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/write-pipeline/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/write-pipeline)<a href="https://agentmods.dev/skills/marin-community/marin/write-pipeline"><img src="https://agentmods.dev/badge/skills/marin-community/marin/write-pipeline/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/write-pipeline"><img src="https://agentmods.dev/badge/skills/marin-community/marin/write-pipeline.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 | $0.00046 | $0.00418 |
| Opus 5.5 | $0.00018 | $0.00167 |
| Sonnet 5.5 | $0.00009 | $0.00084 |
| Haiku 4.5 | $0.00005 | $0.00042 |
Grade A, and why
write-pipeline 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 15d 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
Write a Marin pipeline
Keep the boundary between work and workflow explicit:
lib/**owns concrete implementations intended for reuse: functions, configurations, and produced data types. New library code must not compose a pipeline, construct anArtifactSteporStepSpec, or reference a particular artifact handle, name, version, or output. The execution framework'sArtifactandArtifactStepdefinitions are infrastructure, not a model for new library workflow builders.experiments/**owns artifact graph construction and one-off binding code: choosing inputs, names, versions, dependencies, resources, and which reusable functions to run. Keep a transformation here only when it is specific to that experiment. Move work intended for reuse into a concretelib/**implementation, then bind it inexperiments/**.- Put experiment-specific tests beside their experiment, including tests of its graph and one-off transformations; do not put them in root
tests/**orlib/**. Keep tests of reusable library behavior in the library's normal test location. Follow rootTESTING.mdand the relevant module instructions.
Inspect nearby current pipelines before editing. Read layout and examples for placement decisions and artifact binding when working with ArtifactStep, apply, paths, or caching. Existing library builders that return steps are exceptions, not precedent for adding more pipeline composition to lib/**.
For a change, verify that the experiment builds the intended dependencies and that reusable work can run without importing experiments/**. Dry-run the graph where the entrypoint supports it; run focused behavior tests without submitting a live job unless requested. Update user-facing docs when the workflow or API changes. Use the manage-pr skill if asked to publish the result.
What ships with it
2 files 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.
- 15d ago Changed 54330fe1eca8
- 1mo ago First seen · 17 lines · 46 tokens per session scan A ddc657a58926
write-pipeline is a skill published in the GitHub repository marin-community/marin (4,074 stars, last pushed today), licensed Apache-2.0. It adds 46 tokens to every session and 418 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-25.
write-pipeline compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| write-pipelinemarin-community/marin | Skill | 4.1k | today | Apache-2.0 | A | 46 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |