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AC seo-affiliate-guide

Crea guías de compra SEO optimizadas para posts de afiliado en español. Úsala siempre que el usuario quiera escribir, generar o mejorar una guía de compra, comparativa de productos, ranking de los mejores X, post de afiliado, reseña con intención de compra, o cualquier contenido orientado a monetización con enlaces de afiliado. También actívala si el usuario menciona: "guía de compra", "mejor [producto]", "comparativa", "review seo", "post de afiliado", "contenido para amazon", "artículo de afiliación", "los mejores X", o frases similares. Este skill cubre estructura SEO, intención de búsqueda, copywriting persuasivo y buenas prácticas E-E-A-T.

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files body ≈ 1 764 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Crea guías de compra SEO optimizadas para posts de afiliado en español.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerMarketingtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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 51/100

  • 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
  • 85Steps. 56 steps, 1 vague phrases
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1764 tokens
  • 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 8 example trigger phrases
  • +3Description length 652: enough signal without eating the budget
  • +4Structure: 23 headings
  • +3Step-by-step instructions: 56 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.