reproducible-github-issues

reproducible-github-issues is a skill for Claude Code, Codex from Blaizzy/mlx-vlm. It costs 67 tokens per session (780 once invoked), scanned A, original, MIT.

A workflow for preparing reproducible GitHub issues for MLX-VLM, including problems with model use, setup, inputs, crashes, results, or speed.

In plain words
What is it for?
Use it to collect system and package details and write an issue-ready bug report; it does not open the issue unless asked.
Why use it?
It gathers the exact environment, commands, inputs, expected result, actual result, and error details needed for someone else to reproduce the problem.

Skill for Claude CodeCodex

Part of the mlx-vlm-skills plugin — 8 skills shipped together

Install

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.

agentmods
npx agentmods add skills/blaizzy/mlx-vlm/reproducible-github-issues
Any agent
npx skills add Blaizzy/mlx-vlm --skill reproducible-github-issues
Clone the repo
git clone --depth 1 https://github.com/Blaizzy/mlx-vlm

Made for: Claude Code, Codex.

Or install mlx-vlm-skills, the plugin that ships this one along with the rest of its 8 skills.

Wrote 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.

agentmods badge for reproducible-github-issues

README.md
[![agentmods](https://agentmods.dev/badge/skills/blaizzy/mlx-vlm/reproducible-github-issues.svg)](https://agentmods.dev/skills/blaizzy/mlx-vlm/reproducible-github-issues)
Your own site
<a href="https://agentmods.dev/skills/blaizzy/mlx-vlm/reproducible-github-issues"><img src="https://agentmods.dev/badge/skills/blaizzy/mlx-vlm/reproducible-github-issues.svg" alt="Measured on agentmods" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 780 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00067 $0.00780
Opus 5 $0.00034 $0.00390
Sonnet 5 $0.00013 $0.00156
Haiku 4.5 $0.00007 $0.00078

Measured 3d ago against content hash 14fe74ac754a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

reproducible-github-issues scanned grade A 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 3d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

3. Prefer `curl` over client SDKs for server repros.
skills/skills/reproducible-github-issues/SKILL.md · 116 lines

How it starts

The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Reproducible GitHub Issues

Use this workflow to turn a failure into a concise, actionable MLX-VLM issue. Do not open a GitHub issue unless the user explicitly asks; otherwise produce issue-ready Markdown.

Required Information

Collect or infer:

  • MLX-VLM version or git commit.
  • Install method: PyPI, editable checkout, branch, or wheel.
  • Python version, OS version, machine/chip, and whether MLX Metal or MLX CUDA is in use.
  • Exact model ID or local path.
  • Whether the model is from Hugging Face cache, a local conversion, or a custom checkpoint.
  • Exact uv run CLI command or server startup command.
  • Exact request body for server issues.
  • Input media facts: image dimensions, audio duration/sample rate, video duration/frame count, and whether the input can be shared.
  • Expected behavior, actual behavior, and full error/traceback.

Collect the Environment Automatically

Instead of hand-filling versions, run and paste the output into the Environment section:

uv run python - <<'PY'
import platform, mlx.core as mx
try:
    import mlx_vlm
    v = getattr(mlx_vlm, "__version__", "unknown")
except Exception as e:
    v = f"import failed: {e}"
print("mlx-vlm:", v)
print("mlx:", mx.__version__, "| default device:", mx.default_device())
print("python:", platform.python_version(), "| platform:", platform.platform())
PY

Repro Minimization

  1. Reduce to the smallest command or request that still fails.
  2. Remove private paths, tokens, and unrelated environment variables.
  3. Prefer curl over client SDKs for server repros.
  4. Prefer one image/audio/video file before multi-input repros.
  5. Use small public media or synthetic inputs when possible.
  6. State whether the bug reproduces with a public model or only a private/local checkpoint.

Issue Template

### Summary

<One sentence describing the failure.>

### Environment

- MLX-VLM:
- Python:
- OS:
- Hardware:
- Install method:

### Model

- Model:
- Source: <HF cache | local path | converted checkpoint>
- Trust remote code: <yes/no>

### Reproduction

```bash
uv run mlx_vlm.generate <args>
```

For server issues:

```bash
uv run mlx_vlm.server <args>
```

```bash
<curl request>
```

### Expected Behavior

<What should have happened.>

### Actual Behavior

<What happened instead.>

### Logs / Traceback

```text
<trimmed traceback or relevant logs>
```

### Inputs

<Describe attached or shareable inputs. Include dimensions/duration when relevant.>

Read the full file on GitHub · 116 lines

Changes

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.

  1. 3d ago First seen · 116 lines · 67 tokens per session scan A 14fe74ac754a

Subscribe to this mod's changes

reproducible-github-issues is a skill published in the GitHub repository Blaizzy/mlx-vlm (5,458 stars, last pushed yesterday), licensed MIT. It adds 67 tokens to every session and 780 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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