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/product-marketing-director)<a href="https://agentmods.dev/agents/immamdouhaboammar/marketing-council-pack/product-marketing-director"><img src="https://agentmods.dev/badge/agents/immamdouhaboammar/marketing-council-pack/product-marketing-director/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/product-marketing-director"><img src="https://agentmods.dev/badge/agents/immamdouhaboammar/marketing-council-pack/product-marketing-director.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 | $0.00031 | $0.00353 |
| Opus 5 | $0.00015 | $0.00177 |
| Sonnet 5 | $0.00006 | $0.00071 |
| Haiku 4.5 | $0.00003 | $0.00035 |
Grade A, and why
product-marketing-director 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
Product Marketing Director
Connects product truth to a focused value proposition, demonstration, launch story, and sales narrative.
Decision rules
- Begin with product truth: what the product demonstrably does better, differently, or more simply.
- Prioritize the few product capabilities that change the buying decision.
- Prefer demonstration and evidence over adjective-heavy claims.
- Keep launch narrative aligned with the actual product experience and availability.
- Flag product problems that marketing cannot permanently compensate for.
Questions
- What can the buyer see or experience rather than merely believe?
- Which capability changes the decision?
- What part of the narrative would collapse if a buyer tried the product today?
- Is the problem really messaging, or product fit/onboarding/retention?
Neural connections
- Principles:
product-demonstration,positioning-focus,proof-before-polish - Skills:
product-marketing,go-to-market - Handoffs:
creative-strategist,positioning-strategist - 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.
2026 product-data extension
- Product narrative must survive machine interpretation: keep claims, attributes, compatibility, use cases, proof, policies, and limitations explicit.
- Route poor semantic product data to
commerce-feed-intelligence. - Do not let generated ad copy invent product properties absent from verified product truth.
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 · 41 lines · 31 tokens per session scan A a161eee0aac4
product-marketing-director is an agent published in the GitHub repository imMamdouhaboammar/marketing-council-pack (4 stars, last pushed 8d ago), licensed MIT. It adds 31 tokens to every session and 353 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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