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 agentmods add skills/williancesar/saasoned/growth-network-effectsnpx skills add williancesar/saasoned --skill growth-network-effectsgit 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-network-effects)<a href="https://agentmods.dev/skills/williancesar/saasoned/growth-network-effects"><img src="https://agentmods.dev/badge/skills/williancesar/saasoned/growth-network-effects.svg" alt="Measured on agentmods" 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 | $0.00093 | $0.01195 |
| Opus 5 | $0.00046 | $0.00598 |
| Sonnet 5 | $0.00019 | $0.00239 |
| Haiku 4.5 | $0.00009 | $0.00120 |
Grade A, and why
growth-network-effects 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 5d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Growth: Network Effects
Owns cold-start and network-driven growth. Hub: growth-foundations
(worldview, shared vocabulary, router). Does not redefine hub terms.
Stance. You do not scale a network — you scale atomic networks. With no working atomic network, Claude refuses to discuss scaling and says why (hub Guardrail 2). Seed the hard side first, do unscalable things, prove one small network, then repeat.
Frameworks index
| Framework | Source | Depth |
|---|---|---|
| Atomic network · the hard side · seeding | Chen, The Cold Start Problem | references/atomic-network.md |
| The five-stage arc | The Cold Start Problem | references/the-arc.md |
| Network-effect taxonomy · come-for-the-tool · anti-network effects | The Cold Start Problem | references/network-effect-taxonomy.md |
Cold-start diagnosis (run before any growth advice)
- Is this actually a network product? Does value depend on other users being present? No → this is a channel/retention problem; route out.
- Name the atomic network. The smallest set of users that is stable and useful on its own (e.g., one city, one company, one friend group, one classroom). If you can't name it, that's the first deliverable.
- Identify the hard side. The minority who do the disproportionate work the network needs (sellers, hosts, organizers, creators). Hardest to get and keep — plan acquisition/retention for them specifically.
- Locate the stage on the arc (Cold Start → Tipping Point → Escape Velocity → Ceiling → Moat). Advice differs per stage.
- Only then discuss tactics. If no atomic network exists yet, the only valid topic is seeding one — refuse scale talk and cite the source.
Decision cues
- "It works for me but new users see an empty room" → classic empty-network cold start; the atomic network isn't reached for a new user. Seed density in one network, don't broaden.
- "Chicken-and-egg / two-sided won't start" → constrain to the smallest atomic network and over-serve the hard side first.
- "Let's launch in 20 cities" with no proven city → refuse; prove and saturate ONE atomic network first (Guardrail 2). Cite The Cold Start Problem.
- "Growth stalled at scale" → Ceiling stage (saturation/anti-network effects), not a seeding problem; see the-arc.md + anti-network effects.
- "More users but worse experience" → anti-network effect (congestion/ spam/low quality); adding users makes it worse — fix quality before growth.
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.
- 5d ago First seen · 92 lines · 93 tokens per session scan A 7210586fd127
growth-network-effects is a skill published in the GitHub repository williancesar/saasoned (10 stars, last pushed 3mo ago), licensed MIT. It adds 93 tokens to every session and 1,195 once invoked, about $0.0005 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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