SKILLEMALL.ai

AB email-sequences

Design and write email campaigns and sequences including onboarding flows, lifecycle campaigns, transactional emails, newsletters, broadcast sends, and launch and announcement emails. Use this skill whenever the user wants to write email copy, plan an email sequence, design an onboarding drip, or set up lifecycle email campaigns. Triggers on email sequence, drip campaign, onboarding email, lifecycle email, welcome email, transactional email, newsletter, email broadcast, launch email, announcement email, nurture sequence, abandoned cart, re-engagement, win-back. Also triggers when planning email automation flows or writing email subject lines for campaigns.

rampstackco/claude-skills Agent Skills author: rampstackco 4 files body ≈ 2 403 tokens Open the sourcegithub.com↗ analyzed 6 h ago

Design and write email campaigns and sequences including onboarding flows, lifecycle campaigns, transactional emails, newsletters, broadcast sends, and launch…

As a process B 78/100 · Nearly there — weak spots: running it twice, progress reporting

GeneratorMarketingWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
B
78/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Failures and branches w 10
50
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: email-sequences (rampstackco/claude-skills)

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: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "catalog_summary"
    • note frontmatter-key unknown frontmatter key "display_order"

    Process rating: all ten parameters 78/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 8 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 100 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2403 tokens

    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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 664: enough signal without eating the budget
    • +4Structure: 23 headings
    • +3Step-by-step instructions: 100 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.