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 forsvn-labs/meta-skills --skill model-growth-funnelgit clone --depth 1 https://github.com/forsvn-labs/meta-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/forsvn-labs/meta-skills/model-growth-funnel)<a href="https://agentmods.dev/skills/forsvn-labs/meta-skills/model-growth-funnel"><img src="https://agentmods.dev/badge/skills/forsvn-labs/meta-skills/model-growth-funnel/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/forsvn-labs/meta-skills/model-growth-funnel"><img src="https://agentmods.dev/badge/skills/forsvn-labs/meta-skills/model-growth-funnel.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 | $0.00049 | $0.00461 |
| Opus 5 | $0.00024 | $0.00230 |
| Sonnet 5 | $0.00010 | $0.00092 |
| Haiku 4.5 | $0.00005 | $0.00046 |
Grade A, and why
model-growth-funnel 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 12d 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Model a growth funnel
Turn a business target into explicit math, assumptions, constraints, and the next evidence needed. This is a decision model, not a forecast.
Define the outcome and units
Name the target, time window, currency, customer/account definition, and whether the target means bookings, recurring revenue, recognized revenue, activation, or another outcome. Do not mix people, accounts, opportunities, orders, and revenue in one rate.
Work backward from the outcome through the smallest useful funnel. For each transition, show:
- numerator and denominator;
- current observed value and source, when available;
- planning assumption when evidence is absent;
- owner and date for replacing the assumption;
- operational action required at that volume.
Keep arithmetic inspectable. Show formulas and rounded operational totals.
Test feasibility
Run at least downside, base, and upside cases across the assumptions most likely to change the decision. Do not vary everything at once.
Check:
- audience/market capacity;
- acquisition and sales throughput;
- onboarding, delivery, and support capacity;
- average contract or order value;
- gross margin and marginal service cost;
- retention/churn where the time horizon requires it;
- acquisition cost, payback, and LTV:CAC only when their inputs exist.
If the model requires impossible throughput, unjustified conversion, or negative economics, say so and identify the binding constraint. Do not reverse-engineer optimistic rates merely to hit the goal.
Deliver
Return:
- decision and target definition;
- assumptions table with source/owner;
- base model and formulas;
- downside/base/upside sensitivity;
- capacity and unit-economics constraints;
- the assumptions with highest decision sensitivity;
- smallest evidence plan for replacing them;
- feasible range, revised target, or explicit no-go recommendation.
Separate model outputs from observed results. Keep spending and external system changes behind explicit approval.
What ships with it
1 file 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.
- 12d ago First seen · 64 lines · 49 tokens per session scan A d77477e415ba
model-growth-funnel is a skill published in the GitHub repository forsvn-labs/meta-skills (14 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 461 once invoked, about $0.0002 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 2026-08-30.
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