AD fliz-ai-video-generator
Complete integration guide for the Fliz REST API - an AI-powered video generation platform that transforms text content into professional videos with voiceovers, AI-generated images, and subtitles. Use this skill when: - Creating integrations with Fliz API (WordPress, Zapier, Make, n8n, custom apps) - Building video generation workflows via API - Implementing webhook handlers for video completion notifications - Developing automation tools that create, manage, or translate videos - Troubleshooting Fliz API errors or authentication issues - Understanding video processing steps and status polling Key capabilities: video creation from text/Brief, video status monitoring, translation, duplication, voice/music listing, webhook notifications.
As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 14. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 48/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 4 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 100Steps. 11 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1377 tokens
- low 11 top-level sections: this looks like several domains in one skill
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
- +2Single-language instructions
- +3Description length 748: enough signal without eating the budget
- +4Structure: 22 headings
- +3Step-by-step instructions: 11 items
- +4Has examples (12 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 4 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.