AC reelyze
Reelyze is an AI analyst for short-form video. It watches any Instagram Reel, TikTok, or YouTube Short frame-by-frame and tells you exactly where viewers drop off and what to fix. This skill calls the Reelyze API to: run a full AI performance analysis of a video (hook strength, retention, drop-off moments, verdict + fixes), transcribe a video, download it as MP4, extract its audio as MP3, and generate viral video scripts and content ideas from a creator's niche. Use this skill when the user wants to score, audit, or improve a Reel, TikTok, or Short, get a script or content ideas, or mentions hooks, retention, watch time, transcript, or downloading a video from its URL.
Reelyze is an AI analyst for short-form video.
As a process C 56/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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: 2. 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 56/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 9 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 38 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2440 tokens
- 100Progress reporting. Reports progress
- 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 677: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 38 items
- +4Has examples (4 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.