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/voxtechnologies/anty-framework/network-effectsnpx skills add VoxTechnologies/anty-framework --skill network-effectsgit clone --depth 1 https://github.com/VoxTechnologies/anty-frameworkWhat 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 | $0.00075 | $0.01345 |
| Opus 5 | $0.00037 | $0.00673 |
| Sonnet 5 | $0.00015 | $0.00269 |
| Haiku 4.5 | $0.00007 | $0.00135 |
Grade A, and why
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 2d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- network-effects — 100% identical, 0 lines differ
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.
Network Effects Strategy
When to Apply
- Product's value increases with more users (network-effect products)
- Marketplace, social, or community products
- When evaluating viral growth potential
- Cold start problems (chicken-and-egg)
- Growth ceiling diagnosis
Core Framework
Atomic Network Definition
The smallest group where the product becomes self-sustaining. Define during onboarding:
"Does your product's value increase as more people use it?"
-> YES:
"Let's define your Atomic Network — the smallest self-sustaining group.
Reference thresholds:
Slack: 3 people + 2,000 messages = 93% long-term retention
Zoom: 2 people (smallest possible)
Airbnb: 300 listings + 100 reviewed per city
Uber: 15-20 concurrent drivers, ETA < 3 min per city
Tinder: 20,000 users in a single market
What is the minimum unit for YOUR product?
How many users in one [team/city/community] make it work?"
Finding the threshold: Plot network size (X) vs engagement metric (Y). Look for the inflection point ("kink") where engagement spikes. Everything before the kink is anti-network-effect territory.
Anti-Peanut-Buttering
"Do NOT spread across segments until atomic network is achieved in the first one. Density > breadth."
Concentrating resources in one segment to achieve critical mass beats thinly spreading across many.
"Zero" Tracking
A "zero" = the product's core value cannot be fulfilled because the network is too sparse:
- No drivers available
- No listings for a search
- AI gives generic recommendation
Track zero rates per segment. Users who get "zeroed" churn AND don't return — the damage persists.
Escape Velocity — 3-Force Decomposition
Once atomic network is established, track three independent growth forces:
| Force | Key Metric | Benchmark |
|---|---|---|
| Engagement | DAU/MAU ratio, D30 retention | DAU/MAU > 50%, D30 > 15-20% |
| Acquisition | Viral factor | 0.5 = 2x amp, 0.7 = 3.3x, 0.95 = 20x, >1.0 = explosive |
| Economic | CAC trend + LTV trend | Both improving simultaneously |
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.
- 2d ago First seen · 124 lines · 75 tokens per session scan A fa11d5ae89d5
network-effects is a skill published in the GitHub repository VoxTechnologies/anty-framework (6 stars, last pushed 4mo ago), licensed MIT. It adds 75 tokens to every session and 1,345 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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