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 second-curvegit 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/second-curve)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/second-curve"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/second-curve/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/second-curve"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/second-curve.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 | $0.00110 | $0.01957 |
| Opus 5 | $0.00055 | $0.00979 |
| Sonnet 5 | $0.00022 | $0.00391 |
| Haiku 4.5 | $0.00011 | $0.00196 |
Grade A, and why
second-curve 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The Second Curve
Overview
Every business follows an S-curve: slow start, steep growth, peak, then decline. Companies that endure start a second S-curve before the first peaks. Named by Charles Handy in The Empty Raincoat (1994): the optimal start is during late-growth or early-maturity — when the first curve still funds investment but the team can still see the need. The canonical case is Intel's 1985 pivot from memory to microprocessors; the second curve (microprocessors, started 1971) was real before the first was abandoned.
Composes with s-curve-technology-adoption, feedback-loops, first-principles, founder-mindset.
When to Use
- Business growing steadily 2-5 years and metrics still look good — this is when the discipline applies most
- Growth recently decelerated but not yet negative — early maturity signal
- A competitor launched a meaningfully different product in adjacent space
- AI-native startups are attacking your core; you're weighing AI capex / AI-native reinvestment against your legacy (seat/license) cash cow
- Leadership debating "double down vs explore" for capital allocation
- Someone says: "second curve," "S-curve transition," "diversification timing," "the Innovator's Dilemma"
Not when: < 2 years post-PMF; pre-PMF; any second-curve spend would kill the first curve.
Coaching Novices (Adaptive Front Door)
- Engine mode: user has a concrete case → run The Process directly.
- Coach mode: user is unfamiliar → 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: every business is on an S-curve; start the second while the first still climbs — earlier feels reckless, later is structurally too late.
- Check fit: pre-PMF or very early → not yet. Confirm post-PMF with a growing first curve.
- Elicit their real situation: what business, where on the curve, what second-curve candidates exist?
[WAIT — do not advance until user responds]
- Run The Process one step at a time: diagnose first-curve position → identify candidates → time the start.
[WAIT — do not advance until user responds]
- Close by naming the specific 90-day move and what identity shift it requires.
[WAIT — do not advance until user responds]
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 · 122 lines · 110 tokens per session scan A 4a8f43de66fb
second-curve is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 11d ago), licensed MIT. It adds 110 tokens to every session and 1,957 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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