SKILLEMALL.ai

AD Regex Assistant

AI-powered regular expression generation, explanation, testing, debugging, and cross-language conversion. Generate regex from natural language, explain complex patterns, test against files, debug failures, and convert between Python, JavaScript, Go, Java, Rust and more. Powered by evolink.ai

ClawHub Agent Skills author: EvolinkAI v1.0.0 MIT-0 10 files · 1 script body ≈ 955 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
99
Quality 40%
81
Run on models
none yet
Process rating
D
41/100
Unfinished process
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Exfiltration net-credential-use scripts/regex.sh:44
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host; quoted — discussed, not commanded)
      local api_key="${EVOLINK_API_KEY:?Set EVOLINK_API_KEY for AI features. Get one at https://evolink.ai/signup}"
      vendor-hostquoted

    Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 41/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (Regex Assistant) differs from the folder (ai-regex-assistant)
    • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
    • 100Steps. 11 steps
    • 100Execution cost. Instruction body is 955 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low The response is described with custom markup (9 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 292: enough signal without eating the budget
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 11 items
    • +4Has examples (0 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

    External checks

    ClawHub: clean
    This is a disclosed AI regex tool; its main risk is that AI commands can send your regex inputs and selected file content to EvoLink.
    LLM: benign (high) · VirusTotal: · 29 May 2026