SKILLEMALL.ai

CB auditor-formula100k

Audita comunidades Skool y estrategias de contenido completas con la metodología FÓRMULA 100K. 2 modos: skool (12 dimensiones de comunidad) y contenido (10 dimensiones de estrategia). Activar SIEMPRE que se pida 'audita esta comunidad Skool', 'revisa la comunidad de [cliente]', 'diagnóstico de Skool', 'auditoría de mi comunidad', 'qué le falta a esta comunidad', 'audita la estrategia de contenido', 'diagnóstico de contenido', 'revisa qué le falta a mi contenido', 'auditoría de redes sociales', 'reposicionamiento de contenido', 'por qué no convierto con mi contenido', 'auditoría de estrategia'. NO activar para análisis de un solo perfil (analizador-perfiles-formula100k), un solo guion (corrector-guiones-formula100k) ni un solo gancho (evaluador-ganchos-formula100k). Aplica el Framework Maestro de 5 fases (Briefing, Mapeo, Brechas, Recomendaciones, Plan 30/60/90). Entrega documento Markdown + scorecard CSV + resumen ejecutivo.

ClawHub Claude Code author: Fórmula 100K v1.0.1 MIT-0 4 files body ≈ 3 823 tokens Open the sourceclawhub.ai↗ analyzed 11 d ago

Audita comunidades Skool y estrategias de contenido completas con la metodología FÓRMULA 100K.

As a process B 67/100 · Nearly there — weak spots: when it triggers, failures and branches, progress reporting

AnalyzerTelegramData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
69
Run on models
none yet
Process rating
B
67/100
Nearly there
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 67/100

  • 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
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 71 steps, 1 vague phrases
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3823 tokens
  • 100Running it twice. No mutating operations
  • low 16 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 938: 120–800 characters recommended
  • -5TODO / placeholder text left in the skill
  • -218 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 32 headings
  • +3Step-by-step instructions: 71 items
  • +3Output format is stated explicitly
  • +4Has examples (11 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
The skill performs a coherent audit workflow, but it can route client data through external services and persist business audit details without a clear opt-in or retention control.
LLM: suspicious (medium) · VirusTotal: · 17 Sept 2026