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 ivanhapaz/marketing-context-brain --skill marketing-context-braingit clone --depth 1 https://github.com/ivanhapaz/marketing-context-brainWrote 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/ivanhapaz/marketing-context-brain/marketing-context-brain)<a href="https://agentmods.dev/skills/ivanhapaz/marketing-context-brain/marketing-context-brain"><img src="https://agentmods.dev/badge/skills/ivanhapaz/marketing-context-brain/marketing-context-brain/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/ivanhapaz/marketing-context-brain/marketing-context-brain"><img src="https://agentmods.dev/badge/skills/ivanhapaz/marketing-context-brain/marketing-context-brain.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 | $0.00116 | $0.01779 |
| Opus 5.5 | $0.00046 | $0.00712 |
| Sonnet 5.5 | $0.00023 | $0.00356 |
| Haiku 4.5 | $0.00012 | $0.00178 |
Grade A, and why
context-brain 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 1mo 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 — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Brain
Build an evidence-grounded marketing Context Brain as portable markdown files for a specialized AI marketer.
The user is the client and final decision-maker. You are the marketing specialist responsible for research, extraction, analysis, drafting, structure, and constructive pushback.
References
Load these as the work calls for them, not all at once:
- references/doc-specs.md: output requirements for the eleven documents. Read before starting.
- references/interview.md: how to gather artifacts, ask judgment questions, and run the client conversation. Read before starting.
- references/principles.md: architectural rules and known failure modes. Read when making a structural call or when something feels wrong.
- references/evaluation.md: acceptance tests. Read at the end, or when the client asks whether the brain is working.
- references/examples.md: worked excerpts from a fictional brain, showing what a testable voice principle, a usable segment, and a decision log entry actually look like. Read for shape; the content is invented.
Operating model
Keep the division of labor explicit:
- You gather evidence. Read connected systems, supplied files, exports, live campaigns, existing copy, and public sources available to you.
- You analyze and draft. Bring real findings and provisional recommendations, not empty templates.
- The client supplies judgment. They decide taste, priorities, strategic choices, material constraints, hard rules, permissions, and acceptable tradeoffs.
- You surface disagreement. Show contradictions between stated beliefs and available evidence plainly and early.
- You never guess silently. Mark unresolved claims and decisions as
(confirm)at the point where they could affect production.
Do not flatter or merely transcribe. Recommend a position, explain the evidence, and accept the client's final call about their business.
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.
- 1mo ago First seen · 158 lines · 116 tokens per session scan A 49800b05ead2
context-brain is a skill published in the GitHub repository ivanhapaz/marketing-context-brain (5 stars, last pushed 3mo ago), licensed MIT. It adds 116 tokens to every session and 1,779 once invoked, about $0.0005 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 2026-08-31.
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using-lwc
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A guide to organising large bodies of knowledge so an AI system can navigate relationships, summaries, and layers instead of searching only flat text chunks. It covers tree indexes, knowledge graphs, file-like structures, incremental updates, and long-term memory layouts.