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 krillinai/growth-skills --skill marketing-mix-modelinggit clone --depth 1 https://github.com/krillinai/growth-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/krillinai/growth-skills/marketing-mix-modeling)<a href="https://agentmods.dev/skills/krillinai/growth-skills/marketing-mix-modeling"><img src="https://agentmods.dev/badge/skills/krillinai/growth-skills/marketing-mix-modeling/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/krillinai/growth-skills/marketing-mix-modeling"><img src="https://agentmods.dev/badge/skills/krillinai/growth-skills/marketing-mix-modeling.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 | $0.00083 | $0.02774 |
| Opus 5.5 | $0.00033 | $0.01110 |
| Sonnet 5.5 | $0.00017 | $0.00555 |
| Haiku 4.5 | $0.00008 | $0.00277 |
Grade A, and why
marketing-mix-modeling 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 2mo 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Marketing Mix Modeling
Build a versioned aggregate model of how media and other growth inputs relate to a reconciled customer or business outcome across time and markets. Preserve identification assumptions, baseline, carryover, saturation, experiments, uncertainty, and supported response ranges so an MMM informs decisions without turning fit, platform credit, or modeled contribution into causal certainty.
Read model-and-data-contract.md before accepting the decision, outcome, entity, market, time grain, sources, media, controls, vintages, or feasibility. Read transformations-identification-and-estimation.md before choosing adstock, lag, saturation, priors, constraints, controls, pooling, interactions, or an estimation method. Read validation-calibration-and-decisions.md before validating, calibrating with experiments, reporting contribution, building response curves, comparing models, or creating budget scenarios. Read output-contract.md before delivery. Use playbook-sources.md for the pinned Growth Playbook basis.
Select One Mode
| Mode | Use |
|---|---|
specification |
Define a calculation-ready model and measurement contract when compatible aggregate evidence is unavailable |
feasibility |
Decide whether history, variation, sources, outcomes, dimensions, and calibration can support the intended decision |
build |
Estimate and validate a bounded model from supplied compatible data |
audit |
Inspect an existing model, contribution report, response curve, scenario, or decision for data, identification, validation, and governance failure |
calibrate |
Reconcile an existing MMM with compatible experiment or other causal evidence without forcing agreement |
refresh |
Preserve the prior version and update affected data, transformations, assumptions, model, calibration, or decisions after material change |
What ships with it
5 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.
- 2mo ago First seen · 102 lines · 83 tokens per session scan A 85e6dae3b2e3
marketing-mix-modeling is a skill published in the GitHub repository krillinai/growth-skills (43 stars, last pushed 2mo ago), licensed MIT. It adds 83 tokens to every session and 2,774 once invoked, about $0.0003 per session on Opus 5.5. 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.
marketing-mix-modeling compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| marketing-mix-modelingkrillinai/growth-skills | Skill | 43 | 2mo ago | MIT | A | 83 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |