Install
openclaw skills install @soupandpsy/amazing-psycoderAmazing PsyCoder
Orchestrates psychological experiment creation by enforcing a 3-step chain: design via 5-phase programming, code generation, and mandatory code review for Ps...
Amazing PsyCoder — System Orchestrator
Version
v1.3 — stable, 2026-06-10. Adds analysis pipeline (psy-ana-designer → psy-ana-coder → psy-ana-reviewer).
Purpose
This is the single entry point for the Amazing PsyCoder system. It orchestrates two mandatory sequential chains that convert psychological experiments from idea to audited code, and experimental data from raw files to publication-ready analysis:
- Experiment Pipeline: psy-exp-designer (5-phase design) → psy-exp-coder (code generation) → psy-exp-reviewer (audit)
- Analysis Pipeline: psy-ana-designer (5-phase progressive) → psy-ana-coder (R/Python code) → psy-ana-reviewer (audit)
This skill does NOT generate code itself. It routes the user through the correct sequence and enforces that 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
Experiment Pipeline
User describes experiment (English / 中文)
│
▼
┌──────────────────────────────────────┐
│ ① psy-exp-designer │ 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 psy-exp-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 psy-exp-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
└──────────────────────────────────────┘
Analysis Pipeline
User has experiment data + scientific questions
│
▼
┌──────────────────────────────────────┐
│ ④ psy-ana-designer │ Analysis design layer
│ Input: experiment config + questions│ 5-phase progressive confirmation
│ Output: analysis config YAML │ 12-dimension method comparison
│ Gates: Gate 1→2→3→4→5 │ 60 methods + 48 charts refs
└──────────────┬───────────────────────┘
│ analysis config YAML
▼
┌──────────────────────────────────────┐
│ ⑤ psy-ana-coder │ Analysis code generation
│ Input: analysis config YAML │ 12-step script structure
│ Output: analysis.R/.py + report │ R (tidyverse/lme4/ggplot2)
│ Gate: 10-item Quality Gate │ Python (pandas/statsmodels/seaborn)
└──────────────┬───────────────────────┘
│ Runnable analysis script
▼
┌──────────────────────────────────────┐
│ ⑥ psy-ana-reviewer │ Analysis audit layer
│ Input: analysis script + data │ 4 review modes
│ Output: audit report + readiness │ Statistical correctness checks
│ Gate: 0 Critical + 0 Major │ Reproducibility scoring
└──────────────────────────────────────┘
Two independent pipelines. Seven skills total (1 orchestrator + 6 sub-skills). Same rigorous standard. Experiment: Designer→Coder→Reviewer. Analysis: Designer→Coder→Reviewer.
All steps in both pipelines are mandatory — none can be skipped. Experiment: Designer → Coder → Reviewer. Analysis: Designer → Coder → Reviewer. No experiment code is complete without passing reviewer audit. No analysis script is publishable without reproducibility audit.
How to Use This Skill
When a user invokes this skill, analyze their request to determine which pipeline and stage they need. The user's own words tell you where to route them — no forced stage-selection question unless their intent is genuinely ambiguous.
Routing Decision Tree
Route directly based on the user's expressed need:
Analyze the user's request — what do they actually want?
│
├─ 🧪 EXPERIMENT — they want to build/design/code/review an experiment
│
│ ├─ "I want to build an experiment" / "我要做一个…实验" / "设计一个…范式"
│ │ → psy-exp-designer (start Phase 1)
│ │
│ ├─ "Generate experiment code from this config" / "用这个config生成实验代码"
│ │ → User has config → psy-exp-coder
│ │
│ ├─ "Generate experiment code" / "生成实验代码" (no config visible)
│ │ → "你有实验 config YAML 吗？如果没有，需要先通过 psy-exp-designer 设计实验。"
│ │ Has config → psy-exp-coder
│ │ No config → psy-exp-designer
│ │
│ ├─ "Review this experiment code" / "审计这个实验" / "实验代码有没有问题"
│ │ → psy-exp-reviewer
│ │
│ └─ "Experiment code error" / "实验代码报错"
│ → Design error → psy-exp-designer
│ Code error → psy-exp-coder
│
├─ 📊 ANALYSIS — they want to design/code/review a data analysis
│
│ ├─ "Design my analysis" / "设计分析方案" / "用什么统计方法" / "怎么分析这个数据"
│ │ → psy-ana-designer (start Phase 1)
│ │
│ ├─ "Analyze my data" / "分析我的数据" / "帮我做统计分析"
│ │ → psy-ana-designer (design before code — never jump straight to coder)
│ │
│ ├─ "Generate analysis code from this config" / "用这个analysis config生成代码"
│ │ → User has analysis_config.yaml → psy-ana-coder
│ │
│ ├─ "Generate analysis code" / "生成分析代码" (no config visible)
│ │ → "你有 analysis_config.yaml 吗？如果没有，需要先通过 psy-ana-designer 设计分析方案。"
│ │ Has config → psy-ana-coder
│ │ No config → psy-ana-designer
│ │
│ ├─ "Review this analysis" / "审计分析代码" / "检查分析脚本"
│ │ → psy-ana-reviewer
│ │
│ └─ "Analysis script error" / "分析代码报错" / "分析结果不对"
│ → Design error (wrong method) → psy-ana-designer
│ Code error (API misuse) → psy-ana-coder
│
├─ 🔀 CROSS-PIPELINE — experiment done, now want analysis
│
│ ├─ "Experiment passed review, now analyze the data" / "实验做完了，分析数据"
│ │ → psy-ana-designer
│ │ → "如果有实验 config YAML 可以直接复用；没有的话我帮你手动收集实验信息。"
│ │
│ └─ "Build experiment AND analyze" / "设计实验并分析数据"
│ → psy-exp-designer first → after pipeline completes, remind user to return for analysis
│
├─ ❓ AMBIGUOUS — unclear which pipeline
│
│ └─ "帮我做 Stroop" / "I want to do a Stroop study"
│ → "你需要设计实验程序，还是分析已有数据？"
│ Build experiment → psy-exp-designer
│ Analyze data → psy-ana-designer
│
└─ ℹ️ GENERAL
├─ "有哪些范式" → Paradigm Coverage Matrix
├─ "有哪些分析方法" → 60 methods + 48 charts summary
└─ "这个系统怎么用" → System overview + both pipelines
Mandatory Execution Order
Experiment Pipeline:
- First: Invoke
psy-exp-designer— guide user through 5-phase design. Output: experiment config YAML - Second: Invoke
psy-exp-coder— generate platform code from config. Output:.py/.js/.m+ README - Third: Invoke
psy-exp-reviewer— audit the generated code. Output: audit report + readiness label
Analysis Pipeline:
- First: Invoke
psy-ana-designer— guide user through 5-phase progressive confirmation. Output: analysis config YAML - Second: Invoke
psy-ana-coder— generate R or Python analysis script. Output:analysis.R/.py+ report - Third: Invoke
psy-ana-reviewer— audit the analysis script. Output: audit report + readiness label
Never skip a step. Never generate experiment code before the trial window timeline is confirmed. Never generate analysis code before the scientific question and method are 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 ⚠️ | Both Designers |
| 3 | Decision traceability | Decision Registry records source of every decision | Both Designers |
| 4 | Skeleton-first generation | All code generation MUST start from platform spec Canonical Code Skeleton | Both Coders |
| 5 | Spec provides API, reference provides logic | Paradigms/methods define logic; API patterns from spec | Both Coders |
| 6 | Anti-pattern zero-tolerance | Blocking APIs, wrong RT sources, missing random effects — blocked | Both Coders & Reviewers |
| 7 | Your experiment/analysis, our standards | User owns the design; system guarantees code quality | All |
| 8 | Design before code | No code generation before design is confirmed | Both pipelines |
| 9 | Post-generation audit mandatory | All generated code must pass through Reviewer before use | Both Coders & Reviewers |
| 10 | Input bounds output | Reviewer's conclusions cannot exceed what the input supports | Both Reviewers |
| 11 | Scientific question drives method | Analysis methods chosen by scientific question, not habit | psy-ana-designer |
| 12 | 12-dimension comparison | Every method choice backed by structured A vs B comparison | psy-ana-designer |
| 13 | Method before code | Analysis method must be confirmed before generating analysis code | psy-ana-designer, psy-ana-coder |
| 14 | Recovery path always provided | Audit reports with Critical/Major issues MUST include explicit fix path back to the correct upstream skill | Both Reviewers |
Red Lines (System-Wide Absolute Prohibitions)
These rules span all six pipeline skills. Violation is never acceptable:
| # | Rule | Owned by | Consequence of violation |
|---|---|---|---|
| R1 | No code generation before trial window timeline is complete | psy-exp-designer | Structural errors, expensive late-stage fixes |
| R2 | No assumed response mapping | psy-exp-designer | Guessing key mapping invalidates accuracy data |
| R3 | No time.sleep() in experiment code | psy-exp-coder | Blocks event loop, Escape unresponsive |
| R4 | No event.getKeys(maxWait=...) | psy-exp-coder | Blocks event loop |
| R5 | No data saved only at experiment end | psy-exp-coder | Crash = all data lost |
| R6 | No silent filling of [MISSING] values | psy-exp-designer | Every gap must be resolved by asking user or offering flagged default |
| R7 | No Chinese/CJK text without explicit font | psy-exp-coder | PsychoPy default font lacks CJK glyphs; text renders as tofu (□□□) |
| R8 | No skipping paradigm Must-Confirm items | psy-exp-designer | Unconfirmed items produce broken experiments |
| R9 | No rt_onset omitted on response windows | psy-exp-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 |
| R11 | No analysis method recommendation without 12-dimension comparison | psy-ana-designer | Unexamined method choice risks statistical validity |
| R12 | No analysis code without seed + exclusion log + effect size | psy-ana-coder | Missing elements break reproducibility |
| R13 | No analysis script delivery without session info output | psy-ana-coder | Non-reproducible without environment capture |
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
Experiment Review Modes (psy-exp-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) |
Analysis Review Modes (psy-ana-reviewer)
| Mode | Input | Maximum label |
|---|---|---|
analysis-audit | Complete analysis script + data | ready_for_publication |
plan-review | Analysis config YAML | analysis_plan_ready |
triage-only | Research question | None (missing-info list only) |
blocked | Insufficient input | None |
Readiness Labels
| Label | Pipeline | Meaning |
|---|---|---|
ready_for_collection | Experiment | Zero Critical + zero Major — can collect data |
ready_for_publication | Analysis | Zero Critical + zero Major — reproducible and complete |
ready_after_minor_fixes | Both | Only Minor issues remain |
not_ready_for_collection | Experiment | Critical or Major issues exist — do NOT collect |
not_ready | Analysis | Critical or Major issues exist |
pre_code_ready | Experiment | Design complete, ready for code generation |
analysis_plan_ready | Analysis | Analysis design complete, ready for code generation |
blocked | Both | Input insufficient for any review |
Severity Classification
| Severity | Definition | Can proceed? |
|---|---|---|
| Critical | Invalidates all data; must fix before any collection | No — fix before any data collection or publication |
| Major | Degrades data quality; fix before formal collection | No — fix before formal data collection (exp) or publication (ana) |
| Minor | Does not affect data quality; fix when convenient | Yes — fix when convenient |
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 Analysis, Variants, References, 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) — Full Programming-Layer Spec
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 |
Analysis Platform API Quick Reference
| Dimension | R | Python |
|---|---|---|
| Data import | readr::read_csv() | pandas.read_csv() |
| Filtering | dplyr::filter() | df[df['col'] > x] |
| Grouped stats | group_by() %>% summarise() | df.groupby().agg() |
| Paired t-test | t.test(paired=TRUE) | scipy.stats.ttest_rel() |
| Mixed model | lme4::lmer() | statsmodels.MixedLM() |
| GLMM (binomial) | lme4::glmer(family=binomial) | statsmodels.Logit() / pymer4 |
| Effect size | effectsize::cohens_d() / repeated_measures_d() | pingouin.compute_effsize() |
| Post-hoc | emmeans::emmeans() + pairs() | statsmodels.stats.multicomp |
| Visualization | ggplot2 + ggrain | matplotlib + seaborn |
| Reproducibility | set.seed() + sessionInfo() | np.random.seed() + sys.version |
Inter-Skill Communication Protocol
Experiment Pipeline
psy-exp-designer → psy-exp-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
Analysis Pipeline
Designer → Coder:
- Artifact:
analysis_config.yaml(saved to working directory) - Precondition: Gate 5 passed (user confirmed full Analysis Decision Registry)
- Coder's duty: Phase 0 validate config → confirm language (R/Python) → preview plan → generate code → deliver
Coder → Reviewer:
- Artifact: Generated analysis script (
analysis.R/.py) + report (.Rmd/.ipynb) - Precondition: Coder's 10-item Quality Gate passed
- Reviewer's duty: Intake → detect platform → Gate 0 grep scan → 5-dimension audit → output graded report + readiness label + recovery path
Shared Artifacts
| Artifact | Producer | Consumer | Format |
|---|---|---|---|
| Experiment config YAML | psy-exp-designer | psy-exp-coder | .yaml (internal) |
| Condition files | psy-exp-designer | psy-exp-coder | .xlsx / .csv |
| Experiment code | psy-exp-coder | psy-exp-reviewer | .py / .js / .m |
| Experiment README | psy-exp-coder | psy-exp-reviewer | .md |
| Analysis config YAML | psy-ana-designer | psy-ana-coder | .yaml (saved to disk) |
| Analysis script | psy-ana-coder | psy-ana-reviewer | .R / .py |
| Analysis report | psy-ana-coder | psy-ana-reviewer | .Rmd / .ipynb |
| Audit report | Both Reviewers | User | Markdown (graded + readiness label) |
Code Output Specification
Experiment Deliverables
| 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 |
Analysis Deliverables
| File | Format | Content |
|---|---|---|
| Analysis script | .R / .py | Config-driven, 12-step structure, seed + exclusion log + effect sizes + session info |
| Analysis report | .Rmd / .ipynb | Exclusion summary, descriptive stats, model results, figures, environment info |
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
│ │
│ │ # === Experiment Pipeline ===
│ ├── psy-exp-designer/ ← ① Experiment design
│ │ ├── SKILL.md ← 5-phase workflow + red lines
│ │ ├── README.md
│ │ ├── paradigms/ ← 38 paradigm reference files
│ │ └── references/ ← config-schema, timing, data-recording
│ ├── psy-exp-coder/ ← ② Experiment code generation
│ │ ├── SKILL.md ← 4-layer arch + 9-item gate
│ │ ├── README.md
│ │ ├── psychopy/ ← PsychoPy (full auto)
│ │ ├── jspsych/ ← jsPsych
│ │ └── psychtoolbox/ ← PTB
│ ├── psy-exp-reviewer/ ← ③ Experiment audit
│ │ ├── SKILL.md ← 5 review modes + platform-aware audit
│ │ └── README.md
│ │
│ │ # === Analysis Pipeline ===
│ ├── psy-ana-designer/ ← ④ Analysis design
│ │ ├── SKILL.md ← 5-phase progressive + 12-dimension comparison
│ │ ├── README.md
│ │ ├── methods/ ← 60 analysis method references
│ │ └── plots/ ← 48 chart type references
│ ├── psy-ana-coder/ ← ⑤ Analysis code generation
│ │ ├── SKILL.md ← 12-step script + R↔Python mapping
│ │ ├── README.md
│ │ ├── r/ ← R platform (spec/mapping/checklist/demo)
│ │ └── python/ ← Python platform (spec/mapping/checklist/demo)
│ └── psy-ana-reviewer/ ← ⑥ Analysis audit
│ ├── SKILL.md ← 4 review modes + reproducibility scoring
│ ├── README.md
│ ├── r/checklist/ ← R audit checklist
│ └── python/checklist/ ← Python audit checklist
├── 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
- Quick R/Python stats questions: Answer directly; don't invoke the full analysis pipeline
- General Python/JavaScript/MATLAB/R questions: Answer directly
- Non-experiment programming tasks: Not in scope
- Data analysis without experiment context: The analysis pipeline CAN handle standalone data — psy-ana-designer will manually collect experiment information if no config YAML exists
Related skills
- Downloads
- Security audit
- Review
- Last updated
- 1mo ago
- Current version
- v1.3.0
- License
- MIT-0