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 imMamdouhaboammar/marketing-council-pack --skill category-strategygit 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/skills/immamdouhaboammar/marketing-council-pack/category-strategy)<a href="https://agentmods.dev/skills/immamdouhaboammar/marketing-council-pack/category-strategy"><img src="https://agentmods.dev/badge/skills/immamdouhaboammar/marketing-council-pack/category-strategy/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/immamdouhaboammar/marketing-council-pack/category-strategy"><img src="https://agentmods.dev/badge/skills/immamdouhaboammar/marketing-council-pack/category-strategy.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 | $0.00037 | $0.00605 |
| Opus 5 | $0.00018 | $0.00302 |
| Sonnet 5 | $0.00007 | $0.00121 |
| Haiku 4.5 | $0.00004 | $0.00060 |
Grade A, and why
category-strategy 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 7d 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Category Strategy
Job
Decide category frame, maturity response, entry points, and demand creation posture
Own this request only when category frame is the clear decision boundary. If ownership is ambiguous or several functions compete, route to marketing-council. If the user explicitly asks for dependent work across functions, use ../../scripts/dynamic_router.py to build a bounded DAG.
Operating contract
- Read
references/skill-spec.jsonfirst for activation, invariants, workflow freedom, evidence rules, handoffs, and completion conditions. - Use
references/decision-model.mdwhen framing or challenging the decision. - Check
references/failure-modes.mdbefore finalizing a recommendation. - Render the response against
references/output-contract.md. - Use packaged shared references or current external research only when they are load-bearing. Never present inference as evidence.
Evidence discipline
Classify material claims as fact, inference, assumption, or unknown. Prefer supplied primary evidence. Verify current platform, policy, product, pricing, or market claims when freshness affects the recommendation. Do not fabricate research, tool calls, metrics, customer language, or causal proof.
Routing
- Focused request: stay inside this Skill.
- Ambiguous or cross-functional ownership: hand to
marketing-council. - Explicit dependency chain: use
../../scripts/dynamic_router.py. - After Skill ownership is known, theory/agent selection may use
../../scripts/neural_router.py; neural nodes never replace Skill routing.
Execution connections
- Primary specialist:
../../agents/market-architect.md - Skeptical counterweight:
../../agents/marketing-skeptic.md - Domain challenge gate:
../../hooks/category-maturity-check.md - Evidence gate:
../../hooks/evidence-gate.md - Keep these as decision inputs, not automatic authority. The Skill owns the final evidence-bound synthesis.
Neural connections
- Owning Skill:
category-strategy - Decision boundary:
category frame - Neural graph:
../../neural/graph.json - Neural router:
../../scripts/neural_router.py - Theory and specialist selection happens only after Skill ownership; neural nodes never replace Skill routing.
- Use the local
references/skill-spec.jsonevidence policy and invariants to reject neural recommendations that are unsupported by the request evidence.
What ships with it
9 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.
- 7d ago Changed · +18 lines 07a725daf7f9
- 12d ago First seen · 38 lines · 37 tokens per session scan A b3d44bacd529
category-strategy is a skill published in the GitHub repository imMamdouhaboammar/marketing-council-pack (4 stars, last pushed 8d ago), licensed MIT. It adds 37 tokens to every session and 605 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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