AB youmind-ghost-article
Write and publish Ghost articles with AI — topic research via YouMind knowledge base, Ghost-oriented writing, Markdown-to-HTML conversion, feature image upload, and one-click publishing. Use when user wants to "write Ghost article", "publish to Ghost", "Ghost 文章", "发布到 Ghost".
Write and publish Ghost articles with AI — topic research via YouMind knowledge base, Ghost-oriented writing, Markdown-to-HTML conversion, feature image…
As a process B 69/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting
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: 24. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "triggers" - note
edit-residuethe text marks something as outdated (lines 105, 115, 118): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 69/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 23 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 38 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2834 tokens
- low 11 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
- +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 4 example trigger phrases
- +3Description length 277: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 38 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.