Agent skill

Ab Test Results Readout

by hashgraph-online in hashgraph-online/awesome-codex-plugins

Analyze and communicate A/B test results with metric readouts, subgroup analysis, data-quality checks, ad hoc investigation, visualization, and launch recommendations.

MITAuto-check passedMarketing & SEO

Install Ab Test Results Readout

skills CLI
$ npx skills add hashgraph-online/awesome-codex-plugins --skill ab-test-results-readout -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins ab-test-results-readout --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/ab-test-results-readout .claude/skills/ab-test-results-readout && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ab-test-results-readout
GitHub stars
1.3k
Token cost
~859 tokens
SKILL.md length
250 words
Files
6 (incl. references)
Skills in repo
716
Repo updated
First seen
Licence
MIT

At a glance

Analyze and communicate A/B test results with metric readouts, subgroup analysis, data-quality checks, ad hoc investigation, visualization, and launch recommendations.

  • Works in 7 steps: Reconstruct the test design: hypothesis,… → Verify data quality and whether… → Compare primary and guardrail metrics… → …
  • Interpreting experiment results
  • SKILL.md covers Source Traceability, Related Advanced Skills, Reference Routing and Workflow, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Ab Test Results Readout is an agent skill from hashgraph-online/awesome-codex-plugins. Analyze and communicate A/B test results with metric readouts, subgroup analysis, data-quality checks, ad hoc investigation, visualization, and launch recommendations. Use when interpreting experiment results, preparing an A/B test report, explaining flat or mixed results, checking guardrails, segmenting test/control data, or turning experiment data into a product decision.

Its SKILL.md is about 860 tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `guidelines.md`, `references/core/examples.md` and `references/core/knowledge.md`). Compatibility notes: Codex, Claude Code, and other Agent Skills-compatible clients.

It sits in Marketing & SEO, covering A/B testing and Data cleaning. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is MIT.

When your agent uses it

  • Interpreting experiment results
  • Preparing an A/B test report
  • Explaining flat
  • Checking guardrails

Example prompts

  • “/ab-test-results-readout”

Requirements

  • Compatibility (from SKILL.md): Codex, Claude Code, and other Agent Skills-compatible clients.

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Reconstruct the test design: hypothesis, variants, population, and metrics.
  2. Verify data quality and whether exposure/eligibility match the brief.
  3. Compare primary and guardrail metrics against baseline and decision rules.
  4. Run subgroup analysis when averages obscure meaningful differences.
  5. Investigate outliers, missing data, or surprising movement.
  6. Visualize results so stakeholders can compare control, test, and segments.
  7. Recommend ship, stop, iterate, or investigate with caveats.

What it can do on your machine

Read from SKILL.md and the folder at commit 3e1456a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Codex, Claude Code, and other Agent Skills-compatible clients.

    From compatibility in the SKILL.md frontmatter.

Context cost

Ab Test Results Readout loads about 859 tokens when it runs, and up to ~2.2k if it reads all its reference files. Until then it costs about 100 tokens; SKILL.md has 250 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~100
When it runs · the whole SKILL.md, loaded when a task matches
~859
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from hashgraph-online/awesome-codex-plugins at commit 3e1456a, republished under its MIT licence (© hashgraph-online). 250 words, ~859 tokens.

Download SKILL.mdSave it as .claude/skills/ab-test-results-readout/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
ab-test-results-readout
description
Analyze and communicate A/B test results with metric readouts, subgroup analysis, data-quality checks, ad hoc investigation, visualization, and launch recommendations. Use when interpreting experiment results, preparing an A/B test report, explaining flat or mixed results, checking guardrails, segmenting test/control data, or turning experiment data into a product decision.
compatibility
Codex, Claude Code, and other Agent Skills-compatible clients.
license
MIT
metadata.version
0.1.0
metadata.displayName
A/B Test Results Readout
metadata.category
Product Management
metadata.tags
practical-ab-testing,ab-testing,experimentation,analytics,data-visualization

A/B Test Results Readout

Use this skill to turn experiment data into a clear decision. It emphasizes metric interpretation, data-quality checks, subgroup analysis, ad hoc analysis, visualization, and launch recommendations.

Source Traceability

Primary source: Practical A/B Testing by Leemay Nassery. Guidance is transformed and paraphrased from chapter 4 lines 2950-3742 and chapter 1 lines 572-718. Metric tradeoff context comes from chapter 2 lines 1296-1472.

  • trustworthy-experiment-insights: use when the readout needs false positive, false negative, power, replication, meta-analysis, or suspicious-lift review.
  • experiment-verification-monitoring: use when result interpretation depends on whether assignment, exposure, metrics, canaries, or active monitoring were healthy.
  • long-term-impact-evaluation: use when short-term readout is not enough to decide durable product or business impact.

Reference Routing

NeedRead
Readout conceptsreferences/core/knowledge.md
Analysis and reporting rulesreferences/core/rules.md
Example readoutsreferences/core/examples.md
Step-by-step report workflowworkflows/prepare-results-readout.md

Workflow

  1. Reconstruct the test design: hypothesis, variants, population, and metrics.
  2. Verify data quality and whether exposure/eligibility match the brief.
  3. Compare primary and guardrail metrics against baseline and decision rules.
  4. Run subgroup analysis when averages obscure meaningful differences.
  5. Investigate outliers, missing data, or surprising movement.
  6. Visualize results so stakeholders can compare control, test, and segments.
  7. Recommend ship, stop, iterate, or investigate with caveats.

Output Format

markdown
# A/B Test Results Readout

## Executive Decision
[Ship | Stop | Iterate | Investigate] because [reason].

## Test Summary
- Hypothesis:
- Population:
- Control:
- Test:
- Run window:

## Metric Results
| Metric | Role | Control | Test | Change | Interpretation |
|--------|------|---------|------|--------|----------------|

## Segment Findings
| Segment | What changed | Decision impact |
|---------|--------------|-----------------|

## Data Quality Notes
- Eligibility/exposure:
- Missing data:
- Outliers:
- Instrumentation concerns:

## Recommendation
- Decision:
- Rollout conditions:
- Follow-up analysis:

Quality Bar

  • Do not hide guardrail regressions behind a primary-metric win.
  • Do not overstate subgroup findings; label them exploratory when not pre-planned.
  • Do not show only averages when the product decision depends on user groups.
  • Use charts to clarify comparisons, not to decorate the readout.

© hashgraph-online, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in plugins/LVTD-LLC/skills/skills/ab-test-results-readout of hashgraph-online/awesome-codex-plugins.

  • SKILL.md
  • guidelines.md
  • references/core/examples.md
  • references/core/knowledge.md
  • references/core/rules.md
  • workflows/prepare-results-readout.md

Open the folder on GitHubat commit 3e1456a

Compare with similar skills

Ab Test Results Readout next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Ab Test Results Readout compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Ab Test Results Readout this skillhashgraph-online/awesome-codex-plugins1.3k—~859Automated safety check: PassMIT
Review Experiment Resultsharness/harness-skills115—~3.9kAutomated safety check: PassApache-2.0
AnalyticsNexus-JPF/note-companion8707 repos~2.2kAutomated safety check: PassMIT
App Analyticsappeeky/aso-skills2.2k—~1.6kAutomated safety check: PassMIT
Ab Test Analysisnimrodfisher/data-analytics-skills470—~708Automated safety check: PassMIT
Ab Testingericrisco/rsc-harness180—~2.4kAutomated safety check: PassMIT

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Questions about Ab Test Results Readout

What does Ab Test Results Readout do?

Analyze and communicate A/B test results with metric readouts, subgroup analysis, data-quality checks, ad hoc investigation, visualization, and launch recommendations. Ab Test Results Readout is an agent skill from hashgraph-online/awesome-codex-plugins. Analyze and communicate A/B test results with metric readouts, subgroup analysis, data-quality checks, ad hoc investigation, visualization, and launch recommendations.

When should I use Ab Test Results Readout?

Ab Test Results Readout fits situations like: interpreting experiment results; preparing an A/B test report; explaining flat; checking guardrails.

How do I install Ab Test Results Readout in Claude Code?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill ab-test-results-readout -a claude-code`. Or copy the skill folder (plugins/LVTD-LLC/skills/skills/ab-test-results-readout in hashgraph-online/awesome-codex-plugins) into .claude/skills/ab-test-results-readout in your project. Claude Code loads it when a task matches its description.

How do I install Ab Test Results Readout in Codex?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill ab-test-results-readout -a codex`. Or copy the skill folder (plugins/LVTD-LLC/skills/skills/ab-test-results-readout in hashgraph-online/awesome-codex-plugins) into .agents/skills/ab-test-results-readout in your project. Codex loads it when a task matches its description.

Can I use Ab Test Results Readout in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill ab-test-results-readout -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ab-test-results-readout, .gemini/skills/ab-test-results-readout, .github/skills/ab-test-results-readout and .opencode/skills/ab-test-results-readout in your project.

What does Ab Test Results Readout need to run?

SKILL.md names no scripts, command-line tools or credentials: Ab Test Results Readout is instructions for the agent only. Compatibility (from SKILL.md): Codex, Claude Code, and other Agent Skills-compatible clients..

Does Ab Test Results Readout access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Ab Test Results Readout safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Ab Test Results Readout use?

Ab Test Results Readout is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ab Test Results Readout use?

About 859 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.4k tokens, read only when the agent opens those files.

What are the alternatives to Ab Test Results Readout?

Skills that share tags, products or a category with Ab Test Results Readout: Review Experiment Results (harness/harness-skills, 115 stars), Analytics (Nexus-JPF/note-companion, 870 stars), App Analytics (appeeky/aso-skills, 2.2k stars) and Ab Test Analysis (nimrodfisher/data-analytics-skills, 470 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ab Test Results Readout?

hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,267 GitHub stars. The repository holds 716 skills in this directory. The repository was last updated on October 10, 2026.

Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.