AC ecommerce-content-marketing
E-commerce content marketing strategy planner. Generates content calendars, topic ideas, and platform-specific strategies by analyzing customer reviews, trends, competitor content, and SEO opportunities. Two modes: (A) Build — create a full content strategy from scratch, (B) Audit — analyze existing content and find gaps. Supports TikTok, Instagram, YouTube, Pinterest, blog/SEO, and Amazon A+. No API key required. Use when: (1) planning content for a new product launch, (2) building a content calendar, (3) finding viral content ideas, (4) analyzing competitor content strategies, (5) extracting customer pain points for content topics.
As a process C 55/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 5086 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 55/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Failures and branches. 4 branches
- 70Execution cost. Instruction body is 5086 tokens
- 85Steps. 65 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- low 12 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)
- +1No license
- +2Single-language instructions
- +3Description length 641: enough signal without eating the budget
- +4Structure: 33 headings
- +3Step-by-step instructions: 65 items
- +3Output format is stated explicitly
- +4Has examples (25 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.