SKILLEMALL.ai

BC neodomain-ai

Generate images and videos via Neodomain AI API. Supports text-to-image, image-to-video, text-to-video, universal multi-modal video, motion control video, and batch storyboard video generation. Use when user wants to create AI-generated images or videos using the Neodomain platform.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 13 files body ≈ 3 199 tokens Open the sourcegithub.com analyzed 2 d ago

Generate images and videos via Neodomain AI API.

As a process C 50/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

IntegrationMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
94
Quality 40%
82
Run on models
none yet
Process rating
C
50/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
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.

How to improve

    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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • medium Dangerous commands cmd-shell-rc INSTALL.md:46
      Writes to a shell startup file
      echo 'export NEODOMAIN_ACCESS_TOKEN="your_token_here"' >> ~/.zshrc
    • low Exfiltration net-credential-use SKILL.md:39
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host; quoted — discussed, not commanded)
      1. 先用图片 API 测试 token 是否有效:`curl -H "accessToken: $TOKEN" https://story.neodomain.cn/agent/ai-image-generation/models`
      vendor-hostquoted

    Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 50/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 40Consistency. Frontmatter name (neodomain-ai) differs from the folder (neo-ai)
    • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 100Steps. 38 steps
    • 100Execution cost. Instruction body is 3199 tokens
    • 100Running it twice. No mutating operations

    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)
    • -244 emoji in the instructions: noise for the model
    • -34 of 10 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 283: enough signal without eating the budget
    • +4Structure: 28 headings
    • +3Step-by-step instructions: 38 items
    • +3Output format is stated explicitly
    • +4Has examples (14 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.