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BC magic-hour

Generate AI video and images with the Magic Hour API (Sora 2, Veo 3.1, Kling 3.0, WAN 2.2, GPT-image, Nano Banana Pro). Text-to-video, image-to-video, image generation; free tier available.

ClawHub Agent Skills author: RhythmP28 v1.0.0 MIT-0 12 files body ≈ 1 210 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Generate AI video and images with the Magic Hour API (Sora 2, Veo 3.1, Kling 3.0, WAN 2.2, GPT-image, Nano Banana Pro). Text-to-video, image-to-video, image…

As a process C 55/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationMedia 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
88/100
safety, quality, tests
Safety 60%
98
Quality 40%
73
Run on models
none yet
Process rating
C
55/100
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

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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
  • low Exfiltration net-credential-use references/api.md:34
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    until curl -s https://api.magichour.ai/v1/video-projects/$ID -H "Authorization: Bearer $MAGIC_HOUR_API_KEY" | jq -e '.status=="complete" or .status=="error"' >/dev/null; do sleep 5; done
    vendor-host
  • low Exfiltration net-credential-use references/api.md:35
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    curl -s https://api.magichour.ai/v1/video-projects/$ID -H "Authorization: Bearer $MAGIC_HOUR_API_KEY" | jq '{status, url: .downloads[0].url, credits_charged}'
    vendor-host

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

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 55/100

  • 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. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 100Steps. 14 steps
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1210 tokens
  • 100Progress reporting. Reports progress

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
  • -31 of 5 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 189: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 14 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: clean
This skill is a coherent Magic Hour integration that uses an API key to generate media and optionally save outputs locally, with the main privacy consideration being that prompts and images go to Magic Hour's hosted service.
LLM: benign (high) · VirusTotal: · 22 Aug 2026