SKILLEMALL.ai

CF html-reel

Turn a tweet, a video, a YouTube video or a landing page into a 9:16 reel (Instagram Reels, TikTok, Shorts) that says what the source says and looks like it, with every cut on a word. Read the source (its words, its media, its measured fonts and colours), pick a structure (a promo, a showcase, "found this", an explainer, before and after), write the script in the creator's voice from the source's own facts, make the voice with timestamps (their cloned ElevenLabs voice), then build the picture from HTML scenes drawn from one clock (window.__frame(t)) in the source's look, opening on its cover (the hook's best moment as the first frame), its demo video framed and cut to words, and assemble it in Fil's video editor over MCP. The creator is in it from the first draft as a placeholder in the camera layouts (a backlit studio silhouette) (full frame, a bubble, half the frame), swapped for their phone takes when they record, and everything retimed to their own words by word anchors, t = W(τ); a reel can also be faceless. Use when someone wants a reel, a short or a vertical video from a post, a thread, a launch, a landing page, a demo video or a YouTube video, "a reel like this one", or a talking-head promo cut to their own delivery.

The skillemall take

Promises to turn a tweet, video, or landing page into a vertical reel: cut by word, clone the source's voice, match its design. Sounds like automating a video editor's job.

Checks show it's rougher. Code quality 49/100, process score 31/100—numbers that speak for themselves. Files exist (28), but links are broken, scripts didn't run on models. The description is long and vague: unclear if it actually cuts by word or just slices video, how voice cloning works (does it need user data?), whether landing pages work at all. No critical errors found, but no proof of function either.

Don't install. This is a sketch, not a tool.

MengTo/Skills Agent Skills author: MengTo 28 files · 18 scripts body ≈ 6 560 tokens Open the sourcegithub.com↗ analyzed 4 d ago

Turn a tweet, a video, a YouTube video or a landing page into a 9:16 reel (Instagram Reels, TikTok, Shorts) that says what the source says and looks like it…

As a process F 31/100 · No process to follow — References files that are not bundled: scripts/reel-clock.css, scripts/cursors/

ProcedureYouTubeMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
C
80/100
safety, quality, tests
Safety 60%
100
Quality 40%
49
Run on models
none yet
Process rating
F
31/100
No process to follow
References files that are not bundled: scripts/reel-clock.css, scripts/cursors/
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. 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: 28. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1244 chars, limit 1024
  • warning body-long SKILL.md body ≈ 6560 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: scripts/reel-clock.css
  • warning missing-ref reference to a missing file: scripts/cursors/

Process rating: all ten parameters 31/100

Will not run. References files that are not bundled: scripts/reel-clock.css, scripts/cursors/
  • 0Tools and files. 2 referenced file(s) missing: scripts/reel-clock.css, scripts/cursors/
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 8 mutating operations with no state check
  • 70Execution cost. Instruction body is 6560 tokens
  • 100Steps. 82 steps
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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 1244: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 82 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)
  • +3All 18 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 49.