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AC workflow-automator

Automate repeatable workflows with WhatsApp/Telegram notifications, Excel/CSV processing, browser automation, and flexible scheduling. Describe tasks in plain English — the agent decomposes, executes, and schedules them. Use when the user wants to automate multi-step tasks, schedule recurring workflows, extract data from websites, process files, or send reports to messaging channels.

ClawHub Agent Skills author: qashsolutions v2.0.6 MIT-0 15 files · 11 scripts body ≈ 4 518 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 63/100 · Has gaps — weak spots: inputs and preconditions, consistency, running it twice

ProcedureTelegramWhatsAppData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
94
Quality 40%
88
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
0
Running it twice w 4
30
Consistency w 8
40
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • medium Dangerous commands cmd-destructive-fs scripts/execute-step.sh:17
      Destructive filesystem command (wipes root/home/drive) (detector / deny-list definition; string literal in code, not executed)
      UNSAFE_PATTERNS="rm -rf /|mkfs|dd if=.*of=/dev|chmod -R 777 /|:(){ :|:& };:"
      detectorcode literal
    • low Dangerous commands cmd-privilege scripts/execute-step.sh:17
      Privilege escalation / world-writable permissions (detector / deny-list definition; string literal in code, not executed)
      UNSAFE_PATTERNS="rm -rf /|mkfs|dd if=.*of=/dev|chmod -R 777 /|:(){ :|:& };:"
      detectorcode literal

    Files scanned: 15. 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 63/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 12 mutating operations with no state check
    • 40Consistency. Frontmatter name (workflow-automator) differs from the folder (openclaw-workflow-automator)
    • 60Tools and files. Uses tools (bash, web) 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
    • 70Execution cost. Instruction body is 4518 tokens
    • 100Steps. 115 steps
    • 100Failures and branches. 5 branches, has a failure section
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 15 top-level sections: this looks like several domains in one skill

    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)
    • -35 of 11 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 386: enough signal without eating the budget
    • +4Structure: 40 headings
    • +3Step-by-step instructions: 115 items
    • +3Output format is stated explicitly
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    This is a powerful unattended workflow automation skill, not clear malware, but it can run approved shell, browser, messaging, and scheduled actions with persistent local data.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026