SKILLEMALL.ai

AB image-analyzer-advisor

Analyze images and provide detailed visual insights, object detection, composition analysis, and actionable recommendations. Use when the user shares or references an image file or URL and wants detailed analysis, understanding of visual content, or suggestions for improvement. Triggers on requests like: "analyze this image", "what's in this photo", "examine this screenshot", "analyze this chart/graph/diagram", "what does this image show", "look at this image and tell me", or any request to inspect, describe, or get insights from an image. Also use when working with image URLs or file paths that need visual examination.

ClawHub Agent Skills author: Fuzzyb33s v1.0.1 MIT-0 2 files body ≈ 317 tokens Open the sourceclawhub.ai analyzed 2 d ago

Analyze images and provide detailed visual insights, object detection, composition analysis, and actionable recommendations.

As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, failures and branches, progress reporting

AnalyzerAI and agentstype 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
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Analyze images and provide detailed visual insights, object detect… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 68/100

    • 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
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 20 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 317 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)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +3Description length 627: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 20 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)

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

    External checks

    ClawHub: clean
    This is a simple image-analysis guidance skill with no executable code, persistence, credential use, or hidden behavior.
    LLM: benign (high) · VirusTotal: · 20 Jun 2026