AB content-engine
Full-stack content creation pipeline from research to publication. Analyzes top-ranking competitor articles, identifies content gaps, generates SEO-optimized blog posts with brand voice, adds meta descriptions and internal link suggestions, formats for WordPress/Ghost/Notion/Hugo/Jekyll, and creates platform-specific social media promotion posts for LinkedIn, Twitter/X, and Reddit. Use this skill for: blog post writing, article creation, SEO content, keyword research, content gap analysis, content strategy, content calendar planning, "write a blog post about X", competitor content analysis, "what should I write about next", social media post generation from content, content marketing automation, editorial workflow, copywriting, long-form content, content optimization, meta description generation, or any request involving researching a topic and producing publish-ready content. Replaces manually chaining web research, writing, SEO tools, CMS formatting, and social scheduling into one step.
As a process B 69/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- 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
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 69/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 9 mutating operations with no state check
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 61 steps
- 100Failures and branches. 8 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1956 tokens
- 100Progress reporting. Reports progress
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 1003: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +4Structure: 17 headings
- +3Step-by-step instructions: 61 items
- +4Has examples (4 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.