Review Experiment Results
harness/harness-skills
Explain Harness FME experiment results: winner determination, statistical significance, guardrail metric impact, and data-quality caveats (low sample size, missing data).
Analyse a finished A/B test and write an honest results readout with real statistics.
Install Experiment Readout
$ npx skills add mohitagw15856/pm-claude-skills --skill experiment-readout -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mohitagw15856/pm-claude-skills experiment-readout --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/experiment-readout .claude/skills/experiment-readout && rm -rf skills-srcUse ~/.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/
Install the "experiment-readout" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/experiment-readout into .claude/skills/experiment-readout/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "experiment-readout", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/experiment-readoutType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mohitagw15856/pm-claude-skills --skill experiment-readout -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mohitagw15856/pm-claude-skills experiment-readout --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/experiment-readout .agents/skills/experiment-readout && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "experiment-readout" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/experiment-readout into .agents/skills/experiment-readout/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "experiment-readout", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mohitagw15856/pm-claude-skills --skill experiment-readout -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mohitagw15856/pm-claude-skills experiment-readout --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/experiment-readout .cursor/skills/experiment-readout && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "experiment-readout" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/experiment-readout into .cursor/skills/experiment-readout/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "experiment-readout", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mohitagw15856/pm-claude-skills.git --path skills/experiment-readout--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mohitagw15856/pm-claude-skills --skill experiment-readout -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mohitagw15856/pm-claude-skills experiment-readout --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/experiment-readout .gemini/skills/experiment-readout && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "experiment-readout" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/experiment-readout into .gemini/skills/experiment-readout/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "experiment-readout", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mohitagw15856/pm-claude-skills experiment-readoutInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mohitagw15856/pm-claude-skills --skill experiment-readout -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/experiment-readout .github/skills/experiment-readout && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "experiment-readout" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/experiment-readout into .github/skills/experiment-readout/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "experiment-readout", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mohitagw15856/pm-claude-skills --skill experiment-readout -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mohitagw15856/pm-claude-skills experiment-readout --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/experiment-readout .opencode/skills/experiment-readout && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "experiment-readout" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/experiment-readout into .opencode/skills/experiment-readout/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "experiment-readout", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
experiment-readout- GitHub stars
- 1.4k
- Token cost
- ~1k tokens
- SKILL.md length
- 468 words
- Files
- 2 (incl. scripts)
- Skills in repo
- 1,348
- Repo updated
- First seen
- Licence
- MIT
At a glance
Analyse a finished A/B test and write an honest results readout with real statistics.
- Asked to read out an A/B test
- SKILL.md covers Required Inputs, Output Format, Programmatic Helper and Quality Checks, plus 3 more sections
- Runs Python scripts from its folder; calls python3
- Analyse experiment results
What it does
Experiment Readout is an agent skill from mohitagw15856/pm-claude-skills. Analyse a finished A/B test and write an honest results readout with real statistics. Use when asked to read out an A/B test, analyse experiment results, check if a result is statistically significant, or decide ship/no-ship from test data. Produces a readout — the computed lift, p-value & confidence interval, a significance verdict, guardrail check, and a clear ship / no-ship / iterate recommendation. Includes a stdlib significance calculator.
Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/ab_significance.py`).
It sits in Data & Analytics, covering Statistics and A/B testing. The repository describes itself as: 1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in… The licence is MIT.
When your agent uses it
- Asked to read out an A/B test
- Analyse experiment results
- Check if a result is statistically significant
- Decide ship/no-ship from test data
Example prompts
- “/experiment-readout”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit 1cbf1f0. 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
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3
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.
Context cost
Experiment Readout loads about 1k tokens when it runs. Until then it costs about 117 tokens; SKILL.md has 468 words of instructions outside code blocks.
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); the scripts in this folder are not scanned.
SKILL.md
The full file from mohitagw15856/pm-claude-skills at commit 1cbf1f0, republished under its MIT licence (© mohitagw15856). 468 words, ~1,034 tokens.
Download SKILL.mdSave it as
.claude/skills/experiment-readout/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- experiment-readout
- description
- Analyse a finished A/B test and write an honest results readout with real statistics. Use when asked to read out an A/B test, analyse experiment results, check if a result is statistically significant, or decide ship/no-ship from test data. Produces a readout — the computed lift, p-value & confidence interval, a significance verdict, guardrail check, and a clear ship / no-ship / iterate recommendation. Includes a stdlib significance calculator.
Experiment Readout Skill
A test result is only a decision if the statistics are sound — and "variant looks higher" is not a result. This skill computes the lift, the p-value, and a confidence interval from the raw counts, checks the guardrails, and writes an honest readout with a clear ship/no-ship call — flagging the traps (peeking, underpowered, novelty, a significant but tiny effect) that make teams ship noise.
Required Inputs
Ask for these only if they aren't already provided:
- The metric & data — for a conversion test: users and conversions per variant (control vs. treatment). For a continuous metric: mean, SD, and n per variant.
- The hypothesis — what you expected and the minimum effect that matters.
- Guardrail metrics — what shouldn't get worse (revenue, latency, retention).
- Test setup — planned sample size/duration, and whether it ran to plan (for the peeking check).
Output Format
Experiment Readout: [test name]
1. Result — computed (use the helper): control vs. treatment rate, absolute & relative lift, p-value, and the confidence interval on the difference.
| Variant | N | Conversions | Rate |
|---|---|---|---|
| Control | |||
| Treatment |
→ Lift: X% (CI: [a%, b%]) · p = 0.0xx
2. Verdict — significant at the stated bar or not, and whether the effect is big enough to matter (a significant +0.2% may not be worth the complexity). Distinguish statistical from practical significance.
3. Guardrails — did anything you promised not to harm move? A win that tanks a guardrail isn't a win.
4. Validity checks — was it run to the planned sample (no peeking/early-stopping)? Sample-ratio mismatch? Novelty/seasonality? Call out anything that undermines the result.
5. Recommendation — ship / no-ship / iterate / re-run, with the reason. If inconclusive, say so — "no significant difference" is a valid, useful result, not a failure to spin.
Show full SKILL.md (191 more words)Show less
Programmatic Helper
scripts/ab_significance.py (stdlib only) computes the two-proportion z-test, p-value, lift, and CI:
# python3 ab_significance.py <control_n> <control_conv> <treat_n> <treat_conv>
python3 scripts/ab_significance.py 10000 800 10000 880
python3 scripts/ab_significance.py 10000 800 10000 880 --jsonQuality Checks
- Lift, p-value, and a confidence interval are computed (not just "higher")
- Statistical significance AND practical significance are both assessed
- Guardrail metrics are checked, not just the primary
- Validity is checked: ran to planned n, no peeking, no sample-ratio mismatch
- An inconclusive result is reported honestly, not spun into a win
- The recommendation is explicit (ship/no-ship/iterate/re-run)
Anti-Patterns
- Do not call significance by eye — compute the p-value and CI; a higher number isn't a result
- Do not ignore the confidence interval — a CI spanning zero (or huge) means you don't actually know the effect
- Do not confuse statistical with practical significance — a tiny significant lift may not be worth shipping
- Do not trust a peeked/early-stopped test — stopping when it looks good inflates false positives massively
- Do not spin a null result — "no detectable difference" is honest and often the right call
Based On
Frequentist A/B analysis — two-proportion z-test, confidence intervals, guardrails, and the peeking/practical-significance pitfalls.
Example Trigger Phrases
- "Read out an A/B test."
- "Analyse experiment results."
- "Check if a result is statistically significant."
- "Decide ship/no-ship from test data."
© mohitagw15856, 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 1 other file (scripts) in skills/experiment-readout of mohitagw15856/pm-claude-skills.
- SKILL.md
- scripts/ab_significance.py
Open the folder on GitHubat commit 1cbf1f0
Compare with similar skills
Experiment 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Experiment Readout this skillmohitagw15856/pm-claude-skills | 1.4k | — | ~1k | Automated safety check: Pass | MIT | |
| Review Experiment Resultsharness/harness-skills | 115 | — | ~3.9k | Automated safety check: Pass | Apache-2.0 | |
| A/B Test Analysisphuryn/pm-skills | 27k | — | ~893 | Automated safety check: Pass | MIT | |
| Statistical Analystalirezarezvani/claude-skills | 28k | — | ~2.5k | Automated safety check: Pass | MIT | |
| Experimentation Analyticsrampstackco/claude-skills | 945 | — | ~8.9k | Automated safety check: Pass | MIT | |
| Power Analysisgaasher/Agent-Loop-Skills | 174 | — | ~2.2k | Automated safety check: Pass | MIT |
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Related
Questions about Experiment Readout
What does Experiment Readout do?
Analyse a finished A/B test and write an honest results readout with real statistics. Experiment Readout is an agent skill from mohitagw15856/pm-claude-skills. Analyse a finished A/B test and write an honest results readout with real statistics.
When should I use Experiment Readout?
Experiment Readout fits situations like: asked to read out an A/B test; analyse experiment results; check if a result is statistically significant; decide ship/no-ship from test data.
How do I install Experiment Readout in Claude Code?
Run `npx skills add mohitagw15856/pm-claude-skills --skill experiment-readout -a claude-code`. Or copy the skill folder (skills/experiment-readout in mohitagw15856/pm-claude-skills) into .claude/skills/experiment-readout in your project. Claude Code loads it when a task matches its description.
How do I install Experiment Readout in Codex?
Run `npx skills add mohitagw15856/pm-claude-skills --skill experiment-readout -a codex`. Or copy the skill folder (skills/experiment-readout in mohitagw15856/pm-claude-skills) into .agents/skills/experiment-readout in your project. Codex loads it when a task matches its description.
Can I use Experiment 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 mohitagw15856/pm-claude-skills --skill experiment-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/experiment-readout, .gemini/skills/experiment-readout, .github/skills/experiment-readout and .opencode/skills/experiment-readout in your project.
What does Experiment Readout need to run?
Going by SKILL.md and its folder, Experiment Readout needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Experiment 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 Experiment 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Experiment Readout use?
Experiment Readout is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Experiment Readout use?
About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Experiment Readout?
Skills that share tags, products or a category with Experiment Readout: Review Experiment Results (harness/harness-skills, 115 stars), A/B Test Analysis (phuryn/pm-skills, 27k stars), Statistical Analyst (alirezarezvani/claude-skills, 28k stars) and Experimentation Analytics (rampstackco/claude-skills, 945 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Experiment Readout?
mohitagw15856 (a GitHub user) maintains it in mohitagw15856/pm-claude-skills, which has 1,434 GitHub stars. The repository holds 1,348 skills in this directory. The repository was last updated on October 9, 2026.
Source: mohitagw15856/pm-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.