SKILLEMALL.ai

AC web-search

Search the public web through the AISA web search endpoint and return structured titles, links, and snippets. Use when: the user asks to look something up online, gather recent sources, or browse general web results.

ClawHub Agent Skills author: AIsa v1.0.0 MIT-0 4 files body ≈ 233 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
51/100
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

    • note frontmatter-key unknown frontmatter key "primaryEnv"
    • note frontmatter-key unknown frontmatter key "requires"

    Process rating: all ten parameters 51/100

    • 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
    • 40Consistency. Frontmatter name (web-search) differs from the folder (web-search-aisa)
    • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
    • 100Steps. 6 steps
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 233 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +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
    • +3Description length 216: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 6 items
    • +4Has examples (2 code blocks)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    This appears to be a real AISA search skill, but it advertises simple web search while the bundled client also supports URL extraction, deep-research/model queries, and AI synthesis through external endpoints.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026