CC motion-takeover-f100k
Planea TAKEOVERS faceless a pantalla completa para un video de YouTube 16:9 grabado con tu cara, estilo 'Claude Routines': en los momentos clave la pantalla se llena de mockups paso a paso, trazos SVG e imágenes IA, y luego vuelve tu cara. A partir del .srt del video ya cortado arma el plan de 2 carriles (takeovers + overlays ligeros), renderiza cada takeover como PNG 1920×1080 y, si quieres movimiento, lo anima con Higgsfield. Entrega las piezas + una hoja de montaje con el segundo exacto de cada takeover para ponerlas encima en tu editor. En este agente no edita ni compone el video. Activar cuando se diga: 'takeovers para mi video', 'motion graphics fullscreen tipo el video que te mandé', 'mockups paso a paso', 'estilo Claude Routines', 'cortes a gráfica'. NO usar para 9:16 (motion-reels-f100k).
Planea TAKEOVERS faceless a pantalla completa para un video de YouTube 16:9 grabado con tu cara, estilo 'Claude Routines': en los momentos clave la pantalla…
As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bashallowed-tools: Bash Read Write Edit AskUserQuestion Skill
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 52/100
- 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
- 70Execution cost. Instruction body is 4596 tokens
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 42 steps
- 100Consistency. Name and required fields are in place
- 100Running it twice. No mutating operations
- low 17 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)
- +3Description length 808: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -5TODO / placeholder text left in the skill
- -212 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 26 headings
- +3Step-by-step instructions: 42 items
- +4Has examples (13 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.