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 G1Joshi/Agent-Skills --skill kerasgit clone --depth 1 https://github.com/G1Joshi/Agent-SkillsWrote 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/g1joshi/agent-skills/keras)<a href="https://agentmods.dev/skills/g1joshi/agent-skills/keras"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/keras/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/g1joshi/agent-skills/keras"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/keras.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 | $0.00015 | $0.00318 |
| Opus 5 | $0.00008 | $0.00159 |
| Sonnet 5 | $0.00003 | $0.00064 |
| Haiku 4.5 | $0.00002 | $0.00032 |
Grade A, and why
keras 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.
What it actually says
Keras
Keras 3 is a game changer: it is now multi-backend. You can write Keras code and run it on top of JAX, PyTorch, or TensorFlow.
When to Use
- Portability: Write once, run on any framework.
- Simplicity:
model.fit()is still the cleanest API in the industry. - XLA: Keras 3 enables XLA compilation on all backends by default.
Core Concepts
Backend Agnostic
The Model is just a blueprint. You choose the engine at runtime.
os.environ["KERAS_BACKEND"] = "jax"
Functional API
Defining models as a graph of layers: x = Dense()(inputs).
Keras Core (keras.ops)
A numpy-like API that works across all frameworks (differentiable numpy).
Best Practices (2025)
Do:
- Use Keras 3: Migrate from
tf.keras. - Use JAX backend: For fastest training on TPUs/GPUs.
- Use PyTorch backend: If you need to integrate into a larger PyTorch codebase.
Don't:
- Don't mix
tf.*ops: Usekeras.ops.*to remain framework-agnostic.
References
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 · 46 lines · 15 tokens per session scan A 1f86821e769a
keras is a skill published in the GitHub repository G1Joshi/Agent-Skills (12 stars, last pushed 7mo ago), licensed MIT. It adds 15 tokens to every session and 318 once invoked, about $0.0001 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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