CD calendarizador-contenido-formula100k
Arma calendarios de contenido semanales (Lunes-Domingo) en CSV y XLSX con la metodología FÓRMULA 100K. Usar SIEMPRE que el usuario pida 'arma mi calendario', 'calendariza estos guiones', 'ordena estas ideas en un calendario', 'convierte esto en calendario semanal', 'haz mi calendario en Excel', 'organiza mis guiones por día', 'calendariza este lote/enlaces/TikToks/reels/carruseles'. 3 modos de entrada: (1) guiones listos; (2) ideas sueltas que desarrolla llamando a guionizacion-formula100k o carrusel-viral-formula100k; (3) enlaces de video que transcribe con transcripcion-youtube-formula100k y reescribe como referencia. 2 tipos de pieza: REELS y CARRUSELES (columnas propias, altura de fila dinámica). Distribución según propósito: Experimentación 70/30/0, Crecimiento 40/50/10, Nutrición 20/70/10, Venta 20/50/30. NO confundir con calendarizador-historias (stories) ni calendarizador-urgencias.
Arma calendarios de contenido semanales (Lunes-Domingo) en CSV y XLSX con la metodología FÓRMULA 100K.
As a process D 42/100 · Unfinished process — 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: 5. 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 42/100
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70Execution cost. Instruction body is 4903 tokens
- 85Steps. 92 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Running it twice. No mutating operations
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 903: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -5TODO / placeholder text left in the skill
- -222 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 24 headings
- +3Step-by-step instructions: 92 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.