SKILLEMALL.ai

AB newsletter-launch

Plug-and-play newsletter launcher. Runs a short setup wizard, then scaffolds all project files and wires up all automation crons for a fully operational newsletter in one conversation. Use when starting a new newsletter from scratch or setting up a second newsletter on a new topic. Triggers on: 'launch a newsletter', 'new newsletter', 'start a newsletter', 'set up a newsletter', 'create a newsletter', 'second newsletter', 'newsletter on [topic]'. NOT for: editing an existing newsletter, writing issues, or keyword research. Requires: newsletter-seo-pipeline skill must be installed.

ClawHub Agent Skills author: micphigoo v1.0.0 MIT-0 6 files body ≈ 2 865 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process B 65/100 · Nearly there — weak spots: result and completion, inputs and preconditions

GeneratorWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
B
65/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Tools and files w 18
60
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: 6. 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 65/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 70Failures and branches. 6 branches
    • 100Steps. 16 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2865 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (11 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
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 587: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 16 items
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: suspicious
    The skill is purpose-aligned newsletter automation, but it under-discloses sensitive credential storage and creates persistent jobs that can use those credentials and publish content.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026