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.
npx skills add williancesar/saasoned --skill growth-customer-discoverygit clone --depth 1 https://github.com/williancesar/saasonedWrote 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.
[](https://agentmods.dev/skills/williancesar/saasoned/growth-customer-discovery)<a href="https://agentmods.dev/skills/williancesar/saasoned/growth-customer-discovery"><img src="https://agentmods.dev/badge/skills/williancesar/saasoned/growth-customer-discovery/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.
<a href="https://agentmods.dev/skills/williancesar/saasoned/growth-customer-discovery"><img src="https://agentmods.dev/badge/skills/williancesar/saasoned/growth-customer-discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00086 | $0.01263 |
| Opus 5 | $0.00043 | $0.00632 |
| Sonnet 5 | $0.00017 | $0.00253 |
| Haiku 4.5 | $0.00009 | $0.00126 |
Grade A, and why
growth-customer-discovery 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Growth: Customer Discovery
Owns truthful learning and audience-building. Hub: growth-foundations
(worldview, shared vocabulary, router). Does not redefine hub terms.
Stance. Talk about their life, not your idea. Opinions, compliments, and hypotheticals are bad data and must be excluded — not softened. Find your audience before/while building; "build it and they will come" is a predicted failure (hub Guardrail), not a strategy.
Frameworks index
| Framework | Source | Depth |
|---|---|---|
| Question hygiene · good vs. bad data · commitment & advancement · deflecting compliments | Fitzpatrick, The Mom Test | references/the-mom-test.md |
| Audience-first · Audience–Product Fit · Discovery → Exploration → Transformation · build in public | Kahl, The Embedded Entrepreneur | references/embedded-entrepreneur.md |
| Question-critique-and-rewrite procedure | this skill | references/question-rewrite.md |
Question hygiene (the core filter)
Good data is specifics about the past and actual behavior. Bad data is generics, opinions, and hypotheticals about the future. Apply on every question:
| Bad (exclude/rewrite) | Good (seek) |
|---|---|
| "Would you use…?" / "Do you think…?" | "Walk me through the last time you…" |
| "Do you like this idea?" | "What have you tried to solve it? What did it cost you?" |
| "Would you pay for X?" | "What do you pay for today to deal with this?" |
| Any compliment received | A commitment of time/reputation/money |
Default move: convert every hypothetical/opinion question into a past-behavior question before the conversation.
Commitment & advancement (did you actually learn anything?)
A conversation only counts as validation if the person spends a currency and advances:
- Currencies: time (a real next meeting/work), reputation (an intro, a public endorsement), money (pre-order, deposit, paid pilot).
- Advancement: they move to a concrete next step. Compliments and "keep me posted" are zero-commitment → no signal.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 110 lines · 86 tokens per session scan A f39668e97491
growth-customer-discovery is a skill published in the GitHub repository williancesar/saasoned (10 stars, last pushed 3mo ago), licensed MIT. It adds 86 tokens to every session and 1,263 once invoked, about $0.0004 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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