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BA n8n-workflow-automation

Designs and outputs n8n workflow JSON with robust triggers, idempotency, error handling, logging, retries, and human-in-the-loop review queues. Use when you need an auditable automation that won’t silently fail.

ClawHub Agent Skills author: KOwl64 v1.0.0 3 files body ≈ 921 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process A 84/100 · Runs to the end — no weak spots found

ProcedureZapierInfrastructuretype 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
B
79/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
50
No improvement model run: 48% with skill · 55% without
Process rating
A
84/100
Runs to the end
When it triggers w 12
50
Tools and files w 18
60
Inputs and preconditions w 11
70
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: n8n-workflow-automation (ClawHub)

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: 3. 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 84/100

    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (web, node) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 49 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 921 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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 211: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 49 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    Model run · 10 Sept 2026

    With the skill
    48%
    -7 pp vs baseline
    Without the skill (baseline)
    55%
    triggers: +100% / −75%

    No improvement Pass rate 48% is below threshold 80%; Skill fires on negative phrases: only 75% handled correctly · 7 cases · $0.094

    External checks

    ClawHub: clean
    This skill is an instruction-only helper for designing n8n workflows and includes clear safeguards around secrets, approvals, logging, and review.
    LLM: benign (high) · VirusTotal: benign · 10 Jul 2026