SKILLEMALL.ai

AC hairstyle-recommender

Analyze portrait photos to recommend the most flattering hairstyle based on face shape, facial features, hair texture, and personal style. Use when the user uploads a portrait/headshot photo and asks for hairstyle recommendations, haircut advice, or wants to see how they would look with a suggested hairstyle. Triggers on phrases like "推荐发型", "适合什么发型", "帮我看看剪什么头发", "发型建议", "hairstyle recommendation", "what haircut suits me".

ClawHub Agent Skills author: nellyxiaolong-cmyk v1.0.2 MIT-0 4 files body ≈ 1 085 tokens Open the sourceclawhub.ai analyzed 3 d ago

Analyze portrait photos to recommend the most flattering hairstyle based on face shape, facial features, hair texture, and personal style.

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
93
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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: 4. 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 59/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 54 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1085 tokens
    • 100Running it twice. No mutating operations

    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 427: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 54 items
    • +4Has examples (8 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: suspicious
    The skill is coherent for hairstyle advice, but it mandates portrait-based image generation without clear user consent or privacy disclosure for external tools.
    LLM: suspicious (high) · 7 Sept 2026