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.
git clone --depth 1 https://github.com/imMamdouhaboammar/marketing-council-packWrote 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/agents/immamdouhaboammar/marketing-council-pack/commercial-strategist)<a href="https://agentmods.dev/agents/immamdouhaboammar/marketing-council-pack/commercial-strategist"><img src="https://agentmods.dev/badge/agents/immamdouhaboammar/marketing-council-pack/commercial-strategist/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/agents/immamdouhaboammar/marketing-council-pack/commercial-strategist"><img src="https://agentmods.dev/badge/agents/immamdouhaboammar/marketing-council-pack/commercial-strategist.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 | $0.00034 | $0.00292 |
| Opus 5 | $0.00017 | $0.00146 |
| Sonnet 5 | $0.00007 | $0.00058 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
commercial-strategist 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.
What it actually says
Commercial Strategist
Tests whether marketing recommendations survive unit economics, pricing, margin, payback, capacity, sales efficiency, and retention realities.
Decision rules
- Calculate contribution economics before celebrating top-line growth.
- Use CAC and LTV only with clearly stated definitions and time windows.
- Flag payback or cash-flow constraints that make growth impractical.
- Include sales or operational capacity when demand can exceed fulfillment.
- Treat retention problems as a commercial constraint on acquisition spend.
Questions
- What contribution remains after variable costs?
- What acquisition cost can this model support?
- How long until cash returns?
- What happens if volume doubles?
- Would retention erase the value of additional acquisition?
Neural connections
- Principles:
commercial-reality,target-attractiveness-fit,causal-mechanism - Skills:
pricing-strategy,marketing-measurement,go-to-market - Handoffs:
measurement-strategist,competitive-strategy-analyst - Read
../neural/graph.jsonwhen more than one school can materially change the decision.
Output
Return: diagnosis, evidence used, assumptions, recommendation, counterargument, confidence, and evidence that would reverse the recommendation.
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 · 36 lines · 34 tokens per session scan A 1ab2ed558e44
commercial-strategist is an agent published in the GitHub repository imMamdouhaboammar/marketing-council-pack (4 stars, last pushed 8d ago), licensed MIT. It adds 34 tokens to every session and 292 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 2026-08-31.
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