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 thaolst/ai-growth-agents-for-marketers --skill agents-in-productiongit clone --depth 1 https://github.com/thaolst/ai-growth-agents-for-marketersWrote 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/thaolst/ai-growth-agents-for-marketers/agents-in-production)<a href="https://agentmods.dev/skills/thaolst/ai-growth-agents-for-marketers/agents-in-production"><img src="https://agentmods.dev/badge/skills/thaolst/ai-growth-agents-for-marketers/agents-in-production/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/thaolst/ai-growth-agents-for-marketers/agents-in-production"><img src="https://agentmods.dev/badge/skills/thaolst/ai-growth-agents-for-marketers/agents-in-production.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 | $0.00079 | $0.00373 |
| Opus 5.5 | $0.00032 | $0.00149 |
| Sonnet 5.5 | $0.00016 | $0.00075 |
| Haiku 4.5 | $0.00008 | $0.00037 |
Grade A, and why
agents-in-production 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 2mo 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
Agents in Production — Pre-Deploy Review
Bạn là expert review AI prompt trước khi deploy vào thực tế.
Input cần có
- Mô tả agent: làm gì, nhận input gì, trả về output gì
- System prompt đang dùng
- Ví dụ input thật
- Output agent trả về với input đó
Output format
Điểm yếu của prompt
Chỗ nào có thể cho kết quả không nhất quán hoặc sai?
Edge cases chưa xử lý
Input bất thường nào có thể làm agent fail?
Cải thiện đề xuất
Thay đổi cụ thể trong prompt để output ổn định hơn.
Monitoring
Dấu hiệu nào cho thấy agent đang degraded khi chạy thật?
Verdict
Deploy ngay, cần test thêm, hay cần thiết kế lại?
Nguyên tắc
Tập trung vào lỗi thực tế, không phải lỗi lý thuyết. Nếu use case an toàn để deploy với một số hạn chế, nói rõ hạn chế đó thay vì chặn hoàn toàn.
English
You are an expert reviewing an AI prompt before production deployment.
Focus on real failure modes, not theoretical ones. If the use case is safe to deploy with some limitations, state those limitations clearly rather than blocking deployment entirely.
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.
- 2mo ago First seen · 55 lines · 79 tokens per session scan A d84e76741eee
agents-in-production is a skill published in the GitHub repository thaolst/ai-growth-agents-for-marketers (5 stars, last pushed 3mo ago), licensed MIT. It adds 79 tokens to every session and 373 once invoked, about $0.0003 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.
Other skills, from other repositories
systematic-debugging
4-phase root cause debugging: understand bugs before fixing.
react-patterns
React 18/19 patterns including hooks discipline, server/client component boundaries, Suspense + error boundaries, form actions, data fetching, state management decision trees, and accessibility-first composition. Use when writing or reviewing React components.
golang-testing
Go testing best practices including table-driven tests, test helpers, benchmarking, race detection, coverage analysis, and integration testing patterns. Use when writing or improving Go tests.
verification-loop
A comprehensive verification system for Claude Code sessions. Use when verifying a Claude Code session's work before claiming it is complete.
mem0-test-integration
Verify a Mem0 integration produced by /mem0-integrate. Runs in the same workspace on the same branch (loose coupling) — installs dependencies, runs the repo's native test suite, then exercises a real end-to-end smoke flow against the user's API key. Produces a scorecard. TRIGGER when: user has just run /mem0-integrate…
darwinian-evolver
Evolve prompts/regex/SQL/code with Imbue's evolution loop.