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End-to-end agent for training LTX models. Probes filesystem and GPU, picks the right conditioning mode from the user's intent, prepares the dataset (scenes, captions, references), preprocesses, autotunes, launches, and monitors training. Use when the user wants to train, fine-tune, LoRA, or otherwise produce a custom LTX model.

Lightricks/LTX-2 Claude Code author: Lightricks NOASSERTION 11 files body ≈ 6 341 tokens Open the sourcegithub.com↗ analyzed 7 d ago

End-to-end agent for training LTX models.

As a process C 60/100 · Has gaps — References files that are not bundled: ../../../packages/ltx-trainer/docs/

ProcedureData and analyticsAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
80/100
safety, quality, tests
Safety 60%
89
Quality 40%
67
Run on models
none yet
Process rating
C
60/100
Has gaps
References files that are not bundled: ../../../packages/ltx-trainer/docs/
Tools and files w 18
0
Result and completion w 14
40
When it triggers w 12
70
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 3

✓ No critical or high findings

Medium and low: 3
  • medium Dangerous commands cmd-pipe-to-shell-known-host references/onboarding.md:48
    Pipe-to-shell installer from a well-known host (still executes remote code)
    curl -LsSf https://astral.sh/uv/install.sh | sh
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read Grep Glob Edit Write Agent AskUserQuestion TodoWrite
  • low Concealment en-hide-from-user SKILL.md:123
    Instruction to hide actions from the user (negated — the text forbids it)
    Principle: only ask when reuse-vs-regenerate is a genuine judgment call with cost either way. Never silently delete user-supplied data (hard invariant #1).
    negated

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6341 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: ../../../packages/ltx-trainer/docs/

Process rating: all ten parameters 60/100

Will not run. References files that are not bundled: ../../../packages/ltx-trainer/docs/
  • 0Tools and files. 1 referenced file(s) missing: ../../../packages/ltx-trainer/docs/
  • 40Result and completion. Does not say what the result is
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Failures and branches. 5 branches
  • 70Execution cost. Instruction body is 6341 tokens
  • 85Steps. 83 steps, 2 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 19 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (23 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +3Description length 329: enough signal without eating the budget
  • +4Structure: 27 headings
  • +3Step-by-step instructions: 83 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.