SKILLEMALL.ai

AC searxng

Multi-engine web search aggregation via local Python script. Use when: (1) searching the web for information, articles, documentation, (2) searching code repos on GitHub/GitLab, (3) finding academic papers on arXiv/Semantic Scholar/Crossref, (4) searching Hacker News or Reddit discussions, (5) looking up HuggingFace models, (6) searching StackOverflow for programming answers, (7) fetching news from Bing News or Reuters, (8) any task requiring web search beyond the built-in web_search tool — especially when multiple sources or specific engines are needed. NOT for: single quick lookups (use web_search), image generation, or real-time streaming data.

ClawHub Agent Skills author: mrzhangkris v1.0.0 MIT-0 4 files body ≈ 1 577 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 64/100 · Has gaps — weak spots: consistency, running it twice, progress reporting

GeneratorGitHubGitLabSoftware developmentResearchWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
94
Run on models
none yet
Process rating
C
64/100
Has gaps
Progress reporting w 2
0
Running it twice w 4
30
Consistency w 8
40
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 64/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (searxng) differs from the folder (searxng-lite)
    • 50When it triggers. No condition that starts the skill
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 22 steps
    • 100Execution cost. Instruction body is 1577 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
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 655: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 22 items
    • +3Output format is stated explicitly
    • +4Has examples (4 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.

    External checks

    ClawHub: clean
    This is a disclosed multi-engine search tool, so its network requests are expected, but users should avoid sending sensitive queries to it.
    LLM: benign (high) · VirusTotal: · 29 May 2026