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BC ofox-video-core

Requires OFOX_API_KEY — create one at https://app.ofox.ai. Shared execution layer for the Ofox video generation API (api.ofox.ai) — creates a video job, polls it to completion, downloads the finished mp4 from a persistent CDN URL, and reports the real cost. This is a library skill, not a standalone user-facing one — it is invoked by scenario skills such as seedance-short-drama, seedance-ad-creative, and seedance-product-video, which build model/prompt/resolution choices for a specific use case and then call into this skill's script rather than re-implementing the API calls. Load this skill directly only when a user explicitly names the Ofox video API, asks to call it with specific low-level parameters, or asks to debug/resume a stuck or failed Ofox video job by job id — for a plain scenario request ("make me a short drama scene", "generate a cinematic ad clip"), use the relevant scenario skill instead, which itself depends on this one.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: OFOX AI v1.21.2 MIT-0 23 files · 13 scripts body ≈ 10 231 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Requires OFOXAPIKEY — create one at https://app.ofox.ai. Shared execution layer for the Ofox video generation API (api.ofox.ai) — creates a video job, polls…

As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorMedia and videotype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
B
81/100
safety, quality, tests
Safety 60%
82
Quality 40%
80
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Concealment
If you install

The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.

For the author

Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 1

  • high Concealment en-hide-from-user references/prompt-structure.md:950
    Instruction to hide actions from the user
    not merely crop the picture — it can silently delete part of what a

Files scanned: 23. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 10231 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 52/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 31 mutating operations with no state check
  • 40Execution cost. Instruction body is 10231 tokens: crowds the task out of the window
  • 60Tools and files. Uses tools (bash, read, web) that frontmatter does not declare
  • 100Steps. 23 steps
  • 100Failures and branches. 5 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 17 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (6 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 949: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (17 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

External checks

ClawHub: suspicious
The skill mostly matches its Ofox video-generation purpose, but its documented dotenv loading and endpoint/request override paths could expose the API key or change billable requests.
LLM: suspicious (high) · 9 Sept 2026