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/file-issue/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/file-issue)<a href="https://agentmods.dev/skills/marin-community/marin/file-issue"><img src="https://agentmods.dev/badge/skills/marin-community/marin/file-issue.svg" alt="Measured on agentmods" 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 | $0.00031 | $0.01072 |
| Opus 5 | $0.00015 | $0.00536 |
| Sonnet 5 | $0.00006 | $0.00214 |
| Haiku 4.5 | $0.00003 | $0.00107 |
Grade A, and why
file-issue 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 6d 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 — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
File a GitHub issue
Before drafting, read AGENTS.md and:
.agents/skills/writing-style/SKILL.md.agents/skills/writing-style/issues.md.agents/skills/writing-style/ai-writing-donts.md
Issue Kinds and Body Structure
Pick the smallest matching structure.
| Kind | When to use | Labels |
|---|---|---|
| bug | A bug or regression was found | bug, agent-generated |
| task | An improvement, refactor, or feature request | agent-generated + priority if known |
| experiment | An experiment needs tracking | experiment, agent-generated |
Bug body
<what is broken and its impact -- concrete symptoms or error messages>
Reproduce:
1. <step>
2. <step>
Expected: <what should happen instead>
<optional: concise evidence or confirmed root cause>
Task body
<what needs to be done and why -- enough context for anyone on the team>
Done when:
<specific, testable completion criteria>
Experiment body
## TL;DR
<One-paragraph current summary. Leave blank only when the work is just being kicked off.>
## Description
<Context someone outside the thread can understand.>
## Hypothesis or Goal
<What are you trying to learn, fix, or achieve?>
## Status
<Current state; update as evidence lands.>
## Links
* Logbook:
* W&B Report:
* Important updates:
## Decision Log
## Conclusion
Workflow
1. Gather and classify
Extract the symptom or desired outcome, impact, location, reproduction, known cause, and severity. Ask when the issue or its kind is ambiguous.
2. Check duplicates
Search for existing issues first:
gh issue list --repo marin-community/marin --state open --search "<keyword>"
If a match exists, tell the user and offer to comment on it instead.
3. Draft
Title: At most 80 characters, optionally prefixed with a scope tag. State a
factual symptom for a bug (e.g. [levanter] Gradient accumulation drops the last microbatch) and an imperative outcome for a task (e.g. [levanter] Handle partial accumulation steps). Do not add bug:, task:, or another type
prefix.
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.
- 6d ago First seen · 158 lines · 31 tokens per session scan A eab5668f9997
file-issue is a skill published in the GitHub repository marin-community/marin (3,444 stars, last pushed today), licensed Apache-2.0. It adds 31 tokens to every session and 1,072 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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