Skills send-experiment-designer
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send-experiment-designer

v19.0.0 Content revision r2 Safe βš™οΈ External commands🌐 Network accessπŸ“ Filesystem access

Design a reliable email experiment

Email teams can make costly decisions from underpowered or poorly controlled tests. This skill creates a structured experiment plan and interprets results using user-provided campaign data.

Supports: Claude Codex Code(CC)
πŸ₯ˆ 82 Silver

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request
Review the Skillstore skill "send-experiment-designer" from https://skillstore.io/skills/aaron-he-zhu-send-experiment-designer.md and its manifest at https://skillstore.io/api/skills/aaron-he-zhu-send-experiment-designer/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Test it

Using "send-experiment-designer". Plan a subject-line test with a 40% baseline open rate and a 3-point target lift.

Expected outcome:

  • Mode: A/B subject-line test
  • Primary metric: open rate; guardrails: unsubscribes and spam complaints
  • Plan: randomize recipients, keep content constant, set a fixed read date, and size each cell for the stated lift.

Using "send-experiment-designer". Interpret two variants with supplied delivered and conversion counts.

Expected outcome:

  • Effect: reports the observed conversion-rate difference and uncertainty.
  • Decision status: applies the named precommitted rule only when an owner and rule are supplied.
  • Guardrails: identifies whether unsubscribe, complaint, or bounce thresholds were breached.

Security Audit

Safe
v8 β€’ 7/27/2026 Open versioned report

Most static findings are false positives from Markdown formatting, documentation links, metadata URLs, and a statistical decimal. One documented command runs a local statistics helper; its numeric inputs and referenced script should be reviewed before use. No prompt-injection language, credential collection, data-exfiltration intent, or automatic network activity was found in SKILL.md.

1
Files scanned
138
Lines analyzed
1
Review items
0
False positives ignored
Capability review items (1)

These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.

Medium
Ruby/shell backtick execution
> **Statistical facts (keyless):** `python3 "${CLAUDE_PLUGIN_ROOT}/scripts/connectors/experiment.py"
The instructions explicitly invoke a local Python command to calculate experiment statistics. The arguments are intended to be numeric, but execution of a local script is an external-command capability that requires review of the referenced script.
Audited by: claude View Audit History β†’
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Open versioned report
Security Assessment

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Academic citations (APA Β· BibTeX Β· CFF)

APA citation

aaron-he-zhu. (2026). send-experiment-designer security audit report (audit version 8) [Author version 19.0.0]. Skillstore. https://skillstore.io/skills/aaron-he-zhu-send-experiment-designer/audits/8

BibTeX citation

@techreport{aaron-he-zhu-aaron-he-zhu-send-experiment-designer-2026, author = {aaron-he-zhu}, title = {send-experiment-designer security audit report (audit version 8)}, institution = {Skillstore}, year = {2026}, number = {8}, url = {https://skillstore.io/skills/aaron-he-zhu-send-experiment-designer/audits/8}, note = {Author version 19.0.0} }

CITATION.cff

cff-version: 1.2.0 message: "If you use this Skill, cite its author and this versioned security audit report." title: "send-experiment-designer security audit report (audit version 8)" version: "19.0.0" type: report authors: - name: "aaron-he-zhu" date-released: "2026-07-27" url: "https://skillstore.io/skills/aaron-he-zhu-send-experiment-designer/audits/8" identifiers: - type: other value: "skillstore:aaron-he-zhu-send-experiment-designer:audit:8" description: "Skillstore immutable audit report identifier"

Skillstore Score

Why this score Evidence Confidence: Medium
55
Architecture
100
Maintainability
87
Content
67
Community
100
Spec Compliance

What You Can Build

Plan a subject-line experiment

Define a controlled subject-line A/B test with sample size, guardrails, and a read date.

Assess a completed campaign test

Interpret delivered, open, click, and conversion counts with statistical and practical effect flags.

Measure incremental email value

Create a randomized hold-out plan to evaluate conversion or revenue lift from a send.

Try These Prompts

Beginner: plan an A/B test
Design an email A/B subject-line test. My baseline open rate is 38%, my list has 12,000 people, and I want to detect a 3-point lift.
Intermediate: plan a send-time test
Create a send-time test for our weekly newsletter. Baseline open rate is 40%, the list has 20,000 people, and content must stay constant.
Advanced: size a multivariate test
Plan a 2 by 2 subject and CTA experiment. Baseline click rate is 2.1%, send volume is 8,000 per week, alpha is .05, and power is .80.
Advanced: read a hold-out result
Read this hold-out result using my decision rule. Control: 10,000 delivered and 180 conversions. Variant: 10,000 delivered and 215 conversions. Guardrail unsubscribe rates were 0.12% and 0.13%.

Best Practices

  • Define one primary metric, a practical-effect threshold, and guardrails before sending.
  • Keep one variable isolated per cell and preserve a randomized control group.
  • Set the sample size and read date before the test, then avoid unplanned early decisions.

Avoid

  • Changing subject, creative, and send time in one test cell.
  • Calling a winner from an underpowered test or an early unplanned look.
  • Treating statistical significance as an automatic business decision without an approved rule.

Frequently Asked Questions

What test types can this skill plan?
It supports A/B, multivariate, send-time, and hold-out email experiments.
What data do I need for a new test?
Provide a baseline rate, list size or daily volume, and the minimum lift worth detecting.
What data do I need for a read-out?
Provide per-variant delivered counts and outcome counts, plus any relevant guardrail metrics.
Can it choose a winning campaign automatically?
No. It applies an action only when you provide an owner and a precommitted decision rule.
Does it create email copy?
No. It designs and evaluates experiments, but does not write the subject line, message body, or CTA.
Does it require an email platform connection?
No. It can work from manually exported data. Platform connections are optional conveniences.

Developer Details

License

Apache-2.0

Author version

v19.0.0

Skillstore revision

r2

Ref

0715a6e09ea875c8e28cb705ce87cc83045e69c1

Maintenance freshness

7/28/2026

Usage

3 downloads Β· 1 views

File structure

πŸ“„ SKILL.md