Marin is an open-source research program, software platform, and community for developing foundation models such as large language models. Researchers use it for data preparation, tokenization, pretraining, posttraining, evaluation, and related experiments, including work on audio-text, DNA, and protein models. The catalogue entries are add-ons that support workflows around Marin.
Borrowing it
Nothing to install: this file belongs to marin-community/marin. 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/marin-community/marin/main/.agents/skills/profile-training/SKILL.mdgit clone --depth 1 https://github.com/marin-community/marinWrote 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/marin-community/marin/profile-training)<a href="https://agentmods.dev/skills/marin-community/marin/profile-training"><img src="https://agentmods.dev/badge/skills/marin-community/marin/profile-training/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/marin-community/marin/profile-training"><img src="https://agentmods.dev/badge/skills/marin-community/marin/profile-training.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 93 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00032 | $0.02393 |
| Opus 5 | $0.00016 | $0.01196 |
| Sonnet 5 | $0.00006 | $0.00479 |
| Haiku 4.5 | $0.00003 | $0.00239 |
Grade A, and why
profile-training 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Profile JAX training
Scope
Ingestion sources:
- XPlane protobufs inside Levanter profile directories (source of truth):
plugins/profile/<timestamp>/*.xplane.pb- explicit local
*.xplane.pbfiles via--xplane-file
- xprof aggregate tables exported from the same XPlane protobuf when the
optional
xprofpackage is available: step overview timing, kernel stats, collective breakdowns, xprof bottleneck statements. - Perfetto trace JSON as an explicit/fallback source for older profiles:
plugins/profile/<timestamp>/perfetto_trace.json.gzplugins/profile/<timestamp>/*.trace.json.gz
Prefer XPlane protobuf for new work. Perfetto trace JSON commonly hits the trace
event cap; XPlane contains the uncapped timeline events needed for named-scope
regions, pre-op gaps, gap context, process/thread metadata, and xprof aggregate
tables. Use --trace-file only for a specific Perfetto JSON trace or an older
profile with no XPlane protobuf.
Capture Profiles
Use Levanter profiler flags so profiles land under
<trainer.log_dir>/<run_id>/profiler. Remote Marin runs also upload to
MARIN_PREFIX TTL storage and print an XProf link:
uv run ... \
--trainer.profiler.enabled true \
--trainer.profiler.start_step 5 \
--trainer.profiler.num_steps 10 \
--trainer.profiler.upload.ttl_days 30
For profiles where xprof/HLO protobuf tables matter, enable JAX profile options through the Levanter profiler config:
uv run ... \
--trainer.profiler.enabled true \
--trainer.profiler.start_step 5 \
--trainer.profiler.num_steps 5 \
--trainer.profiler.profile_options.host_tracer_level 1 \
--trainer.profiler.profile_options.python_tracer_level 0 \
--trainer.profiler.profile_options.device_tracer_level 0 \
--trainer.profiler.profile_options.enable_hlo_proto true
HLO metadata increases artifact size, so keep these profile windows short. The
XProf profile: link appears after upload. Set
--trainer.profiler.upload.enabled false for local-only capture. Do not copy
profiles to another GCS region for inspection.
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.
- 9d ago First seen · 265 lines · 32 tokens per session scan A 7a961dfabf6d
profile-training is a skill published in the GitHub repository marin-community/marin (3,512 stars, last pushed today), licensed Apache-2.0. It adds 32 tokens to every session and 2,393 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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