks, and
whether the output obeys the discipline in `SKILL.md`.

The directory has two halves. `check_scenarios.py` validates the data file's shape
and calls no model — stdlib only, no key, runs anywhere Python does.
`run_scenarios.py` executes the scenarios against a model and needs the `anthropic`
SDK plus an `ANTHROPIC_API_KEY`. `scenarios.yaml` is the source of truth for both,
and it is still a file you can read as documentation and run by hand.

## Files

- `scenarios.yaml` — the eval set. 38 scenarios plus five global invariants.
- `check_scenarios.py` — stdlib-only validator and pretty-printer. It checks the
  data file's shape, that every referenced path exists, and that `SKILL.md`'s
  frontmatter description is still inside its 950-character budget (the runtime
  ceiling is 1024; the gap is deliberate headroom, and the way to get it back is
  to move enumeration into the routing list, not to raise the budget). It does
  **not** call a model.
  It bundles a minimal YAML reader rather than taking a PyYAML dependency; its output
  on `scenarios.yaml` has been diffed against PyYAML and is identical.
- `run_scenarios.py` — the executable half. It imports `load` and `validate` from
  `check_scenarios.py` rather than reparsing the YAML, then drives each `prompt`
  through a harness that hands the model one skill and two tools, so triggering and
  file routing are read off the tool calls instead of inferred from the prose.
  Deterministic checks always run; `--judge` adds a second model call that grades the
  mode and the prose assertions. Needs the `anthropic` SDK and `ANTHROPIC_API_KEY`
  unless `--dry-run`.
- `results/` — committed output from judged runs. See "Committed results" below.

## Schema

Top level:

| Key | Meaning |
|---|---|
| `version` | Schema version. Currently `1`. |
| `global_invariants` | Plain-English checks that apply to every scenario where `should_trigger` is true. |
| `scenarios` | The list below. |

Each scenario:

| Key | Type | Meaning |
|---|---|---|
| `id` | string | Stable kebab-case identifier. Referenced in PR discussion. |
| `prompt` | string | Exactly what the user says. Verbatim — do not paraphrase when running. |
| `should_trigger` | bool | Whether the founder-wisdom skill should activate at all. |
| `expected_mode` | `direct` \| `socratic` \| `none` | `none` iff `should_trigger` is false. |
| `expected_files.must_include` | list | Reference files that must appear among those read. Never more than three. |
| `expected_files.must_not_include` | list | Reference files whose presence is a failure. |
| `assertions` | list | Plain-English checks on the response. |
| `rationale` | string | One line naming the `SKILL.md` rule the scenario protects. |

`expected_files` is deli

README.md

# Founder Wisdom

A [Claude Skill](https://www.anthropic.com/news/skills) that surfaces hard-won axioms from experienced startup founders and operators — the pattern-matched wisdom that first-timers usually learn by running into walls.

## What it does

Founders face decisions where the right answer isn't obvious from first principles — it's obvious from pattern. This skill gives Claude access to a curated corpus of those patterns, organized by domain, with the context that makes each one useful.

When you ask Claude a founder-stage question — hiring, fundraising, product, sales, finance, co-founders, governance, crisis, or any of the surrounding territory — Claude consults this corpus and responds with the relevant axioms rather than working from generic priors.

The skill operates in two modes:

- **Direct mode** (default): Surfaces relevant axioms with reasoning and qualifiers. Useful when you want a quick read on a decision.
- **Socratic mode**: Asks the question the axiom answers, rather than handing you the answer. Useful for working through ambivalence, for coaching/mentoring conversations, and for processing live decisions.

## Domains covered

- Hiring, firing, comp, equity grants, the keeper test, and the AI-era talent shift toward systems thinkers
- Fundraising, terms, runway, investor relations
- Product, product-market fit, pivots, and where startup ideas come from — Paul Graham on noticing rather than inventing, and on schlep blindness
- Sales, pricing, GTM, the founder-as-seller, what a visionary customer is actually buying, and selling in the AI era — building the motion like a product, automating in order of workflow legibility
- Finance, cash, burn, CFO timing, ramen profitability, AI-pilot revenue and ERR, the operating metrics that matter (cohorts, NRR, Rule of 40, CAC payback, gross margin), and how to build the two models the axioms keep pointing at — the 13-week cash flow forecast and the Default Alive calculation
- Capital and valuation — cost of capital, dilution math, venture debt, ARR multiples, the liquidation waterfall, 409A, down rounds, secondaries, plus the procedures: computing your own waterfall off the charter, and running a down round
- Bootstrapping and the non-venture path — whether to raise at all, self-financeable growth, overtrading, annual prepay, revenue-based financing, SBIR grants, profit share and phantom equity, the plateau
- Exits and M&A — running a sale process, bankers, LOIs and exclusivity, diligence, earn-outs, escrow, retention packages, acqui-hires, headline price vs. actual payout
- Co-founder dynamics, splits, vesting, titles, and Noam Wasserman's rich-versus-king trade
- Boards and governance — board design, running the board like a team you lead, and why success is what gets founder-CEOs replaced
- Founder time, energy, sustainability, and where founder attention goes — the maker's schedule, the one top idea in your mind
- Customers and market dynamics, and Geoffrey Moore's chasm — why ea

_meta.json

{
  "ownerId": "kn7bwxjecdr5xfbq5tf88jsya583f0sv",
  "slug": "founder-wisdom",
  "version": "1.9.0",
  "publishedAt": 1786553282130
}

references/bootstrapping.md

# Bootstrapping & the Non-Venture Path

Most of this corpus is calibrated to companies that raise institutional money, because that is where most of the observed pattern comes from. This file is the counterpart to that material rather than a rebuttal of it: the venture axioms hold for venture companies, and what breaks here is the subset that quietly assumes a round standing behind them. What changes is the binding constraint — growth is rate-limited by margin instead of by a fundraising calendar, nobody outside the company grades the number, and the characteristic death is a decade-long plateau rather than a zero-cash date. `capital-valuation.md` prices the instruments; this file covers what the absence of a round does to everything else.

This file is not financial, tax, or legal advice. The math is here so founders can ask their CFO and counsel better questions, not so they can skip them.

> **Benchmarks are calibration, not truth.** Figures marked *[bench 2026-07]* — the revenue ceiling that separates a good company from a viable venture asset, annual-prepay discounts, revenue-based-financing caps and remittance rates, SBIR award sizes, profit-share pool sizing, small-business exit multiples — reflect market conditions as of July 2026 and move with the rate environment and the funding market. The mechanics are durable; the numbers are not. Check current data before quoting a threshold, and name the vintage.

## Core axioms

**You can raise later; you cannot un-raise.** The first institutional dollar deletes "good enough" as an available outcome: a $250M fund holding 10% at exit needs a $2.5B result to return itself once, so the $80M acquisition that clears your mortgage rounds to zero on the board's math (`capital-valuation.md`). Name the fund's size against the honest ceiling of the business before the first meeting; if it can't cover, you are volunteering to be a write-off. The limit is matching the fund to the outcome: a $30M pre-seed fund returns itself on a $300M exit. Later has arrived when you can name a payback period you cannot fund from margin; it hasn't when you can't say what the money buys.

**The growth plan in the deck is one you'd never run with your own money.** Three shapes take venture money badly. Services-inflected businesses get funded on a software multiple and spend three years starving the delivery motion that was working. Slow compounders with long sales cycles or regulated buyers are excellent on a ten-year clock and unfundable on a fund's. The real-but-small market is the most honest: a business that tops out at $40M *[bench 2026-07]* is a very good company and a bad venture asset, and the deck that clears diligence is the one with an inflated TAM. The limit is services-as-wedge, where the mismatch is deliberate and time-boxed.

**Margin-funded growth is capped by the gap between paying for a customer and being paid.** The venture path pre-funds that gap with a round; here it is funded by last quarter's profit, whi

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