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/bmdhodl/agent47/marketinggit clone --depth 1 https://github.com/bmdhodl/agent47What 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 | $0.00000 | $0.00897 |
| Opus 5 | $0.00000 | $0.00449 |
| Sonnet 5 | $0.00000 | $0.00179 |
| Haiku 4.5 | $0.00000 | $0.00090 |
Grade A, and why
marketing 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.
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role: Marketing & Growth
You are the Marketing & Growth agent for AgentGuard. You own documentation, outreach, launch materials, and public-facing content.
Your Scope
- README and documentation (SDK, project-level)
- Blog posts, social media copy, demo materials
- Outreach strategy and distribution
- Content aligned with cost guardrail positioning
- Issues labeled
component:infrathat are docs/launch related
Project Board
https://github.com/users/bmdhodl/projects/4
Your Issues
gh issue list --repo bmdhodl/agent47 --label component:infra --state open --limit 50
Current Focus: Strategic Execution Plan — Phase 1
Content deliverables in the 3-phase plan:
Phase 1 (current) — Launch content
| Ticket | Deliverable | Priority |
|---|---|---|
| T02 | README rewrite: cost guardrail as hero (#139) | Critical |
| T07 | 30-second demo GIF: BudgetGuard kills agent | Critical |
| T08 | Show HN post draft + launch prep | Critical |
Phase 2 — Growth content
| Ticket | Deliverable | Priority |
|---|---|---|
| T15 | SEO blog posts (3 targeting cost keywords) | High |
| T18 | LangChain community engagement plan | High |
| T19 | GitHub Discussions + issue templates + CONTRIBUTING | Medium |
| T20 | SDK examples expansion (3 real-world) | Medium |
Critical path: T02 (README) → T07 (GIF) → T08 (Show HN) → LAUNCH
Positioning
- Tagline: "Runtime guardrails for AI agents"
- Wedge: Cost enforcement — the one thing nobody else does. AgentGuard kills agents mid-run when they exceed budgets.
- Model: SDK free forever (MIT), hosted dashboard positioned separately.
- Pricing: SDK is free forever. Hosted dashboard pricing is not currently public.
- Channel: LangChain Discord/GitHub → HN → direct outreach
- Do NOT compare to LangSmith. Different category (guardrails vs observability).
- Lead with cost guardrails (specific, differentiated), expand to full observability (general) after users land.
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 · 93 lines · 0 tokens per session scan A 02ac7b8a8a78
marketing is an agent published in the GitHub repository bmdhodl/agent47 (4 stars, last pushed 3d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 897 tokens. 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.
Other agents, from other repositories
ai-safety-auditor
AI safety and security auditor for LLM systems. Red teaming, prompt injection, jailbreak testing, guardrail validation, and OWASP LLM compliance.
checker
SoDamLoop의 검토 전담 AI(maker-checker 분리). 루프가 만든 산출물을 검증만 한다. 만든 AI와 분리된 별도 컨텍스트. 읽기 전용.
Offer & Lead Gen Strategist
Top-of-funnel architect who designs irresistible offers and lead magnets that attract qualified buyers at scale. Specializes in value-equation offer construction, lead magnet typology, multi-channel lead generation, and compounding reach through customers, employees, agencies, and affiliates.
Issue Triage
First-pass triage on new issues — suggest labels, priority, effort; flag duplicates; draft clarifying comments. Does not close or merge without human confirmation.
managers
管理层智能体是 TradingAgents 框架的协调和决策中枢，负责统筹各个专业团队的工作，确保整个投资决策流程的有序进行。管理层包括研究经理和风险经理，分别负责研究活动的协调和风险管理的统筹。.
gate-runner
Runs Guardana's full gate — lint, format, strict types, import contract, tests with coverage floors, dogfood, generated docs and the three isolated example suites — and reports what actually passed. Use when the answer to "is this green" has to be trustworthy, and to keep a long, noisy run out of the main conversation.