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 deciqAI/knowledge-skills --skill lean-startupgit clone --depth 1 https://github.com/deciqAI/knowledge-skillsWrote 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/deciqai/knowledge-skills/lean-startup)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/lean-startup"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/lean-startup/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/deciqai/knowledge-skills/lean-startup"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/lean-startup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00128 | $0.02367 |
| Opus 5 | $0.00064 | $0.01184 |
| Sonnet 5 | $0.00026 | $0.00473 |
| Haiku 4.5 | $0.00013 | $0.00237 |
Grade A, and why
lean-startup 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lean Startup
Overview
A startup is a temporary organization searching for a repeatable, scalable business model under extreme uncertainty (Steve Blank). Most early-stage failures are from building something no one wanted because the demand assumption was never tested.
Eric Ries (2011): name the riskiest assumption, build the smallest test (MVP), measure real behavior, decide to pivot or persevere — the Build–Measure–Learn loop, run as fast as possible.
Compose: first-principles to find what the model truly depends on; probabilistic-thinking to calibrate experiments; inversion before each Build phase; business-model-canvas to surface the riskiest assumption blocks.
When to Use
Apply when: high uncertainty + limited capital; a team is about to build before testing demand; a pivot-or-persevere decision is on the table; you're building an AI feature on a foundation-model API and worried "the next model release will commoditize us" / "are we just a GPT wrapper?"; no clear answer to "what is the load-bearing assumption and how would we know if it's wrong?"
When NOT to use: known business model in known conditions (execution, not search); decision is not business-model-level; cannot ethically run a test with real customers; using "lean" as a schedule excuse to ship buggy software.
Coaching Novices (Adaptive Front Door)
- Engine mode: user has a concrete hypothesis → run The Process directly.
- Coach mode: no concrete hypothesis or signals unfamiliarity → guide step by step.
In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.
- One-line what-it-is. Most startups fail by building before knowing if anyone wants it; lean startup names the riskiest assumption, tests it with the smallest MVP, measures real behavior, and decides pivot or persevere — fast.
- Check fit. Match against When to Use / When NOT to use; if low uncertainty + known model, redirect.
- Elicit their real hypothesis. Force them to name one load-bearing assumption — specific segment, specific value, specific willingness-to-pay.
[WAIT — do not advance until user responds]
- Walk the loop step by step. Name assumption → design MVP → define metric → set threshold. Pause at each.
[WAIT — do not advance until user responds]
- Close by naming the next-week experiment. One assumption, one MVP, one threshold, one date — not a strategy doc.
[WAIT — do not advance until user responds]
What ships with it
4 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 · 124 lines · 128 tokens per session scan A 4559afde4d67
lean-startup is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 128 tokens to every session and 2,367 once invoked, about $0.0006 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 2026-09-03.
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