Scientific Critical Thinking
weapp-tailwindcss/weapp-tailwindcss
Evaluate research rigor. An agent skill from weapp-tailwindcss/weapp-tailwindcss.
Review and score experiment plans produced by Claude Code. An agent skill from appleweiping/WEIPING_WIKI.
Install Aris Experiment Plan
$ npx skills add appleweiping/WEIPING_WIKI --skill aris-experiment-plan -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install appleweiping/WEIPING_WIKI aris-experiment-plan --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/appleweiping/WEIPING_WIKI.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/aris-experiment-plan .claude/skills/aris-experiment-plan && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "aris-experiment-plan" agent skill from https://github.com/appleweiping/WEIPING_WIKI/tree/main/.codex/skills/aris-experiment-plan into .claude/skills/aris-experiment-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aris-experiment-plan", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/appleweiping/WEIPING_WIKI/tree/main/.codex/skills/aris-experiment-planType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add appleweiping/WEIPING_WIKI --skill aris-experiment-plan -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install appleweiping/WEIPING_WIKI aris-experiment-plan --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/appleweiping/WEIPING_WIKI.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.codex/skills/aris-experiment-plan .agents/skills/aris-experiment-plan && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "aris-experiment-plan" agent skill from https://github.com/appleweiping/WEIPING_WIKI/tree/main/.codex/skills/aris-experiment-plan into .agents/skills/aris-experiment-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aris-experiment-plan", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add appleweiping/WEIPING_WIKI --skill aris-experiment-plan -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install appleweiping/WEIPING_WIKI aris-experiment-plan --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/appleweiping/WEIPING_WIKI.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.codex/skills/aris-experiment-plan .cursor/skills/aris-experiment-plan && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "aris-experiment-plan" agent skill from https://github.com/appleweiping/WEIPING_WIKI/tree/main/.codex/skills/aris-experiment-plan into .cursor/skills/aris-experiment-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aris-experiment-plan", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/appleweiping/WEIPING_WIKI.git --path .codex/skills/aris-experiment-plan--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add appleweiping/WEIPING_WIKI --skill aris-experiment-plan -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install appleweiping/WEIPING_WIKI aris-experiment-plan --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/appleweiping/WEIPING_WIKI.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.codex/skills/aris-experiment-plan .gemini/skills/aris-experiment-plan && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "aris-experiment-plan" agent skill from https://github.com/appleweiping/WEIPING_WIKI/tree/main/.codex/skills/aris-experiment-plan into .gemini/skills/aris-experiment-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aris-experiment-plan", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install appleweiping/WEIPING_WIKI aris-experiment-planInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add appleweiping/WEIPING_WIKI --skill aris-experiment-plan -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/appleweiping/WEIPING_WIKI.git skills-src && mkdir -p .github/skills && cp -r skills-src/.codex/skills/aris-experiment-plan .github/skills/aris-experiment-plan && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "aris-experiment-plan" agent skill from https://github.com/appleweiping/WEIPING_WIKI/tree/main/.codex/skills/aris-experiment-plan into .github/skills/aris-experiment-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aris-experiment-plan", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add appleweiping/WEIPING_WIKI --skill aris-experiment-plan -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install appleweiping/WEIPING_WIKI aris-experiment-plan --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/appleweiping/WEIPING_WIKI.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.codex/skills/aris-experiment-plan .opencode/skills/aris-experiment-plan && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "aris-experiment-plan" agent skill from https://github.com/appleweiping/WEIPING_WIKI/tree/main/.codex/skills/aris-experiment-plan into .opencode/skills/aris-experiment-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aris-experiment-plan", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
aris-experiment-plan- GitHub stars
- 119
- Token cost
- ~1.4k tokens
- SKILL.md length
- 619 words
- Files
- 1
- Skills in repo
- 51
- Repo updated
- First seen
- Licence
- MIT
At a glance
Review and score experiment plans produced by Claude Code. An agent skill from appleweiping/WEIPING_WIKI.
- Works in 4 steps: Baseline Completeness Check → Decision Gate Quality → Compute Feasibility → …
- Tasks that involve Experimental design
- SKILL.md covers Your Mandate, Phase 1: Baseline Completeness…, Phase 2: Decision Gate Quality and Phase 3: Compute Feasibility, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Aris Experiment Plan is an agent skill from appleweiping/WEIPING_WIKI. Review and score experiment plans produced by Claude Code. Evaluate evidence quality, rigor, decision gates, feasibility, and paper potential. Triggers: "review experiment plan", "audit plan", "score plan", "check my experiment design", "is this plan rigorous enough"
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science, covering Experimental design. The repository describes itself as: knowledge base managed with an LLM workflow. The licence is MIT.
When your agent uses it
- Tasks that involve Experimental design
Example prompts
- “review experiment plan”
- “audit plan”
- “score plan”
- “/aris-experiment-plan”
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 76fdc42. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Aris Experiment Plan loads about 1.4k tokens when it runs. Until then it costs about 72 tokens; SKILL.md has 619 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from appleweiping/WEIPING_WIKI at commit 76fdc42, republished under its MIT licence (© appleweiping). 619 words, ~1,430 tokens.
Download SKILL.mdSave it as
.claude/skills/aris-experiment-plan/SKILL.md (or your agent's skills folder).- name
- aris-experiment-plan
- description
- Review and score experiment plans produced by Claude Code. Evaluate evidence quality, rigor, decision gates, feasibility, and paper potential. Triggers: "review experiment plan", "audit plan", "score plan", "check my experiment design", "is this plan rigorous enough"
- role
- auditor
- stage
- experiment-plan
ARIS Experiment-Plan Auditor
You are the AUDITOR for experiment plans. You review the experimental design produced by the implementation agent. You check whether the plan, if executed perfectly, would produce publishable evidence. You do NOT design experiments — you judge them.
Your Mandate
- A plan that passes your audit should survive peer review methodology critique
- Catch missing baselines, weak gates, and unrealistic compute assumptions NOW
- Every "proceed" means: "If they follow this plan exactly, the results are trustworthy"
Phase 1: Baseline Completeness Check
Required Baselines Checklist
- Random baseline included (sanity check)
- Current SOTA baseline identified and included
- At least one "simple but strong" baseline (e.g., well-tuned linear model)
- Ablation baselines for each proposed component
- Total baseline count >= 3 (excluding ablations)
Baseline Quality Criteria
| Criterion | Pass/Fail | Notes |
|---|---|---|
| Baselines use same data splits | ||
| Baselines use same preprocessing | ||
| Baselines are tuned (not strawman) | ||
| Baseline implementations are cited/verified | ||
| Compute budget for baselines is allocated |
Hard rule: If baselines < 3 or any baseline is a strawman → automatic "iterate" verdict.
Seed and Repetition Requirements
- Number of random seeds specified (minimum: 5 for pilot, 20 for paper results)
- Seed selection strategy defined (sequential from 0, or pre-registered list)
- Variance reporting method specified (std dev, CI, IQR)
- Seeds apply to ALL methods equally (not just proposed method)
Hard rule: If seeds < 20 for paper-targeted experiments → flag as insufficient.
Phase 2: Decision Gate Quality
For each decision gate in the plan, verify:
| Gate | Metric | Threshold | Action if Failed | Verdict |
|---|---|---|---|---|
| Gate N | [specific metric] | [numeric threshold] | [specific action] | Pass/Fail |
Gate Quality Criteria
- Every gate has a NUMERIC threshold (not "significant improvement")
- Every gate specifies what happens on failure (pivot/iterate/stop)
- Gates are ordered — later gates depend on earlier gates passing
- At least one early "kill gate" (cheap experiment that validates core assumption)
- No gate relies solely on visual inspection or subjective judgment
Common Gate Failures
- "If results look promising" → FAIL (not numeric)
- "If better than baseline" → FAIL (by how much? significance level?)
- "If compute allows" → FAIL (compute should be pre-allocated)
- Gate threshold set at exactly SOTA → SUSPICIOUS (should exceed by margin)
Hard rule: If any gate lacks a numeric threshold → automatic "iterate" verdict.
Phase 3: Compute Feasibility
Resource Audit
| Resource | Required | Available | Margin | Status |
|---|---|---|---|---|
| GPU hours | OK/Tight/Infeasible | |||
| Storage | OK/Tight/Infeasible | |||
| Wall-clock time | OK/Tight/Infeasible | |||
| API costs (if any) | OK/Tight/Infeasible |
Show full SKILL.md (244 more words)Show less
Feasibility Checks
- Total compute estimated for ALL runs (method * baselines * seeds * gates)
- 30% buffer included for failed runs and debugging
- Longest single run fits within available wall-clock
- Data download/preprocessing time accounted for
- Checkpoint strategy defined (can resume from failure)
Hard rule: If any resource is "Infeasible" → automatic "pivot" verdict.
Phase 4: Score and Verdict
Scoring
| Dimension | Score | Justification |
|---|---|---|
| Evidence Quality | /10 | Will the results be believed? |
| Rigor | /10 | Are comparisons fair and complete? |
| Gates | /10 | Will bad directions be caught early? |
| Feasibility | /10 | Can this actually be executed? |
| Paper Potential | /10 | Does this plan produce a publishable story? |
Scoring Rubric
- 1-3: Plan has structural flaws. Cannot produce trustworthy results.
- 4-5: Plan is incomplete. Key elements missing.
- 6-7: Plan is workable but has gaps that could weaken the paper.
- 8-9: Plan is solid. Minor suggestions only.
- 10: Plan is exemplary. Would use as a template.
Decision Matrix
| Condition | Verdict |
|---|---|
| All dimensions >= 7, all hard rules pass | PROCEED |
| Any hard rule violated | ITERATE (fix specific issue) |
| Any dimension <= 3 | PIVOT (plan needs fundamental redesign) |
| Average >= 7 but one dimension is 5-6 | ITERATE (targeted fix) |
| Average < 5 | PIVOT |
Verdict Format
VERDICT: [PROCEED / ITERATE / PIVOT]
CONFIDENCE: [Low / Medium / High]
SCORES: E={evidence} R={rigor} G={gates} F={feasibility} P={paper} AVG={avg}
HARD RULE VIOLATIONS: [list or "None"]
BLOCKING ISSUE: [one-line summary or "None"]
NEXT ACTION: [specific fix the implementation agent should make]Interaction Rules
- Never design experiments. Your job is to judge plans, not create them.
- Be specific: "Gate 3 needs a threshold" not "gates need work."
- If a plan is genuinely good, say so. Don't manufacture criticism.
- Track iteration count. If a plan has been through 3+ iterations without passing, recommend stepping back to re-examine the research question.
© appleweiping, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .codex/skills/aris-experiment-plan of appleweiping/WEIPING_WIKI.
Open the folder on GitHubat commit 76fdc42
Compare with similar skills
Aris Experiment Plan next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Aris Experiment Plan this skillappleweiping/WEIPING_WIKI | 119 | — | ~1.4k | Automated safety check: Pass | MIT | |
| Scientific Critical Thinkingweapp-tailwindcss/weapp-tailwindcss | 1.9k | 22 repos | ~5.9k | Automated safety check: Notes | MIT | |
| Benchmark Paper TemplateHKUSTDial/Supervisor-Skills | 8.8k | — | ~2.8k | Automated safety check: Pass | CC-BY-4.0 | |
| Claim-Driven Experiment PlannerzjYao36/Auto-Research-Refine | 128 | 6 repos | ~2.3k | Automated safety check: Notes | None | |
| Research Refine PipelinezjYao36/Auto-Research-Refine | 128 | 5 repos | ~1.4k | Automated safety check: Notes | None | |
| Metabolic Study Planneraiming-lab/AutoResearchClaw | 15k | — | ~1.9k | Automated safety check: Pass | MIT |
Similar skills
Benchmark Paper Template
HKUSTDial/Supervisor-Skills
Structures benchmark and evaluation papers around five pillars, with a completeness audit, an Introduction logic chain, a section skeleton and a pre-submission checklist.
Claim-Driven Experiment Planner
zjYao36/Auto-Research-Refine
Turns a refined research proposal into a claim-to-evidence-to-run-order roadmap instead of a sprawling benchmark wishlist.
Research Refine Pipeline
zjYao36/Auto-Research-Refine
Chains research-refine and experiment-plan to turn a vague research direction into a focused proposal and a claim-driven experiment roadmap.
Metabolic Study Planner
aiming-lab/AutoResearchClaw
Turns a broad metabolic modelling topic into a concrete, paper-shaped plan with organism, model, perturbations, metrics and figures before any FBA code is written.
Analytical Method Validation Planner
K-Dense-AI/scientific-agent-skills
Plans, runs, and documents analytical method validation, verification, or transfer studies under ICH Q2(R2)/Q14, USP, ICH M10, CLSI EP, or ISO/IEC 17025.
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Related
Categories
Questions about Aris Experiment Plan
What does Aris Experiment Plan do?
Review and score experiment plans produced by Claude Code. An agent skill from appleweiping/WEIPING_WIKI. Aris Experiment Plan is an agent skill from appleweiping/WEIPING_WIKI. Review and score experiment plans produced by Claude Code.
When should I use Aris Experiment Plan?
Aris Experiment Plan fits situations like: tasks that involve Experimental design.
How do I install Aris Experiment Plan in Claude Code?
Run `npx skills add appleweiping/WEIPING_WIKI --skill aris-experiment-plan -a claude-code`. Or copy the skill folder (.codex/skills/aris-experiment-plan in appleweiping/WEIPING_WIKI) into .claude/skills/aris-experiment-plan in your project. Claude Code loads it when a task matches its description.
How do I install Aris Experiment Plan in Codex?
Run `npx skills add appleweiping/WEIPING_WIKI --skill aris-experiment-plan -a codex`. Or copy the skill folder (.codex/skills/aris-experiment-plan in appleweiping/WEIPING_WIKI) into .agents/skills/aris-experiment-plan in your project. Codex loads it when a task matches its description.
Can I use Aris Experiment Plan in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add appleweiping/WEIPING_WIKI --skill aris-experiment-plan -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aris-experiment-plan, .gemini/skills/aris-experiment-plan, .github/skills/aris-experiment-plan and .opencode/skills/aris-experiment-plan in your project.
What does Aris Experiment Plan need to run?
SKILL.md names no scripts, command-line tools or credentials: Aris Experiment Plan is instructions for the agent only.
Does Aris Experiment Plan access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Aris Experiment Plan safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Aris Experiment Plan use?
Aris Experiment Plan is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Aris Experiment Plan use?
About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Aris Experiment Plan?
Skills that share tags, products or a category with Aris Experiment Plan: Scientific Critical Thinking (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars), Benchmark Paper Template (HKUSTDial/Supervisor-Skills, 8.8k stars), Claim-Driven Experiment Planner (zjYao36/Auto-Research-Refine, 128 stars) and Research Refine Pipeline (zjYao36/Auto-Research-Refine, 128 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Aris Experiment Plan?
appleweiping (a GitHub user) maintains it in appleweiping/WEIPING_WIKI, which has 119 GitHub stars. The repository holds 51 skills in this directory. The repository was last updated on August 26, 2026.
Source: appleweiping/WEIPING_WIKI on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.