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/hoangsonww/ai-rag-assistant-chatbot/agentic-python-specialistgit clone --depth 1 https://github.com/hoangsonww/AI-RAG-Assistant-ChatbotWrote 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/hoangsonww/ai-rag-assistant-chatbot/agentic-python-specialist)<a href="https://agentmods.dev/agents/hoangsonww/ai-rag-assistant-chatbot/agentic-python-specialist"><img src="https://agentmods.dev/badge/agents/hoangsonww/ai-rag-assistant-chatbot/agentic-python-specialist.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 | $0.00033 | $0.00155 |
| Opus 5 | $0.00016 | $0.00077 |
| Sonnet 5 | $0.00007 | $0.00031 |
| Haiku 4.5 | $0.00003 | $0.00015 |
Grade A, and why
agentic-python-specialist 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 4d 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
Agentic Python Specialist
Own work primarily in agentic_ai/.
Expectations
- Preserve config-driven and async-oriented design.
- Treat MCP tool and prompt names as external contracts.
- Prefer compile-time validation unless the runtime environment is ready.
- Return a concise summary of changes, validation run, and any unverified runtime assumptions.
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.
- 4d ago First seen · 27 lines · 33 tokens per session scan A 36adaf6ca942
agentic-python-specialist is an agent published in the GitHub repository hoangsonww/AI-RAG-Assistant-Chatbot (47 stars, last pushed 18d ago), licensed MIT. It adds 33 tokens to every session and 155 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.
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