SKILLEMALL.ai

AC celebrate

Turn a real win into a set of designed, on-brand image assets for social media, email and a profile, in every size those channels need, built around a verified screenshot as proof. Use whenever someone lands a ranking, a milestone, a launch, a star count, an award, an acceptance, a shipped release, a chart position or any other public result and wants to post it, show it off, put it in a newsletter, or use it as hiring or fundraising evidence. Triggers on "make a screenshot I can post", "turn this into a social card", "banner for LinkedIn", "we hit #1", "we just crossed N users", "announcement image", "show off", "brag post", "celebrate this", or a pasted screenshot of a leaderboard, dashboard or chart.

ClawHub Agent Skills author: Ahmad Othman Ammar Adi. v0.1.0 MIT-0 16 files body ≈ 1 525 tokens Open the sourceclawhub.ai analyzed 4 h ago

Turn a real win into a set of designed, on-brand image assets for social media, email and a profile, in every size those channels need, built around a…

As a process C 63/100 · Has gaps — weak spots: result and completion, running it twice, progress reporting

AnalyzerMarketingData and analyticsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
99/100
safety, quality, tests
Safety 60%
100
Quality 40%
97
Run on models
none yet
Process rating
C
63/100
Has gaps
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: 15. 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 63/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 5 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1525 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
    • +2Single-language instructions
    • +5Description quotes 9 example trigger phrases
    • +3Description length 712: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 5 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (6 of 6)
    • +3All 2 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 97.

    External checks

    ClawHub: suspicious
    The skill’s purpose is coherent, but its renderer has under-disclosed unsafe config paths that can execute raw HTML/JavaScript and write files outside the intended output folder.
    LLM: suspicious (high) · 14 Sept 2026