veomni-develop
VeOmni-specific checklist for feature development and refactoring. Covers impact analysis across modalities, trainer hierarchy, data pipeline, and distributed code. Use before implementing any non-trivial change. For model-specific or ops-specific work, use veomni-new-model or veomni-new-op instead. Trigger: 'add feature', 'implement', 'refactor', 'reorganize', 'new capability'.
Best use case
veomni-develop is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
VeOmni-specific checklist for feature development and refactoring. Covers impact analysis across modalities, trainer hierarchy, data pipeline, and distributed code. Use before implementing any non-trivial change. For model-specific or ops-specific work, use veomni-new-model or veomni-new-op instead. Trigger: 'add feature', 'implement', 'refactor', 'reorganize', 'new capability'.
Teams using veomni-develop should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/veomni-develop/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How veomni-develop Compares
| Feature / Agent | veomni-develop | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
VeOmni-specific checklist for feature development and refactoring. Covers impact analysis across modalities, trainer hierarchy, data pipeline, and distributed code. Use before implementing any non-trivial change. For model-specific or ops-specific work, use veomni-new-model or veomni-new-op instead. Trigger: 'add feature', 'implement', 'refactor', 'reorganize', 'new capability'.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
## Impact Analysis Before implementing, check which areas your change affects: | Area | What to check | Why it matters | |------|--------------|----------------| | `veomni/trainer/` | All trainer subclasses (`TextTrainer`, `VLMTrainer`, `DitTrainer`, RL trainers) | Changing `BaseTrainer` method signatures breaks all subclasses | | `veomni/data/data_collator.py` | All modalities (text, VLM, DiT) | Collators are tightly coupled to model-specific preprocessing | | `veomni/distributed/` | Both FSDP2 and legacy FSDP1 paths | Shared distributed code is used differently by each path | | `veomni/models/auto.py`, `loader.py` | Model registry, import-time side effects | `MODELING_REGISTRY` is populated at import time; moving registrations breaks loading | | `configs/` | YAML config keys | Renaming config keys breaks existing training configs silently | | `veomni/models/transformers/*/` | `__init__.py` version gates | Models have v4/v5 transformers branches; changes must work on both | ## Refactoring Safety Rules When restructuring code (same behavior, better structure): 1. **Baseline first**: run `pytest tests/` before any change, record results. 2. **One change per commit**: ONE structural change → update ALL callers → verify tests match baseline → commit. 3. **Never batch multiple refactoring steps into one commit.** 4. Check baseline again at the end — results must be identical. ## Common Traps - `veomni.models.auto` registration depends on **import-time side effects** — moving registrations into functions or delaying them breaks model loading. - Renaming config keys **silently breaks** existing YAML configs in `configs/` — grep all YAML files first. - `veomni.distributed` modules are used differently by **FSDP1 vs FSDP2** — test both if touching shared code. - Data collators in `veomni/data/data_collator.py` are coupled to `DEFAULT_DATA_COLLATE_INFO` — adding new tensor keys requires updating the collate info table. - `MainCollator` has **strict SP ordering** (pad → slice → FA kwargs → slice position_ids) — reordering breaks SP correctness. - `position_ids == 0` marks segment boundaries for FA varlen — any transform that produces position_ids must preserve this convention. ## Documentation Before committing, check if the change requires documentation updates: - **New/changed API** → update or create docs in `docs/`. - **New/changed config fields** → update config examples in `configs/` and relevant docs. - **Architecture change** → update `.agents/knowledge/architecture.md`. - **New constraint discovered** → add to `.agents/knowledge/constraints.md`. ## When to Use Other Skills - **New model** → `/veomni-new-model` - **New op/kernel** → `/veomni-new-op` - **Bug fix or debugging** → `/veomni-debug` - **Dependency update** → `/veomni-uv-update`
Related Skills
veomni-uv-update
Use this skill when updating dependencies managed by uv: bumping a package version, upgrading the uv tool itself, updating torch/CUDA stack, switching transformers version, or regenerating the lockfile. Trigger: 'update dependency', 'bump version', 'upgrade uv', 'update torch', 'update lockfile', 'uv sync fails'.
veomni-review
Use this skill before committing ANY code change — this is a mandatory gate in the commit flow. Also trigger proactively when: you've made changes across multiple files and want to check consistency, you're unsure if a fix is safe, a change touches shared infrastructure (BaseTrainer, distributed, model loading, data pipeline), or a change is larger than a few lines. The review launches a subagent that checks implementation quality, multi-file consistency, and known constraint violations, then rates the change as safe/needs-attention/risky.
veomni-new-op
Use this skill when adding a new optimized kernel or operator to veomni/ops/. Covers the full lifecycle: understanding VeOmni's ops architecture (monkey-patch + global function pointer pattern), implementing the kernel, registering it, adding tests, and documenting it. Trigger: 'add op', 'new kernel', 'add attention variant', 'new fused op', 'add triton kernel', 'optimize operator'.
veomni-new-model
Use this skill when adding support for a new model to VeOmni. Covers the full lifecycle: analyzing the HuggingFace model, creating model patches, defining parallel plans, writing configs, integrating with the trainer, and testing. Trigger: 'add model', 'support new model', 'integrate <model_name>', 'new model support'.
veomni-debug
Use this skill for ANY bug, error, crash, wrong output, loss divergence, gradient explosion, test failure, CUDA error, distributed training hang, checkpoint load failure, or unexpected behavior. Covers both quick fixes (clear root cause) and complex debugging (unclear cause). Trigger: 'fix bug', 'fix error', 'broken', 'crash', 'doesn't work', 'fails with', 'loss NaN', 'training hangs', 'FSDP error', 'OOM'.
create-pr
Create a pull request for the current branch. Handles uncommitted changes, generates a PR title matching the `[{modules}] {type}: {description}` format enforced by CI, and fills in the PR description template. Trigger: 'create pr', 'open pr', 'submit pr', 'make pr'.
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