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 skills/axect/pytorch_template/pytorch-migratenpx skills add Axect/pytorch_template --skill pytorch-migrategit clone --depth 1 https://github.com/Axect/pytorch_templateWhat 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 | $0.00078 | $0.02286 |
| Opus 5 | $0.00039 | $0.01143 |
| Sonnet 5 | $0.00016 | $0.00457 |
| Haiku 4.5 | $0.00008 | $0.00229 |
Grade C, and why
pytorch-migrate scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf "$TEMPLATE_DIR" How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pytorch-migrate
Detect the current version of a pytorch_template-based project and apply all necessary migrations to bring it up to date.
Usage
/pytorch-migrate [project_path]
If project_path is omitted, uses the current working directory.
Step 0: Clone the Template
Clone the latest template into a temporary directory. All code references during migration come from this clone — never from embedded snippets.
TEMPLATE_DIR=$(mktemp -d)
git clone --depth 1 https://github.com/Axect/pytorch_template.git "$TEMPLATE_DIR"
Use $TEMPLATE_DIR as the source of truth for all file contents throughout the migration. After migration is complete, clean up:
rm -rf "$TEMPLATE_DIR"
Step 1: Detect Current Version
Read the project's files and determine which version it's based on by checking for feature markers.
Run these checks in order — the first missing feature determines the starting migration point:
| Check | How to detect | Version if MISSING |
|---|---|---|
config.py has RunConfig dataclass |
class RunConfig exists |
Pre-template (not migratable) |
callbacks.py exists |
File exists | v0 (monolithic, pre-callback refactor) |
pruner.py has PFLPruner |
class PFLPruner in pruner.py |
v1 (pre-PFL pruner, before 2024-12) |
callbacks.py has OptimizerModeCallback |
Class exists | v1 (pre-M1, missing optimizer mode toggle) |
callbacks.py has LossPredictionCallback |
Class exists | v1 (pre-M1, missing loss prediction) |
callbacks.py has NaNDetectionCallback |
Class exists | v2 (pre-NaN detection, before 2024-09) |
callbacks.py has CheckpointCallback |
Class exists | v3 (pre-checkpoint, before 2025-04) |
config.py has data field in RunConfig |
data: str in RunConfig |
v4 (pre-data-decoupling) |
callbacks.py has GradientMonitorCallback |
Class exists | v5 (pre-diagnostics) |
cli.py has preflight command |
def preflight exists |
v5 (pre-preflight) |
cli.py has hpo_report command |
def hpo_report exists |
v5 (pre-hpo-report) |
callbacks.py has CSVLoggingCallback |
Class exists | v6 (pre-dual-logging) |
config.py has logging or wandb field in RunConfig |
logging: str or wandb: bool in RunConfig |
v6 (pre-dual-logging) |
provenance.py exists |
File exists | v6 (pre-provenance) |
cli.py has update_skills command |
def update_skills exists |
v7 (pre-TUI-tabs) |
tools/monitor/src/hpo/mod.rs exists |
File exists | v7 (pre-HPO-monitor) |
config.py has wandb: bool field in RunConfig |
wandb: bool in RunConfig |
v8 (pre-wandb-toggle) |
checkpoint.py has find_resume_checkpoint |
def find_resume_checkpoint exists |
v9 (pre-resume) |
util.py has start_epoch parameter on Trainer.train |
start_epoch literal in util.py |
v9 (pre-resume) |
| All checks pass | — | Current (up to date) |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 186 lines · 78 tokens per session scan C c69ad437eed4
pytorch-migrate is a skill published in the GitHub repository Axect/pytorch_template (10 stars, last pushed 3mo ago), licensed MIT. It adds 78 tokens to every session and 2,286 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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