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/onlygian/G-ForgeWrote 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/onlygian/g-forge/python-ml-architect)<a href="https://agentmods.dev/agents/onlygian/g-forge/python-ml-architect"><img src="https://agentmods.dev/badge/agents/onlygian/g-forge/python-ml-architect/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/onlygian/g-forge/python-ml-architect"><img src="https://agentmods.dev/badge/agents/onlygian/g-forge/python-ml-architect.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 | $0.00059 | $0.01921 |
| Opus 5.5 | $0.00024 | $0.00768 |
| Sonnet 5.5 | $0.00012 | $0.00384 |
| Haiku 4.5 | $0.00006 | $0.00192 |
Grade A, and why
python-ml-architect 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.
The source is not reproduced here
Licensed GPL-3.0
The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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 Changed · -22 lines 7929f7cf5ea6
- 1mo ago First seen · 251 lines · 59 tokens per session scan A 2d97a3fdf795
python-ml-architect is an agent published in the GitHub repository onlygian/G-Forge (4 stars, last pushed 8d ago), licensed GPL-3.0. It adds 59 tokens to every session and 1,921 once invoked, about $0.0002 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 agents, from other repositories
embed
Embeddings and vector search — model selection, pipeline design, similarity search, production index management.
feat
Feature engineering — transformations, encodings, feature stores, pipeline design.
fit
Model training — algorithm selection, hyperparameter tuning, training infrastructure.
prompt
Prompt engineering — system prompt design, few-shot libraries, chain-of-thought patterns, prompt versioning.
score
Model evaluation — metrics design, statistical significance, model comparison, evaluation frameworks.
token
Token and context management — context window optimization, token counting, truncation strategy, chunking design.