CC clonador-carrusel-formula100k
Skill ESPEJO de FÓRMULA 100K. Toma una CAPTURA DE PANTALLA o un ENLACE de Instagram/TikTok del carrusel de cualquier referente, extrae el "ADN de estilo" (layout, tipografía, paleta, patrón de gancho, arquitectura de slides), lo MEJORA con los principios de viralidad y legibilidad de F100K, y RENDERIZA un carrusel completo en PNG (HTML + Chromium headless) con TU tema y TU marca en ese estilo clonado-mejorado. Activar SIEMPRE que alguien diga: "clona este carrusel", "copia el estilo de este carrusel", "hazme un carrusel como este", "imita a este referente", "tengo una captura de un carrusel que me gustó", "clona este carrusel desde este link", "replica este post de instagram", "replica este estilo", "carrusel espejo", o cualquier captura o enlace de un carrusel con intención de reproducir y mejorar su estilo para contenido propio. NO usar para escribir un guion desde cero sin referencia visual (carrusel-viral-formula100k).
Skill ESPEJO de FÓRMULA 100K.
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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 · 0
✓ No critical or high findings
Files scanned: 7. 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 51/100
- 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
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web, node) that frontmatter does not declare
- 100Steps. 48 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2860 tokens
- 100Running it twice. No mutating operations
- low The response is described with custom markup (4 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 936: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +5Description quotes 10 example trigger phrases
- +4Structure: 14 headings
- +3Step-by-step instructions: 48 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.