AgentSkillsCN

Science

基于科学方法的通用思维与迭代引擎。适用于用户说“思考一下”、“弄清楚”、“尝试各种方法”、“实验一下”、“测试这个想法”、“迭代改进”、“优化”时，或任何受益于结构化假设-测试-分析循环的问题解决场景。这是其他工作流所实现的元技能。

SKILL.md
--- frontmatter
name: Science
description: Universal thinking and iteration engine based on the scientific method. USE WHEN user says "think about", "figure out", "try approaches", "experiment with", "test this idea", "iterate on", "improve", "optimize", OR any problem-solving that benefits from structured hypothesis-test-analyze cycles. THE meta-skill that other workflows implement.

Customization

Before executing, check for user customizations at: ~/.opencode/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.

  1. •

    Send voice notification:

    bash
    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 &
  2. •

    Output text notification:

    code
    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

code
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

TriggerWorkflow
"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 cycleWorkflows/FullCycle.md

Diagnostic Workflows

TriggerWorkflow
Quick debugging (15-min rule)Workflows/QuickDiagnosis.md
Complex investigationWorkflows/StructuredInvestigation.md

Resource Index

ResourceDescription
METHODOLOGY.mdDeep dive into each phase
Protocol.mdHow skills implement Science
Templates.mdGoal, Hypothesis, Experiment, Results templates
Examples.mdWorked examples across scales

Domain Applications

DomainManifestationRelated Skill
CodingTDD (Red-Green-Refactor)Development
ProductsMVP -> Measure -> IterateDevelopment
ResearchQuestion -> Study -> AnalyzeResearch
PromptsPrompt -> Eval -> IterateEvals
DecisionsOptions -> Council -> ChooseCouncil

Scale of Application

LevelCycle TimeExample
MicroMinutesTDD: test, code, refactor
MesoHours-DaysFeature: spec, implement, validate
MacroWeeks-MonthsProduct: MVP, launch, measure PMF

Integration Points

PhaseSkills to Invoke
GoalCouncil for validation
ObserveResearch for context
HypothesizeCouncil for ideas, RedTeam for stress-test
ExperimentDevelopment (Worktrees) for parallel tests
MeasureEvals for structured measurement
AnalyzeCouncil for multi-perspective analysis

Key Principles (Quick Reference)

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

Anti-Patterns

BadGood
"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

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

The answer emerges from the cycle, not from guessing.