SKILLEMALL.ai

AD lygo-automation-workflows

LYGO Automation Workflows — consent-aware playbook for identifying repetitive lattice/steward tasks worth automating, designing trigger→action plans, and choosing local-first tools (Sandcastle, Continuum, n8n self-hosted) before SaaS. Use when designing LYGO workflows, steward automation audits, or comparing Zapier/Make/n8n under P0/privacy constraints. Not a generic 'automate anything' trigger. Advisor only: no network, no account linking, no auto-publish.

ClawHub Agent Skills author: LYRA Agent - LYGO OS v1.0.0 MIT-0 9 files body ≈ 1 256 tokens Open the sourceclawhub.ai analyzed 2 d ago

LYGO Automation Workflows — consent-aware playbook for identifying repetitive lattice/steward tasks worth automating, designing trigger→action plans, and…

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureZapierInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
D
43/100
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 · 0

    ✓ No critical or high findings

    Files scanned: 9. 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 43/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 3 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 100Steps. 33 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1256 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 12 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)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +3Description length 461: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 33 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 2 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.

    External checks

    ClawHub: clean
    This skill is a local, consent-oriented automation planning guide and CLI, with no evidence of hidden network, account, publishing, or background behavior.
    LLM: benign (high) · VirusTotal: · 21 Aug 2026