amazing-psycoder

SKILL开发
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安装这个技能

Entry point for the Amazing PsyCoder system. Routes user requests through the mandatory three-skill chain: Programming (5-phase design) → Coder (code generation) → Reviewer (audit). Supports PsychoPy, jsPsych, and Psychtoolbox with 38 paradigm references. Trigger for 心理学实验、实验代码、实验程序、PsychoPy实验、jsPsych实验、psychtoolbox实验、编写实验、生成实验代码、审计实验代码.

一句话选型结论

按资料字段整理

amazing-psycoder是开发类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类开发 安装方式未标注 权限级别未标注权限 许可证许可证不明确
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权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_15292d5a/yjkj-amazing-psycoder
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

开发
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_15292d5a仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791622254
正文体量18.0 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
写代码与改 bug

按需求补代码、定位并修掉报错。

读仓库与生成改动

让模型读懂项目结构,再给出可落地的改动。

跑测试与排查故障

按现象排查问题,补测试用例并复跑。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在开发场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
amazing-psycoder当前 未标注权限 未标注 未标注 未标注 有
技能审查员 浏览器控制 ClawHub 市场 877.9 万 OpenClaw 有
Vercel React 最佳实践 浏览器控制 GitHub 仓库 849.1 万 Codex、Claude、Cursor 有
GitHub 代码协作 联网访问 ClawHub 市场 763.3 万 OpenClaw 有
网页设计指南 联网访问 GitHub 仓库 668.6 万 Codex、Claude、Cursor 有
本体论 只读 ClawHub 市场 663.7 万 OpenClaw 有

SKILL.md 全文

18.0 KB
模型实际读到的说明书原文,来自技能仓库

Amazing PsyCoder — System Orchestrator

Version

v1.2 — stable, 2026-06-06.

Purpose

This is the single entry point for the Amazing PsyCoder experimental skill system. It orchestrates a mandatory sequential chain of three sub-skills that convert psychological experiment ideas into audited, production-quality code.

This skill does NOT generate code itself. It routes the user through the correct sequence and enforces the chain: Programming → Coder → Reviewer. No step may be skipped.

Platforms: Claude Code / Codex / Hermes / OpenClaw — follows the agentskills.io open standard. See PLATFORMS.md for platform-specific installation and tool mapping.

System Architecture

User describes experiment (English / 中文)
       │
       ▼
┌──────────────────────────────────────┐
│ ① psych-experiment-programming      │  Orchestration layer
│   Input: natural language description│  5-phase design workflow
│   Output: config YAML + conditions   │  Design Decision Registry
│   Gates: Gate 1→2→3→4→5             │  Progressive confirmation
└──────────────┬───────────────────────┘
               │ config YAML (internal artifact, not shown to user)
               ▼
┌──────────────────────────────────────┐
│ ② psych-experiment-coder            │  Code generation layer
│   Input: config YAML + conditions    │  12-step code template
│   Output: runnable code + README     │  4-layer priority architecture
│   Gate: 9-item post-generation check │  Canonical Code Skeleton
└──────────────┬───────────────────────┘
               │ Runnable experiment code
               ▼
┌──────────────────────────────────────┐
│ ③ psych-experiment-code-reviewer    │  Audit layer (final mandatory gate)
│   Input: code / config / plan        │  5 review modes
│   Output: audit report + readiness   │  Platform-aware checks
│   Gate: 0 Critical + 0 Major         │  Severity grading
└──────────────────────────────────────┘

> All three steps are mandatory — none can be skipped. Programming → Coder → Reviewer. No experiment code is considered complete without passing reviewer audit with ready_for_collection or ready_after_minor_fixes.

How to Use This Skill

When a user invokes this skill, determine where they are in the pipeline and route accordingly:

Routing Decision Tree

User request
  │
  ├─ "I want to build an experiment" / "我要做一个…实验"
  │    → Invoke psych-experiment-programming (start Phase 1)
  │
  ├─ "Generate code for this config" / "生成代码"
  │    → Check: has Programming Gate 5 passed?
  │       Yes → Invoke psych-experiment-coder
  │       No  → Route back to psych-experiment-programming first
  │
  ├─ "Review this experiment code" / "审计这个实验"
  │    → Invoke psych-experiment-code-reviewer
  │
  ├─ "I got an error" / "代码报错"
  │    → Check the error type:
  │       Design error → psych-experiment-programming
  │       Code error   → psych-experiment-coder (see Debugging & Iteration Loop)
  │
  ├─ "Review found issues" / "审计不通过" / "代码有问题需要修"
  │    → Check the severity:
  │       Critical/Major issues → Fix in psych-experiment-coder, re-audit after
  │       Minor only → User can collect data; fix when convenient
  │
  ├─ "What paradigms are available?" / "有哪些范式"
  │    → Show [Paradigm Coverage Matrix](#paradigm-coverage-matrix)
  │
  └─ "How does this system work?" / "这个系统怎么用"
       → Show system overview + three-step chain

Mandatory Execution Order

  1. First: Invoke psych-experiment-programming — guide user through 5-phase design. Output: complete config YAML (internal, not shown to user)
  2. Second: Invoke psych-experiment-coder — generate platform code from config. Output: .py/.js/.m + README
  3. Third: Invoke psych-experiment-code-reviewer — audit the generated code. Output: audit report + readiness label

Never skip a step. Never generate code before the trial window timeline is confirmed.


Design Principles (System-Wide)

# Principle Description Applies to
1 Output is deliverable Every phase produces complete, usable artifacts All
2 Progressive confirmation Design decisions confirmed phase by phase; defaults flagged [ASSUMED] Programming
3 Decision traceability Design Decision Registry records source of every decision Programming
4 Skeleton-first generation All code generation MUST start from platform spec Canonical Code Skeleton Coder
5 Paradigms provide logic, skeleton provides API Paradigm files define experiment logic; API patterns from spec skeleton Coder
6 Anti-pattern zero-tolerance time.sleep(), event.getKeys(maxWait=), KbCheck for RT, jsPsych.init(), WaitSecs — blocked Coder, Reviewer
7 Your experiment, our standards User owns the experimental design; system guarantees code quality All
8 Window timeline before code No code generation before trial window timeline is validated Programming, Coder
9 Post-generation audit mandatory All generated code must pass through Reviewer before data collection Coder, Reviewer
10 Input bounds output Reviewer's conclusions cannot exceed what the input supports Reviewer

Red Lines (System-Wide Absolute Prohibitions)

These rules span all three skills. Violation is never acceptable:

# Rule Owned by Consequence of violation
R1 No code generation before trial window timeline is complete Programming Structural errors, expensive late-stage fixes
R2 No assumed response mapping Programming Guessing key mapping invalidates accuracy data
R3 No time.sleep() in experiment code Coder Blocks event loop, Escape unresponsive
R4 No event.getKeys(maxWait=...) Coder Blocks event loop
R5 No data saved only at experiment end Coder Crash = all data lost
R6 No silent filling of [MISSING] values Programming Every gap must be resolved by asking user or offering flagged default
R7 No Chinese/CJK text without explicit font Coder PsychoPy default font lacks CJK glyphs; text renders as tofu (□□□)
R8 No skipping paradigm Must-Confirm items Programming Unconfirmed items produce broken experiments
R9 No rt_onset omitted on response windows Coder Missing/incorrect RT onset invalidates all reaction time data
R10 No code delivery without Reviewer pass All All code must pass reviewer audit before data collection

Code Generation Architecture (4-Layer Priority)

All platforms use the same 4-layer priority stack. When layers conflict, higher always wins:

Layer 1: spec/          ← Highest: API spec, anti-patterns, Canonical Code Skeleton
Layer 2: mapping/       ← Structural: config YAML fields → platform code structures
Layer 3: paradigms/      ← Paradigm logic: window sequence, accuracy rules, condition structure
Layer 4: demo/          ← Lowest: raw demo code, logic reference only, never API reference

Code generation priority: spec canonical skeleton > spec anti-patterns > config→code mapping > paradigm logic > demos

Platform Layer Fill Status

Layer PsychoPy jsPsych Psychtoolbox
L1 spec/ ✅ ✅ ✅
L2 mapping/ ✅ ✅ ✅
L3 paradigms/ ✅ 27 paradigms ✅ 25 paradigms ✅ 5 paradigms
L4 demo/_raw/ ✅ 45 .py ✅ 23 .js ✅ 100 .md

Code Template (Overview)

All generated code follows a 12-step structure: imports → parameters → display setup → stimulus preloading → condition loading → helpers → instructions → practice → main loop (blocks → randomization → per-trial windows) → incremental data save → cleanup → package with README. The full template with detailed per-step requirements is in the coder SKILL.md.


Post-Generation Quality Gate (Overview)

Before delivery, all generated code must pass the 9-item Quality Gate defined in the coder SKILL.md. Covers: spec skeleton compliance, anti-pattern scan, API patterns, parameter placement, escape handling, RT source, incremental save, preloading, and CJK font config. Any failure = fix before delivery.


Review Modes and Readiness Labels

Review Modes (auto-selected by Reviewer)

Mode Input Maximum label
code-audit Complete experiment code ready_for_collection
config-audit Config YAML / trial timeline pre_code_ready
implementation-plan-review Pseudocode / architecture plan pre_code_ready
triage-only Natural-language description None (missing-info list only)
blocked Insufficient input None (state what's needed)

Readiness Labels

Label Meaning
ready_for_collection Zero Critical + zero Major — can collect data
ready_after_minor_fixes Only Minor issues remain
not_ready_for_collection Critical or Major issues exist — do NOT collect
pre_code_ready Design complete, ready for code generation
needs_experiment_info Key design information missing
blocked Input insufficient for any review

Severity Classification

Severity Definition Can collect data?
Critical Invalidates all data; must fix before any collection No
Major Degrades data quality; fix before formal collection No
Minor Does not affect data quality; fix when convenient Yes

Paradigm Coverage Matrix

Core Paradigms (14) — Full Programming-Layer Spec

All 10 required sections filled (When to Use, Core Logic, Must Confirm, Do Not Assume, Condition File Columns, Trial Window Timeline, Data Output Columns, Randomization Checks, Common Failure Modes, Example):

Go/No-go · Navon · Priming · Stroop · Eriksen Flanker · Simon · Rating · Stop-signal · IAT · N-back · Dot-probe · Visual Search · Task Switching · EAST

Extended Paradigms (24) — Programming-Layer Reference Descriptions

Antisaccade · ANT · BART · Bilingual Stroop · Change Detection · Children Flanker · Choice RT · Climate Reflection · CPT · Corsi Blocks · Cyberball · Delay Discounting · Drag and Drop · Mental Rotation · Multisensory Nature · Numerical Stroop · Phone a Friend · Posner Cuing · Psychophysics Staircase · Rating to Choice · Sternberg · Ultimatum Game · WCST · Writing Distraction

Paradigm Count Explained

Layer Count What they are
Programming paradigms/ 38 (14 core + 24 extended) Design references for the 5-phase workflow. Apply to ALL platforms
Coder psychopy/paradigms/ 27 PsychoPy code references with platform-specific generation logic
Coder jspsych/paradigms/ 25 jsPsych code references with timeline plugins
Coder psychtoolbox/paradigms/ 5 PTB code references; most paradigms use 12-step template for manual adaptation

Cross-Platform Mandatory API Quick Reference

Dimension PsychoPy jsPsych (7.x) Psychtoolbox
Keyboard keyboard.Keyboard(backend='ptb') Plugin class references KbQueueCreate + KbQueueCheck
RT source key.rt (USB HID async) data.rt (automatic) firstPress - VBLTimestamp
RT origin win.callOnFlip(kb.clock.reset) Stimulus onset (automatic) VBLTimestamp = Screen('Flip') return
Timing loop CountdownTimer trial_duration parameter vbl + (waitframes-0.5)*ifi
Data save try/finally + per-trial flush on_finish callback try/catch + fopen/fprintf/fclose
Quit Escape check in every loop 'escape' in choices KbCheck(KbName('ESCAPE'))
Cleanup win.close() + core.quit() jsPsych.endCurrentTimeline() sca + Priority(0) + ShowCursor
CJK font FONT_CONFIG toggle + TextBox2 CSS font-family Screen('TextFont') + TextStyle

Inter-Skill Communication Protocol

Programming → Coder

  • Artifact: Complete config.yaml (internal, never shown to user)
  • Precondition: Gate 5 passed (user confirmed full Design Decision Registry)
  • Coder's duty: Load config → select platform → copy skeleton → map code → Quality Gate → deliver

Coder → Reviewer

  • Artifact: Generated experiment code (.py / .js / .m) + condition files + README
  • Precondition: Coder's Post-Generation Quality Gate passed
  • Reviewer's duty: Detect platform → load corresponding spec → audit each dimension → output graded report + readiness label

Shared Artifacts

Artifact Producer Consumer Format
config YAML Programming Coder .yaml (internal, not displayed)
Condition files Programming Coder .xlsx / .csv
Experiment code Coder Reviewer, User .py / .js / .m
Experiment README Coder Reviewer, User .md (alongside code)
Audit report Reviewer User Markdown (graded + readiness label)

Code Output Specification

Deliverables

Every code generation produces two files:

File Format Content
Platform experiment file .py / .js / .m Runnable code, all parameters at top, FONT_CONFIG toggle if CJK used
Experiment README .md Window sequence diagram, condition/block structure, response rules, data columns, how to run, parameter line numbers, known limitations

Language Consistency

Code comments and README language MUST match the user's language:
- 中文用户 → 中文 README + 中文代码注释
- English user → English README + English code comments


File Structure

amazing-psycoder-skills/
├── amazing-psycoder/                       ← Entry orchestrator (this skill)
│   ├── SKILL.md
│   ├── PLATFORMS.md                        ← Platform adapter reference
│   ├── install.sh                          ← Cross-platform installer
│   ├── psych-experiment-programming/        ← ① Orchestration layer
│   │   ├── SKILL.md                         ← 5-phase workflow + 10 red lines
│   │   ├── README.md
│   │   ├── paradigms/                       ← 38 paradigm reference files
│   │   └── references/                      ← Design references (config-schema, timing, etc.)
│   ├── psych-experiment-coder/              ← ② Code generation layer
│   │   ├── SKILL.md                         ← Generation flow + 4-layer arch + 9-item gate
│   │   ├── README.md
│   │   ├── psychopy/                        ← PsychoPy (full auto)
│   │   │   ├── spec/README.md               ← Canonical Skeleton + anti-patterns
│   │   │   ├── mapping/README.md            ← Config→code mapping
│   │   │   ├── paradigms/                    ← 27 paradigm references
│   │   │   └── demo/_raw/                   ← 45 demo .py files
│   │   ├── jspsych/                         ← jsPsych
│   │   │   ├── spec/README.md               ← Canonical Skeleton + anti-patterns
│   │   │   ├── mapping/README.md            ← Config→timeline + migration table
│   │   │   ├── paradigms/                    ← 25 paradigm references
│   │   │   └── demo/_raw/                   ← 23 demo .js files
│   │   └── psychtoolbox/                    ← PTB
│   │       ├── spec/README.md               ← Canonical Skeleton + anti-patterns
│   │       ├── mapping/README.md            ← Config→MATLAB + frame loops
│   │       ├── paradigms/                    ← 5 paradigm references
│   │       └── demo/_raw/                     ← 100 API demos by category
│   └── psych-experiment-code-reviewer/      ← ③ Audit layer
│       ├── SKILL.md                         ← 5 review modes + platform-aware audit
│       └── README.md
├── docs/                                    ← Multi-language READMEs
│   ├── README_EN.md
│   ├── README_ZH-HANT.md
│   ├── README_JA.md
│   ├── README_DE.md
│   └── README_FR.md
└── README.md                                ← Main README (简体中文)

When NOT to Use This Skill

  • Quick PsychoPy/jsPsych/PTB API questions: Answer directly; don't invoke the full workflow
  • General Python/JavaScript/MATLAB questions: Answer directly
  • Non-experiment programming tasks: Not in scope

常见问题

5 问
答案由本站依据条目字段整理
amazing-psycoder怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_15292d5a/yjkj-amazing-psycoder。安装方式为未标注。装完刷新技能列表或重开客户端。

amazing-psycoder支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

amazing-psycoder权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

amazing-psycoder收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

amazing-psycoder用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。