Borrowing it
Nothing to install: this file belongs to Red-Hat-AI-Innovation-Team/training_hub. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Red-Hat-AI-Innovation-Team/training_hub/main/.claude/skills/memory-estimation/SKILL.mdgit clone --depth 1 https://github.com/Red-Hat-AI-Innovation-Team/training_hubWrote 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/red-hat-ai-innovation-team/training_hub/memory-estimation)<a href="https://agentmods.dev/skills/red-hat-ai-innovation-team/training_hub/memory-estimation"><img src="https://agentmods.dev/badge/skills/red-hat-ai-innovation-team/training_hub/memory-estimation/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/red-hat-ai-innovation-team/training_hub/memory-estimation"><img src="https://agentmods.dev/badge/skills/red-hat-ai-innovation-team/training_hub/memory-estimation.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 | $0.00040 | $0.00413 |
| Opus 5 | $0.00020 | $0.00206 |
| Sonnet 5 | $0.00008 | $0.00083 |
| Haiku 4.5 | $0.00004 | $0.00041 |
Grade A, and why
memory-estimation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
GPU Memory Estimation
Estimate GPU VRAM requirements before committing to a training run.
Step 1: Check Environment
"${CLAUDE_PLUGIN_ROOT}/scripts/th_detect.sh"
If library=missing, tell the user to install training_hub first via the setup-guide skill.
Step 2: Run Estimation
Execute the estimation script with user-provided parameters or config defaults:
"${CLAUDE_PLUGIN_ROOT}/scripts/th_estimate.sh" $ARGUMENTS
Step 3: Present Results
Parse the JSON output and present clearly:
- Memory estimates — Show low/mid/high VRAM estimates in GB
- GPU fit — Report whether the configuration fits on the available GPU(s)
- Recommendations — If memory is tight, suggest:
- Reduce
max_seq_len(e.g., 4096 -> 2048) - Reduce
effective_batch_size - Switch to LoRA or QLoRA for lower memory
- Add more GPUs for data parallelism
- Reduce
Estimation Methods
| Method | For | Estimator |
|---|---|---|
basic |
SFT, GRPO | BasicEstimator |
osft |
OSFT | OSFTEstimator |
lora |
LoRA-SFT, LoRA-GRPO | LoRAEstimator |
qlora |
Quantized LoRA | QLoRAEstimator |
If no method is specified, the script infers it from the configured algorithm.
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 · 49 lines · 40 tokens per session scan A c817ec7dbef1
memory-estimation is a skill published in the GitHub repository Red-Hat-AI-Innovation-Team/training_hub (95 stars, last pushed today), licensed Apache-2.0. It adds 40 tokens to every session and 413 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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