experiment-analysis-assistant
- Repo stars 1
- Author repo claude-skills
Experiment Analysis Assistant
Overview
Interpret A/B test outcomes, edge cases, segmentation effects, and decision confidence.
Core Workflow
- Gather the smallest high-signal evidence set: failing outputs, logs, configs, recent changes, and relevant runtime context.
- Inspect the implementation and surrounding setup to isolate the narrowest plausible failure surface.
- Rank likely causes, rule out weak explanations, and identify the most actionable next fix or experiment.
- Validate the explanation with the smallest reliable check the repo or environment supports.
Deliver
- A concise diagnosis with the most likely root cause or bounded uncertainty.
- The highest-signal evidence and suspect files, configs, or systems involved.
- The smallest safe fix path or next experiment to run.
Guardrails
- Do not claim a root cause without evidence that explains the observed behavior.
- Separate symptoms from likely causes and call out uncertainty explicitly.
- Prefer the smallest reproducible scope before escalating to broad changes.
- Do not invent metrics, policy decisions, customer commitments, or ownership that the inputs do not support.
- Fluxly category
- Data
- Author-declared agents
- No explicit declaration found; this is not inferred or tested compatibility
- Static check
- 88 / 100 · heuristic scan, not runtime safety proof
- Author / version / license
- @00PrabalK00 · no license declared
- Fluxly token estimate
- Lean
- Fluxly setup estimate
- Plug-and-play
- External API key
- No requirement detected
- Detected OS requirements
- Unspecified
- Runtime requirements
- Unspecified
- Detected file/system behavior
-
- Read-only
- Detected network behavior
- Local-only
- Install commands
- None (reference only)
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
The current SKILL.md does not define a fixed output example. Interpret A/B test outcomes, edge cases, segmentation effects, and decision confidence.
Gather the smallest high-signal evidence set: failing outputs, logs, configs, recent changes, and relevant runtime context. Inspect the implementation and surrounding setup to isolate the narrowest plausible failure surface.
A concise diagnosis with the most likely root cause or bounded uncertainty. The highest-signal evidence and suspect files, configs, or systems involved. The smallest safe fix path or next experiment to run.
Do not claim a root cause without evidence that explains the observed behavior. Separate symptoms from likely causes and call out uncertainty explicitly. Prefer the smallest reproducible scope before escalating to broad changes.
# Experiment Analysis Assistant
## Overview
Interpret A/B test outcomes, edge cases, segmentation effects, and decision confidence.
## Core Workflow
1. Gather the smallest high-signal evidence set: failing outputs, logs, configs, recent changes, and relevant runtime context.
2. Inspect the implementation and surrounding setup to isolate the narrowest plausible failure surface.
3. Rank likely causes, rule out weak explanations, and identify the most actionable next fix or experiment.
4. Validate the explanation with the smallest reliable check the repo or environment supports.
## Deliver
- A concise diagnosis with the most likely root cause or bounded uncertainty.
- The highest-signal evidence and suspect files, configs, or systems involved.
- The smallest safe fix path or next experiment to run.
## Guardrails
- Do not claim a root cause without evidence that explains the observed behavior.
- Separate symptoms from likely causes and call out uncertainty explicitly.
- Prefer the smallest reproducible scope before escalating to broad changes.
- Do not invent metrics, policy decisions, customer commitments, or ownership that the inputs do not support. Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.
sections -> Overview → Core Workflow → Deliver → Guardrails
terms -> Interpret A/B test outcomes, edge cases, segmentation effects, and decision confidence. · 1. Gather the smallest high-signal evidence set: failing outputs, logs, configs, recent changes, and relevant runtime context. · - A concise diagnosis with the most likely root cause or bounded uncertainty. · - Do not claim a root cause without evidence that explains the observed behavior.
files/cmd -> A/B
body sha256 -> 02cd731b5dc8
Decide Fit First
Design Intent
How To Use It
Boundaries And Review