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 stepanenkoviktor0110-boop/ai-dev-methodology-codex --skill prompt-mastergit clone --depth 1 https://github.com/stepanenkoviktor0110-boop/ai-dev-methodology-codexWrote 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/stepanenkoviktor0110-boop/ai-dev-methodology-codex/prompt-master)<a href="https://agentmods.dev/skills/stepanenkoviktor0110-boop/ai-dev-methodology-codex/prompt-master"><img src="https://agentmods.dev/badge/skills/stepanenkoviktor0110-boop/ai-dev-methodology-codex/prompt-master/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/stepanenkoviktor0110-boop/ai-dev-methodology-codex/prompt-master"><img src="https://agentmods.dev/badge/skills/stepanenkoviktor0110-boop/ai-dev-methodology-codex/prompt-master.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 | $0.00043 | $0.01739 |
| Opus 5 | $0.00022 | $0.00870 |
| Sonnet 5 | $0.00009 | $0.00348 |
| Haiku 4.5 | $0.00004 | $0.00174 |
Grade A, and why
prompt-master 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 10d 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 10d ago First seen · 198 lines · 43 tokens per session scan A 70daa45dc2bf
prompt-master is a skill published in the GitHub repository stepanenkoviktor0110-boop/ai-dev-methodology-codex (1 stars, last pushed 4mo ago), with no licence file. It adds 43 tokens to every session and 1,739 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 2026-08-31.
Other skills, from other repositories
llm-integration
LLM integration patterns for function calling, streaming responses, local inference with Ollama, and fine-tuning customization. Use when implementing tool use, SSE streaming, local model deployment, LoRA/QLoRA fine-tuning, or multi-provider LLM APIs.
prompt-engineering
Universal prompt engineering techniques for any LLM. Use when crafting, optimizing, or reviewing prompts for AI models. Triggers on requests like "improve this prompt", "write a system prompt", "optimize my instructions", "help me prompt engineer", "audit this prompt", "review my prompt", or when building agentic…
bmad-advanced-elicitation
Push the LLM to reconsider, refine, and improve its recent output.
better-prompt
A prompt editor that turns rough instructions for AI systems into clearer, more complete prompts. It follows published OpenAI and Anthropic guidance.
building-agent-systems
AI agent and LLM system engineering reference covering single-agent dev (ReAct, tool calling, plan-execute), multi-agent coordination (swarm, role decomposition, file locking), LLM security (prompt injection, jailbreak defense, output filtering), RAG architecture (chunking, hybrid retrieval, rerank), and prompt…
alibaba-cloud-model-provider-setup
Configure OpenClaw to use Alibaba Cloud Bailian provider (Pay-As-You-Go or Coding Plan) through a strict interactive flow. Supports 5 site options and flagship model series. Use this skill when a user asks to add, switch, or repair Alibaba Cloud/Qwen provider configuration in Op…