SKILLEMALL.ai

AF flow-image-gen

Generate the storyboard images for a short-form video job. Walks the image_prompts[] array from a job's input.json, calls Google's Gemini image model to render each prompt as a PNG, and saves files into the job's images/ folder using the filenames specified by the timeline. Up to 4 images in parallel. Use whenever the orchestrator hands off image generation.

ClawHub Agent Skills author: Pushpendra Singh Chauhan v1.0.0 MIT-0 3 files · 1 script body ≈ 1 623 tokens Open the sourceclawhub.ai analyzed 21 h ago

Generate the storyboard images for a short-form video job.

As a process F 68/100 · Will not run — References files that are not bundled: examples/demo-job/

GeneratorMedia and videoAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
F
68/100
Will not run
References files that are not bundled: examples/demo-job/
Tools and files w 18
0
Progress reporting w 2
0
Result and completion w 14
60
the three weakest of ten parameters · all ten

How to improve

  1. 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 · 0

✓ No critical or high findings

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: examples/demo-job/

Process rating: all ten parameters 68/100

Will not run. References files that are not bundled: examples/demo-job/
  • 0Tools and files. 1 referenced file(s) missing: examples/demo-job/
  • 0Progress reporting. Says nothing while it works
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 25 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1623 tokens
  • 100Running it twice. Mutating operations check current state
  • low The response is described with custom markup (5 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 360: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 25 items
  • +3Output format is stated explicitly
  • +4Has examples (7 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

External checks

ClawHub: clean
This skill does what it says: it sends storyboard prompts to Google Gemini to create image files in a job folder.
LLM: benign (high) · VirusTotal: · 30 Jun 2026