Agent skill

Experimentation Throughput Strategy

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

Plan experiment throughput strategies for mature A/B testing programs.

MITAuto-check passedMarketing & SEO

Install Experimentation Throughput Strategy

skills CLI
$ npx skills add hashgraph-online/awesome-codex-plugins --skill experimentation-throughput-strategy -a claude-code

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

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins experimentation-throughput-strategy --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/experimentation-throughput-strategy .claude/skills/experimentation-throughput-strategy && 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
experimentation-throughput-strategy
GitHub stars
1.2k
Token cost
~913 tokens
SKILL.md length
280 words
Files
6 (incl. references)
Skills in repo
686
Repo updated
First seen
Licence
MIT

At a glance

Plan experiment throughput strategies for mature A/B testing programs.

  • Works in 6 steps: Map the current experiment pipeline and… → Identify whether the bottleneck is… → Decide whether isolated testing,… → …
  • Testing capacity is constrained
  • SKILL.md covers Source Traceability, Reference Routing, Workflow and Output Format, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Experimentation Throughput Strategy is an agent skill from hashgraph-online/awesome-codex-plugins. Plan experiment throughput strategies for mature A/B testing programs. Use when testing capacity is constrained, teams are waiting for experiment slots, roadmap coordination is slowing learning, or a team must choose isolated, overlapping, parallel, or capacity-aware experiment scheduling without sacrificing result quality.

Its SKILL.md is about 910 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. 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

  • Testing capacity is constrained
  • Teams are waiting for experiment slots
  • Roadmap coordination is slowing learning
  • A team must choose isolated

Example prompts

  • “/experimentation-throughput-strategy”

Requirements

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

Workflow steps

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

  1. Map the current experiment pipeline and where tests wait.
  2. Identify whether the bottleneck is traffic, coordination, tooling, review,
  3. Decide whether isolated testing, overlapping testing, or a hybrid model fits
  4. Define interference and interaction-effect safeguards.
  5. Add visibility: current tests, upcoming tests, capacity, ownership, and
  6. Write rollout rules so teams know when to schedule, overlap, defer, or split

What it can do on your machine

Read from SKILL.md and the folder at commit 78497e5. 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

Experimentation Throughput Strategy loads about 913 tokens when it runs, and up to ~3.1k if it reads all its reference files. Until then it costs about 90 tokens; SKILL.md has 280 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~90
When it runs · the whole SKILL.md, loaded when a task matches
~913
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.1k

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 78497e5, republished under its MIT licence (© hashgraph-online). 280 words, ~913 tokens.

Download SKILL.mdSave it as .claude/skills/experimentation-throughput-strategy/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
experimentation-throughput-strategy
description
Plan experiment throughput strategies for mature A/B testing programs. Use when testing capacity is constrained, teams are waiting for experiment slots, roadmap coordination is slowing learning, or a team must choose isolated, overlapping, parallel, or capacity-aware experiment scheduling without sacrificing result quality.
compatibility
Codex, Claude Code, and other Agent Skills-compatible clients.
license
MIT
metadata.version
0.1.0
metadata.displayName
Experimentation Throughput Strategy
metadata.category
Product Management
metadata.tags
practical-ab-testing,next-level-ab-testing,ab-testing,experimentation,product-analytics

Experimentation Throughput Strategy

Use this skill to increase the rate of product experimentation without turning the experiment pipeline into an unreliable traffic jam. It focuses on testing capacity, isolated versus overlapping strategies, interaction effects, and the process/tooling needed to coordinate experiments at scale.

Source Traceability

Primary source: Next-Level A/B Testing by Leemay Nassery. Guidance is transformed and paraphrased from Chapter 1 on rate, quality, and cost; Chapter 2 on testing availability, isolated and overlapping strategies, and interaction effects; and Chapter 9 on balancing rate with quality, cost, and usability.

Related skills:

  • ab-testing-platform-strategy for platform architecture and ownership.
  • experiment-verification-monitoring for monitoring conflicts and active-test health.
  • experiment-sensitivity-optimization for reducing traffic needs by improving metric sensitivity.

Reference Routing

NeedRead
Throughput concepts and terminologyreferences/core/knowledge.md
Strategy selection and coordination rulesreferences/core/rules.md
Scenario examples and tradeoffsreferences/core/examples.md
Step-by-step throughput planworkflows/improve-experiment-throughput.md

Workflow

  1. Map the current experiment pipeline and where tests wait.
  2. Identify whether the bottleneck is traffic, coordination, tooling, review, QA, analysis, or decision latency.
  3. Decide whether isolated testing, overlapping testing, or a hybrid model fits the product surface and metric precision needs.
  4. Define interference and interaction-effect safeguards.
  5. Add visibility: current tests, upcoming tests, capacity, ownership, and conflict flags.
  6. Write rollout rules so teams know when to schedule, overlap, defer, or split experiments.

Output Format

markdown
# Experimentation Throughput Plan

## Bottleneck
[What is limiting experiment rate and what evidence shows it.]

## Recommended Strategy
[Isolated | Overlapping | Hybrid | Keep current strategy] because [reason].

## Capacity View
| Surface or Audience | Current Tests | Upcoming Tests | Constraint | Owner |
|---------------------|---------------|----------------|------------|-------|

## Interference Safeguards
- Conflict dimensions:
- Monitoring:
- Escalation:

## Process And Tooling Changes
1. [Change]
2. [Change]
3. [Change]

## Decision Rules
- Overlap when:
- Isolate when:
- Defer when:
- Revisit when:

Quality Bar

  • Do not increase experiment count by ignoring validity risks.
  • Do not default to isolated testing when capacity is the primary constraint and experiments can run independently.
  • Do not default to overlapping testing when experiments change the same user journey, metric, or surface in ways that can interact.
  • Make the coordination mechanism explicit; "teams will communicate" is not a scalable throughput strategy.

© 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/experimentation-throughput-strategy of hashgraph-online/awesome-codex-plugins.

  • SKILL.md
  • guidelines.md
  • references/core/examples.md
  • references/core/knowledge.md
  • references/core/rules.md
  • workflows/improve-experiment-throughput.md

Open the folder on GitHubat commit 78497e5

Compare with similar skills

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Ad Test Designeraaron-he-zhu/aaron-marketing-skills2.9k2 repos~2.8kAutomated safety check: PassApache-2.0
Meta Tags Optimizernowork-studio/notfair-plugin3.9k1 repos~2.7kAutomated safety check: PassMIT

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Categories

Questions about Experimentation Throughput Strategy

What does Experimentation Throughput Strategy do?

Plan experiment throughput strategies for mature A/B testing programs. Experimentation Throughput Strategy is an agent skill from hashgraph-online/awesome-codex-plugins. Plan experiment throughput strategies for mature A/B testing programs.

When should I use Experimentation Throughput Strategy?

Experimentation Throughput Strategy fits situations like: testing capacity is constrained; teams are waiting for experiment slots; roadmap coordination is slowing learning; A team must choose isolated.

How do I install Experimentation Throughput Strategy in Claude Code?

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

How do I install Experimentation Throughput Strategy in Codex?

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

Can I use Experimentation Throughput Strategy 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 experimentation-throughput-strategy -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/experimentation-throughput-strategy, .gemini/skills/experimentation-throughput-strategy, .github/skills/experimentation-throughput-strategy and .opencode/skills/experimentation-throughput-strategy in your project.

What does Experimentation Throughput Strategy need to run?

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

Does Experimentation Throughput Strategy 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 Experimentation Throughput Strategy 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 Experimentation Throughput Strategy use?

Experimentation Throughput Strategy 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 Experimentation Throughput Strategy use?

About 913 tokens (SKILL.md is roughly 3.7k 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 2.2k tokens, read only when the agent opens those files.

What are the alternatives to Experimentation Throughput Strategy?

Skills that share tags, products or a category with Experimentation Throughput Strategy: Ab Testing (coreyhaines31/marketingskills, 54k stars), Analytics (Nexus-JPF/note-companion, 870 stars), Ab Test Setup (freekmurze/dotfiles, 1k stars) and Ad Test Designer (aaron-he-zhu/aaron-marketing-skills, 2.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Experimentation Throughput Strategy?

hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,242 GitHub stars. The repository holds 686 skills in this directory. The repository was last updated on October 8, 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.