AC content-repurposing-engine
Transform one long-form piece of content into platform-native posts for LinkedIn, Twitter/X, Email, Instagram, and Blog/DEV.to. Use when: (1) repurposing blog posts into social content, (2) turning newsletters into multi-platform threads, (3) turning videos/podcasts into written content, (4) building a week of social content from one anchor piece, (5) creating LinkedIn posts, Twitter threads, or email sequences. Triggers on: "repurpose", "content repurposing", "one article many platforms", "turn blog to social", "LinkedIn post from newsletter", "Twitter thread from article", "content calendar", "multi-platform content", "social media content machine", "content recycling
As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
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: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Transform one long-form piece of content into platform-native post… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 57/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 3 mutating operations with no state check
- 40Consistency. Frontmatter name (content-repurposing-engine) differs from the folder (content-repurposing-engine-pro)
- 55Failures and branches. 1 branches
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 14 steps
- 100Execution cost. Instruction body is 1904 tokens
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 9 example trigger phrases
- +3Description length 678: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 14 items
- +4Has examples (10 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.