Customization

Before executing, check for user customizations at: ~/.claude/skills/PAI/USER/SKILLCUSTOMIZATIONS/Science/

If this directory exists, load and apply any PREFERENCES.md, configurations, or resources found there. These override default behavior. If the directory does not exist, proceed with skill defaults.

🚨 MANDATORY: Voice Notification (REQUIRED BEFORE ANY ACTION)

You MUST send this notification BEFORE doing anything else when this skill is invoked.

Send voice notification:

curl -s -X POST http://localhost:8888/notify \
  -H "Content-Type: application/json" \
  -d '{"message": "Running the WORKFLOWNAME workflow in the Science skill to ACTION"}' \
  > /dev/null 2>&1 &

Output text notification:

Running the **WorkflowName** workflow in the **Science** skill to ACTION...

This is not optional. Execute this curl command immediately upon skill invocation.

Science - The Universal Algorithm

The scientific method applied to everything. The meta-skill that governs all other skills.

The Universal Cycle

GOAL -----> What does success look like?
   |
OBSERVE --> What is the current state?
   |
HYPOTHESIZE -> What might work? (Generate MULTIPLE)
   |
EXPERIMENT -> Design and run the test
   |
MEASURE --> What happened? (Data collection)
   |
ANALYZE --> How does it compare to the goal?
   |
ITERATE --> Adjust hypothesis and repeat
   |
   +------> Back to HYPOTHESIZE

The goal is CRITICAL. Without clear success criteria, you cannot judge results.

Workflow Routing

Output when executing: Running the **WorkflowName** workflow in the **Science** skill to ACTION...

Core Workflows

Trigger	Workflow
"define the goal", "what are we trying to achieve"	`Workflows/DefineGoal.md`
"what might work", "ideas", "hypotheses"	`Workflows/GenerateHypotheses.md`
"how do we test", "experiment design"	`Workflows/DesignExperiment.md`
"what happened", "measure", "results"	`Workflows/MeasureResults.md`
"analyze", "compare to goal"	`Workflows/AnalyzeResults.md`
"iterate", "try again", "next cycle"	`Workflows/Iterate.md`
Full structured cycle	`Workflows/FullCycle.md`

Diagnostic Workflows

Trigger	Workflow
Quick debugging (15-min rule)	`Workflows/QuickDiagnosis.md`
Complex investigation	`Workflows/StructuredInvestigation.md`

Resource Index

Resource	Description
`METHODOLOGY.md`	Deep dive into each phase
`Protocol.md`	How skills implement Science
`Templates.md`	Goal, Hypothesis, Experiment, Results templates
`Examples.md`	Worked examples across scales

Domain Applications

Domain	Manifestation	Related Skill
Coding	TDD (Red-Green-Refactor)	Development
Products	MVP -> Measure -> Iterate	Development
Research	Question -> Study -> Analyze	Research
Prompts	Prompt -> Eval -> Iterate	Evals
Decisions	Options -> Council -> Choose	Council

Scale of Application

Level	Cycle Time	Example
Micro	Minutes	TDD: test, code, refactor
Meso	Hours-Days	Feature: spec, implement, validate
Macro	Weeks-Months	Product: MVP, launch, measure PMF

Integration Points

Phase	Skills to Invoke
Goal	Council for validation
Observe	Research for context
Hypothesize	Council for ideas, RedTeam for stress-test
Experiment	Development (Worktrees) for parallel tests
Measure	Evals for structured measurement
Analyze	Council for multi-perspective analysis

Key Principles (Quick Reference)

Goal-First - Define success before starting
Hypothesis Plurality - NEVER just one idea (minimum 3)
Minimum Viable Experiments - Smallest test that teaches
Falsifiability - Experiments must be able to fail
Measure What Matters - Only goal-relevant data
Honest Analysis - Compare to goal, not expectations
Rapid Iteration - Cycle speed > perfect experiments

Anti-Patterns

Bad	Good
"Make it better"	"Reduce load time from 3s to 1s"
"I think X will work"	"Here are 3 approaches: X, Y, Z"
"Prove I'm right"	"Design test that could disprove"
"Pretend failure didn't happen"	"What did we learn?"
"Keep experimenting forever"	"Ship and learn from production"

Quick Start

Goal - What does success look like?
Observe - What do we know?
Hypothesize - At least 3 ideas
Experiment - Minimum viable tests
Measure - Collect goal-relevant data
Analyze - Compare to success criteria
Iterate - Adjust and repeat

The answer emerges from the cycle, not from guessing.