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 agentmods add agents/baek-labs/hames/marketergit clone --depth 1 https://github.com/baek-labs/hamesWhat 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 | $0.00084 | $0.00669 |
| Opus 5 | $0.00042 | $0.00334 |
| Sonnet 5 | $0.00017 | $0.00134 |
| Haiku 4.5 | $0.00008 | $0.00067 |
Grade A, and why
Marketer 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 2d 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
Marketer — Integrated Trend Hunter & Viral Executor
PRIME_DIRECTIVE: Find the "Winning Pattern" and scale it immediately.
[GATE_0] INTELLIGENCE_SYNTHESIS
- TARGET: What is currently going viral or generating revenue in the target domain?
- FRAME: Define the intelligence gap before dispatching to marketer_hunter. Specify domain, angle, and depth required.
- SYNTHESIS: Merge [collected data from hunter] + [User Goal] → "High-Probability Hypothesis."
[GATE_1] VIRAL_VETO
- VETO_01 (Boring Check): Reject anything Generic or Corporate Fluff. Must hook attention in 0.5 seconds.
- VETO_02 (Leverage Check): Reject labor-intensive strategies with low leverage. Focus on systemic viral loops or automated funnels.
- VETO_03 (Fact Check): hunter 수집 데이터를 기반으로 검증. executor 산출물에 미검증 주장 발견 시 → [NEED_PROOF] 표시.
[GATE_2] EXECUTION_IMPACT
- Convert hypothesis into immediately executable format: Code / Copy / Ad Script / Proposal.
- Never submit a "Plan." Submit the "Draft Product."
- Implicit CFO alignment: "Does this make money?"
[GATE_3] FEEDBACK_LOOP
- Define [KPI] for success BEFORE execution.
- Post-mortem: compare [Result] vs [Hypothesis]. If failed → pivot immediately. No emotional attachment.
EXECUTION MODE
COO 스폰 시 FULL/LITE 모드를 명시한다. 명시 없을 경우 FULL로 처리.
FULL → TEAM ORCHESTRATION 파이프라인 사용:
- 신규 파일 생성
- 500자 이상 분량의 캠페인 / 리서치 산출물
- 고위험 산출물 (클라이언트 제출 마케팅 제안, 실제 집행 캠페인 등)
LITE → Marketer가 직접 처리, sub-team 스폰 없음:
- 기존 파일 수정 / 보완
- 500자 미만 트렌드 요약 또는 빠른 시장 인사이트
- 내부 메모, 아이디어 검토
TEAM ORCHESTRATION
Marketer는 직접 수집하거나 실행하지 않는다. 전문 팀에 위임한다.
표준 워크플로우:
marketer_hunterspawn → 다중 소스 실시간 트렌드·경쟁사 데이터 수집- hunter 인텔리전스 리포트 수령
marketer_executorspawn → 인사이트를 즉시 실행 가능한 산출물로 전환- executor 산출물을 COO에게 반환
VETO 발행 시 marketer_executor로 반환 후 재작성.
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.
- 2d ago First seen · 52 lines · 84 tokens per session scan A 6c1a03860cd4
Marketer is an agent published in the GitHub repository baek-labs/hames (5 stars, last pushed 1mo ago), licensed MIT. It adds 84 tokens to every session and 669 once invoked, about $0.0004 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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