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.
git clone --depth 1 https://github.com/nelson820125/iforgeaiWrote 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/nelson820125/iforgeai/python-engineer)<a href="https://agentmods.dev/agents/nelson820125/iforgeai/python-engineer"><img src="https://agentmods.dev/badge/agents/nelson820125/iforgeai/python-engineer/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/agents/nelson820125/iforgeai/python-engineer"><img src="https://agentmods.dev/badge/agents/nelson820125/iforgeai/python-engineer.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 | $0.00082 | $0.00483 |
| Opus 5.5 | $0.00033 | $0.00193 |
| Sonnet 5.5 | $0.00016 | $0.00097 |
| Haiku 4.5 | $0.00008 | $0.00048 |
Grade A, and why
python-engineer 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 1mo 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
#file:{{INSTALL_SKILLS_PATH}}/python-engineer/SKILL.md
Additional Constraints
Anti-AI-Bloat Rules
- Implementation notes describe technical decisions directly — do not explain "what you are about to do"
- Code comments state why, not what — the code itself shows what
- Do not write filler phrases like "The benefit of this approach is" or "It's worth noting that"
- When encountering ambiguity, ask directly rather than implementing assumptions extensively
Workflow Integration
- Primary inputs:
.ai/temp/requirement.md+.ai/temp/architect.md+.ai/temp/wbs.md - Reference tech stack constraints:
.ai/context/architect_constraint.md - After each phase, write a work log to
.ai/records/python-engineer/{version}/task-notes-phase{seq}.md - After completing, click the "✅ Backend development complete, submit for review" handoff button to return to the digital team
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.
- 1mo ago First seen · 37 lines · 82 tokens per session scan A 96320f580df5
python-engineer is an agent published in the GitHub repository nelson820125/iforgeai (12 stars, last pushed 23d ago), licensed MIT. It adds 82 tokens to every session and 483 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.
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