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PsychoPy Experiment Design Skill

作者 hoffnung131 · GitHub ↗ · v1.0.1 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install psychopy-experiment-design-skill
功能描述
Helps design and refine PsychoPy experiments by clarifying research focus, specifying variables, structuring hypotheses, and planning analysis for rigorous a...
使用说明 (SKILL.md)

PsychoPy Experiment Design Skill

Purpose

This skill helps users design, build, troubleshoot, and document experimental tasks using PsychoPy, PsychoJS, Pavlovia, or similar online psychology experiment platforms. It is especially suitable for psychology, cognitive neuroscience, rehabilitation, and behavioral experiments.

The skill focuses on practical implementation, clear trial structure, reliable data recording, and participant-friendly task design.

When to Use

Use this skill when the user needs help with:

  • Designing a PsychoPy Builder experiment
  • Creating a trial-by-trial task structure
  • Setting up blocks, mini-blocks, and practice trials
  • Writing instruction pages
  • Creating condition files in Excel or CSV format
  • Designing tasks such as Stroop, CPT, n-back, oddball, SRTT, Go/No-Go, or reaction-time tasks
  • Checking whether output data look correct
  • Troubleshooting PsychoPy or PsychoJS errors
  • Adapting a task for children, older adults, or clinical populations
  • Making the task suitable for online deployment
  • Explaining experiment timing, response rules, and data columns
  • Writing a task procedure for a thesis, proposal, or ethics application

Typical User Inputs

The user may provide:

  • A task name or paradigm
  • A flowchart or screenshot
  • Trial timing requirements
  • Number of trials, blocks, or mini-blocks
  • Stimulus materials
  • Response keys
  • Target and non-target definitions
  • PsychoPy screenshots
  • Error messages
  • Data files such as CSV or Excel files
  • Requirements for online deployment

If the user provides screenshots, infer the likely PsychoPy Builder structure and explain concrete steps.

Core Workflow

1. Define the Experimental Logic

Identify:

  • What the participant sees or hears
  • What the participant needs to do
  • What counts as a correct response
  • What variables need to be recorded
  • How many trials are needed
  • How trials are grouped into blocks or mini-blocks
  • Whether practice and feedback are needed

2. Build the Trial Timeline

Represent each trial clearly, for example:

Fixation: 500 ms
Stimulus: 1000 ms
Response window: 2000 ms
Blank screen / ITI: 500 ms

For clinical or child participants, avoid overly fast presentation and provide adequate practice.

3. Design the Builder Structure

Translate the task into PsychoPy Builder components:

instructions
practice_trials loop
practice_feedback
formal_instructions
block_loop
trial_loop
break_screen
ending

Explain what each routine and loop should contain.

4. Prepare the Condition File

Condition files should usually include columns such as:

trial_index
block
mini_block
stimulus
condition
correct_answer
is_target
duration
feedback_text

For reaction-time tasks, include correct response keys and target labels.

5. Check Data Recording

Important data columns may include:

  • stimulus identity
  • condition
  • correct response
  • actual response
  • accuracy
  • reaction time
  • block number
  • trial number
  • target / non-target label
  • missed response

For online studies, ensure that resources are uploaded and paths are compatible with PsychoJS.

6. Troubleshoot Errors

Common problems include:

  • Missing resource files
  • Incorrect file paths
  • Components starting at the wrong time
  • Loops not connected correctly
  • Conditions file not selected
  • Unsupported Python code in PsychoJS
  • Wrong variable names
  • Response component not saving data
  • Stimuli appearing only after a click
  • Practice loop not ending
  • Formal trials not starting

When diagnosing errors, prioritize the likely Builder structure and timing settings before suggesting complex code changes.

Output Requirements

The output should be practical and step-by-step. When possible, provide:

  • Recommended Builder routines
  • Loop nesting structure
  • Component settings
  • Example condition-file columns
  • Example code snippets if needed
  • Data-checking logic
  • A concise description suitable for a research proposal

Use clear headings such as:

1. Overall Task Structure
2. Builder Setup
3. Condition File Design
4. Timing Settings
5. Response Recording
6. Data Output Check
7. Common Problems

Special Considerations

For Clinical Participants

Tasks should be:

  • Simple to understand
  • Not too fast
  • Not too long
  • Divided into blocks with breaks
  • Supported by practice trials
  • Designed with clear instructions
  • Tolerant of slower reaction times

For Online Deployment

Check:

  • Whether all files are in the resources folder
  • Whether image/audio file paths are relative paths
  • Whether code components are compatible with JavaScript
  • Whether the experiment works in the browser before formal data collection

For Data Quality

Recommend excluding or flagging trials with:

  • No response
  • Extremely fast responses
  • Extremely slow responses
  • Incorrect key presses
  • Technical interruptions

Do not claim data are valid based only on file existence. Check trial counts, target counts, missing responses, accuracy pattern, and reaction-time distribution.

Example Prompts

我需要用 PsychoPy 做一个 oddball 程序,请告诉我 Builder 里每一步怎么设置。
请帮我把这个 CPT 表格拆分成两个 block。
这个 PsychoPy 数据对吗?请帮我检查 target 数量、反应和正确率。
我的任务上传到 Pavlovia 后图片不显示,可能是什么原因?
请帮我写一段实验流程,用于开题报告或伦理申请。

Example Output Style

For a task design request, use a concrete structure:

Routine 1: instruction
- Text component: task instructions
- Keyboard component: press space to continue

Routine 2: fixation
- Text component: +
- Duration: 0.5 s

Routine 3: stimulus
- Image or text component: $stimulus
- Keyboard component: record response
- Duration: 2 s

Loop: trials
- Conditions file: conditions.xlsx
- Number of repetitions: 1

For data checking, summarize clearly:

The data file contains 40 formal trials. There are 8 target trials and 32 non-target trials. No missing responses were found. The target count matches the task design, so the basic structure appears correct.
安全使用建议
Reasonable to install for help with PsychoPy or PsychoJS experiment design. If using it to inspect research data, share anonymized files only and remove participant-identifying information first.
能力评估
Purpose & Capability
The artifact's stated purpose is to help design, build, troubleshoot, and document PsychoPy/PsychoJS experiments, and the content stays within trial structure, condition files, timing, data checks, and proposal-style documentation.
Instruction Scope
Instructions are practical workflow guidance and do not request prompt overrides, hidden behavior, credential use, unrelated authority, or automatic actions.
Install Mechanism
The package contains a single SKILL.md markdown file with no executable scripts, dependencies, install hooks, or package execution steps.
Credentials
The skill may ask users to provide screenshots, error messages, experiment details, or CSV/Excel data files; this is proportionate for PsychoPy troubleshooting but users should avoid sharing identifiable participant data.
Persistence & Privilege
No persistence, background execution, privilege escalation, credential access, browser/session use, local indexing, or long-running worker behavior was found.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install psychopy-experiment-design-skill
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /psychopy-experiment-design-skill 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.1
- Updated skill to focus on PsychoPy experiment design and troubleshooting, replacing previous academic writing guidance. - Added steps for building trial structures, preparing condition files, and data checking for psychological/behavioral experiments. - Included use cases such as online deployment, error diagnosis, and practical recommendations for adapting tasks to clinical or special populations. - Provided clear output templates and example prompts specifically tailored for PsychoPy Builder and PsychoJS users.
v1.0.0
Academic Research Writing Skill v1.0.0 - Initial Release - Provides structured support for postgraduate-level academic research writing, including literature reviews, proposals, and methodology sections. - Guides users through organizing academic logic, clarifying research focus, and improving language precision. - Offers workflows for hypothesis formulation, methodological consistency, and appropriate academic tone. - Supports both English and Chinese academic writing, with translation and polishing features. - Includes specific guidance for clinical, psychology, and neuroscience research contexts. - Example-oriented approach for generating structured research content and output.
元数据
Slug psychopy-experiment-design-skill
版本 1.0.1
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

PsychoPy Experiment Design Skill 是什么?

Helps design and refine PsychoPy experiments by clarifying research focus, specifying variables, structuring hypotheses, and planning analysis for rigorous a... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 65 次。

如何安装 PsychoPy Experiment Design Skill?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install psychopy-experiment-design-skill」即可一键安装,无需额外配置。

PsychoPy Experiment Design Skill 是免费的吗?

是的,PsychoPy Experiment Design Skill 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

PsychoPy Experiment Design Skill 支持哪些平台?

PsychoPy Experiment Design Skill 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 PsychoPy Experiment Design Skill?

由 hoffnung131(@hoffnung131)开发并维护,当前版本 v1.0.1。

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