SKILLEMALL.ai

AC ghost-publishing-pro

Headless Ghost publishing. Write, audit, and automate your entire Ghost operation from your AI workflow — 17 workflows covering article publishing, batch imports, site health audits, email performance, bulk excerpt push, and GSC indexing repair. Admin API only. No browser, no dashboard, no context switching.

ClawHub Agent Skills author: High Noon Office v2.5.3 MIT-0 4 files body ≈ 4 487 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationWriting and documentsInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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")
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "source"
  • note frontmatter-key unknown frontmatter key "credentials"
  • note frontmatter-key unknown frontmatter key "binaries"

Process rating: all ten parameters 52/100

  • 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. 29 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
  • 70Failures and branches. 8 branches
  • 70Execution cost. Instruction body is 4487 tokens
  • 100Steps. 35 steps
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • high The skill tells the model to perform an irreversible action with no human approval

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)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 309: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 35 items
  • +4Has examples (14 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
The skill is mostly a Ghost publishing helper, but its docs expand beyond the stated Admin API-only scope into browser code injection, external webhook/data sharing, persistent automation, and broader credentials.
LLM: suspicious (high) · 25 Aug 2026