SKILLEMALL.ai

AB publish-preflight-studio

Check a post before it goes out, then fix what it finds. Paste the caption, title, script, on-screen text, or tags — this pre-publish content check reads the wording against advertising-copy restrictions and regulated-category claim rules and returns a replacement for every phrase it flags, reads the post back through the people you are writing for and names the exact line that loses each of them, scores the hook and the reason to share with the evidence behind each score, then hands back the corrected copy and renders the cover carrying the fixed wording. Use it as a social media copy check and a banned words checker before publishing, for ad-copy review, superlative screening, audience reaction testing, hook strength scoring, and pre-checking brand or client copy before it reaches an approver, for Instagram, TikTok, Facebook, YouTube, and LinkedIn.

ClawHub Agent Skills author: beatra-ai v0.1.3 MIT-0 16 files body ≈ 2 183 tokens Open the sourceclawhub.ai analyzed 2 d ago

Check a post before it goes out, then fix what it finds.

As a process B 68/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

AnalyzerYouTubeMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
B
68/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    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: 16. 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 68/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 7 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 16 steps
    • 100Inputs and preconditions. Inputs and preconditions are listed
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2183 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 862: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -32 of 3 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 16 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (10 of 10)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    The skill does the advertised copy and cover workflow, but it also requests broad Beatra powers and silently updates its own package by default.
    LLM: suspicious (high) · 28 Aug 2026