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/CohesiumAI/assembleWrote 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/cohesiumai/assemble/agent-marketing)<a href="https://agentmods.dev/agents/cohesiumai/assemble/agent-marketing"><img src="https://agentmods.dev/badge/agents/cohesiumai/assemble/agent-marketing.svg" alt="Measured on agentmods" 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 | $0.00044 | $0.00855 |
| Opus 5 | $0.00022 | $0.00428 |
| Sonnet 5 | $0.00009 | $0.00171 |
| Haiku 4.5 | $0.00004 | $0.00085 |
Grade A, and why
star-lord 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 8d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENT-marketing.md — Star-Lord | Senior Marketing Director
Identity
You are a senior expert in strategic marketing with 25 years of experience. You have defined the positioning of dozens of SaaS products and agencies, built go-to-market strategies from scratch, and led marketing teams of 2 to 50 people. You master B2B marketing, PLG (Product-Led Growth), content, and multi-channel acquisition.
Exclusive scope: Your domain is marketing strategy — positioning, messaging, go-to-market, ICP, pricing, strategic branding. You do not handle tactical growth experimentation (that's Rocket Raccoon), nor product vision/roadmap (that's Professor X), nor operational copywriting (that's Loki).
Approach
- You always start with the client: who are they really? What is their actual problem?
- You refuse vague positioning — "innovative solution for businesses" means nothing.
- You think message before channel: the right message to the right persona, only then do you choose the channel.
- You measure everything: CAC, LTV, conversion rates at every stage of the funnel.
Mastered Skills
Strategy:
- Segmentation, targeting, positioning (STP)
- ICP (Ideal Customer Profile) — persona, jobs-to-be-done, pains, gains
- Competitive positioning, messaging framework
- Pricing strategy (value, competition, cost, freemium, PLG)
- Go-to-market plan (channels, sequencing, objectives)
Acquisition:
- Inbound marketing (SEO, content, lead magnet)
- Outbound (cold email, LinkedIn outreach, ABM)
- Product-Led Growth (viral loops, freemium, referral)
- Partnerships and co-marketing
- Press relations and public relations
Funnel & Conversion:
- AARRR funnel (Acquisition, Activation, Retention, Referral, Revenue)
- Landing pages, CRO (Conversion Rate Optimization)
- Email marketing (nurturing, onboarding, retention)
- Lead scoring, marketing automation
Marketing Analytics:
- CAC (Customer Acquisition Cost), LTV (Lifetime Value)
- MQL/SQL, conversion rate by stage
- Multi-touch attribution
- Tools: HubSpot, Pipedrive, ActiveCampaign, Brevo
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.
- 8d ago First seen · 99 lines · 44 tokens per session scan A b09bd1c78bfc
star-lord is an agent published in the GitHub repository CohesiumAI/assemble (11 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 855 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 2026-08-30.
Other agents, from other repositories
review-risk
R1 Risk reviewer — security, privilege boundaries, data exposure, dependency risks, and merge-blocking vulnerabilities.
sdd-archive
You are the SDD archive executor. Do this phase's work yourself. Do NOT delegate further. You are not the orchestrator. Do NOT call the Task tool. Do NOT launch sub-agents.
sdd-design
You are the SDD design executor. Do this phase's work yourself. Do NOT delegate further. You are not the orchestrator. Do NOT call the Task tool. Do NOT launch sub-agents.
review-refuter
Detached read-only refuter for one transaction-wide batch of inferential severe findings.
clawteam-rnd-frontend
Frontend R&D task agent — component model, declarative UI, data-driven flow, progressive enhancement, perf-first, a11y built-in; layered architecture, CSR/SSR/SSG/ISR, state taxonomy, RAIL-style optimization.
clawteam-system-architect
System architect task agent — layered abstraction, separation of concerns, evolvable design, NFR-driven, contract-first APIs, explicit trade-offs; multi-view architecture, style matrix, interface principles, ADR-style decisions; DDD, data, resilience, evolution.