MFLUX is a native MLX implementation of generative image models that runs locally on Mac computers. It is for generating images with supported models through command-line tools or a Python API. The catalogue skills and instruction support workflows built around these image-generation models.
Borrowing it
Nothing to install: this file belongs to mflux-community/mflux. 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/mflux-community/mflux/main/.cursor/skills/mflux-pr/SKILL.mdgit clone --depth 1 https://github.com/mflux-community/mfluxWrote 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/mflux-community/mflux/mflux-pr)<a href="https://agentmods.dev/skills/mflux-community/mflux/mflux-pr"><img src="https://agentmods.dev/badge/skills/mflux-community/mflux/mflux-pr/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/mflux-community/mflux/mflux-pr"><img src="https://agentmods.dev/badge/skills/mflux-community/mflux/mflux-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00029 | $0.00854 |
| Opus 5.5 | $0.00012 | $0.00342 |
| Sonnet 5.5 | $0.00006 | $0.00171 |
| Haiku 4.5 | $0.00003 | $0.00085 |
Grade A, and why
mflux-pr 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 20d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mflux pull request workflow
When to Use
- You’re about to open a PR (or want a safe sequence to do it).
Instructions
- If you run tests as part of PR hygiene, prefer fast tests first:
just test-fast
- Keep commits focused and messages consistent with repo history.
- If the PR changes CLI defaults, public APIs, or model behavior, check for README/example drift before opening the PR.
- Always ask for permission before pushing to the remote repository.
- If
ghisn’t available, fall back to the GitHub web UI (or stop and ask).
PR body and release note (required)
The release-note CI check fails the PR if the body has no complete release-note block.
Use the mflux-pr-docs skill to write the PR body. That skill writes the What section and the release-note block, runs the CI check, and gets the approval of the developer.
If the check fails on an open PR, use the mflux-pr-docs skill again. It edits the body of the open PR. The check runs again on an edit. You do not need a new commit.
Pre-merge checklist (model port PRs)
Use after the core port lands and you are polishing for merge. For the full integration surfaces tick list (LoRA key formats, save routing, tokenizer edge cases, etc. learned from past closed PRs), see mflux-model-porting → Integration surfaces checklist.
Correctness
just lintandjust test-fastjust ci-extractafter changingAVAILABLE_MODELSorscripts/ci_extract_models.py- Slow golden tests for the new model:
MFLUX_PRESERVE_TEST_OUTPUT=1 uv run pytest tests/image_generation/test_generate_image_<model>.py -m slow -v - Optional but high-signal: diffusers side-by-side + latent injection (
mflux-debugging,mflux-manual-testing)
Cross-model diff audit
List files changed outside src/mflux/models/<model>/:
| Category | Expected |
|---|---|
pyproject.toml, cli/defaults/defaults.py, ModelConfig, mflux-save routing |
Required wiring |
scripts/ci_extract_models.py OVERLAY / EXTRA_ENTRIES |
Required CI-manifest wiring for every new model key or standalone tool |
README.md table + attribution |
Required |
Training runner.py, example JSON, .gitignore JSON exceptions |
If training supported |
| Shared VAE/callback/training one-liners | Only if required; document blast radius in PR |
Personal .gitignore, unrelated formatting |
Remove |
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.
- 20d ago Changed · -13 lines 0f9070c00376
- 27d ago Changed · +21 lines 2deea8535d25
- 1mo ago Changed · +2 lines 6dd00f5d38d8
- 2mo ago First seen · 63 lines · 29 tokens per session scan A 9c1d215cad52
mflux-pr is a skill published in the GitHub repository mflux-community/mflux (2,547 stars, last pushed yesterday), licensed MIT. It adds 29 tokens to every session and 854 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
github-automation
GitHub workflow automation, PR management, issue tracking, and code review coordination. Integrates with GitHub Actions and repository management. Use when: PR creation, code review, issue management, release automation, workflow setup. Skip when: local-only changes, non-GitHub repositories.
changelog
Auto-generate a changelog from git commits and sprint data. Internal and player-facing versions.
feature-publish
Commit the feature, write the PR body, publish in the selected mode, and drive the PR.
comet-safe-delivery
A Chinese-language procedure for safely delivering specified Comet changes through Git. It covers checking worktrees and unrelated edits, staging exact files, validating hooks, and authorized commits or pushes.
git-workflow
Guided git workflows: prepare PRs, clean up branches, resolve merge conflicts, handle monorepo tags, squash-and-merge patterns. Use when asked to prepare a PR, clean branches, resolve conflicts, or tag a release.
git-push
A GitHub publishing workflow that handles first-time uploads, routine updates, and tagged releases. Git is a system for recording code changes, while GitHub hosts repositories and releases online.