SKILLEMALL.ai

AC search-image

Search images from text queries and return the most relevant image result, candidate images, source pages, or ready-to-open search links. Use when the user asks to search for an image, find reference images, look up a character, person, brand, mascot, meme, wallpaper, avatar, or logo, wants several engines searched, wants the best match instead of the literal first result, or wants the best candidate sent as an attachment. Prefer multi-engine search with relevance ranking, then download and send the best match; if confidence is weak or downloading fails, return several candidate links and search URLs.

ClawHub Agent Skills author: mumu v0.1.0 MIT-0 21 files body ≈ 2 063 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 61/100 · Has gaps — weak spots: inputs and preconditions, consistency, running it twice

ReferenceInfrastructureDesignMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
61/100
Has gaps
Inputs and preconditions w 11
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: 21. 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 61/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 17 mutating operations with no state check
    • 40Consistency. Frontmatter name (search-image) differs from the folder (smart-image-search)
    • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 92 steps, 1 vague phrases
    • 100Failures and branches. 10 branches, has a failure section
    • 100Execution cost. Instruction body is 2063 tokens
    • low 11 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (4 tags): a typed call is more reliable

    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)
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • -32 of 9 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 608: enough signal without eating the budget
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 92 items
    • +3Output format is stated explicitly
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (9 of 9)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This skill does ordinary image searching and downloading, but users should know their search terms are sent to public image search engines.
    LLM: benign (high) · VirusTotal: · 29 May 2026