experiment-design
Skill33 starsChanged 9 months agoMITView on GitHub
Designs fast, reliable validation experiments with hypothesis, method, success metric, and decision rules (Ship/Iterate/Kill). Use when you need to validate an assumption or test a product hypothesis before committing resources.
Files
Experiment Design Planner
Purpose
Design fast, reliable validation experiments.
Steps
- State the hypothesis.
- Choose the smallest valid test.
- Define success metric.
- Set sample size or duration.
- Define decision rule.
Output
Hypothesis
Experiment Method
Success Metric
Duration / Sample Size
Decision Rule
Ship / Iterate / Kill
References
See worked example for a complete scenario.
Other versions29 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 29
- microsoft/hve-core★ 1.6ksame name
- growthenginenowoslawski/coldoutboundskills★ 759same name
- lingzhi227/agent-research-skills★ 350same name
- Yeachan-Heo/My-Jogyo★ 241same name
- flonat/flonat-research★ 145same name
- voidful/academic-skills★ 126same name
- itseffi/agentic-os★ 114same name
- TashanGKD/tashan-research-skills★ 19same name
- opensite-ai/opensite-skills★ 15same name
- lenar-amirov/product-pipeline-public★ 13same name
19 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
Used alongsideProjects with it also use list-quality-scorecard and positive-reply-scoring.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
automatewithudaySkilllist-quality-scorecard
Use when a lead list is enriched and about to be uploaded to Smartlead or another sender, and it needs a grade on duplicates, title relevance, bad-title patterns, catch-all density, verification coverage, and ICP fit first. Also use when a campaign underperformed and the list is the suspect.
Also in 3 projects that use this
- automatewithudaySkill
positive-reply-scoring
Use when judging whether a Smartlead campaign is actually working: pull replies, classify them (interested, soft positive, referral, neutral, negative, OOO, bounce, unsubscribe), and compute positive reply rate against the 1% bar. Also use when raw reply rate looks fine but pipeline is not showing up.
Also in 3 projects that use this
In this repository14 other files it gives its agents.
- assumption-mapperSkill
- feature-adoption-analyzerSkill
- jtbd-extractorSkill
- launch-readinessSkill
- outcome-definitionSkill
- post-launch-learningSkill
- prd-criticSkill
- problem-claritySkill
- retention-drop-diagnoserSkill
- roadmap-reality-checkerSkill
- stakeholder-alignment-checkerSkill
- tradeoff-articulatorSkill
- user-segment-prioritizerSkill
- value-vs-effortSkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.