Design Audit Against Rams' Principles
thedotmack/claude-mem
Audits a design against Dieter Rams' ten principles of good design, scores each with evidence, and hands off a make-plan prompt for a new, refined or redesigned outcome.
A skill your agent uses when designing or auditing the evaluation of an ASE (IEEE/ACM Automated Software Engineering) paper, covering real subject systems, fair runnable tool baselines, task-matched…
MITAuto-check passed
Install Ase Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ase-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ase-experiments --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/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/ASE-Skills/skills/ase-experiments .claude/skills/ase-experiments && 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 "ase-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ASE-Skills/skills/ase-experiments into .claude/skills/ase-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ase-experiments", 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/brycewang-stanford/Awesome-Journal-Skills/tree/main/ASE-Skills/skills/ase-experimentsType 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 brycewang-stanford/Awesome-Journal-Skills --skill ase-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ase-experiments --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/ASE-Skills/skills/ase-experiments .agents/skills/ase-experiments && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ase-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ASE-Skills/skills/ase-experiments into .agents/skills/ase-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ase-experiments", 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 brycewang-stanford/Awesome-Journal-Skills --skill ase-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ase-experiments --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/ASE-Skills/skills/ase-experiments .cursor/skills/ase-experiments && 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 "ase-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ASE-Skills/skills/ase-experiments into .cursor/skills/ase-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ase-experiments", 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/brycewang-stanford/Awesome-Journal-Skills.git --path ASE-Skills/skills/ase-experiments--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 brycewang-stanford/Awesome-Journal-Skills --skill ase-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ase-experiments --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/ASE-Skills/skills/ase-experiments .gemini/skills/ase-experiments && 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 "ase-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ASE-Skills/skills/ase-experiments into .gemini/skills/ase-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ase-experiments", 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 brycewang-stanford/Awesome-Journal-Skills ase-experimentsInstalls 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 brycewang-stanford/Awesome-Journal-Skills --skill ase-experiments -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/ASE-Skills/skills/ase-experiments .github/skills/ase-experiments && 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 "ase-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ASE-Skills/skills/ase-experiments into .github/skills/ase-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ase-experiments", 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 brycewang-stanford/Awesome-Journal-Skills --skill ase-experiments -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ase-experiments --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/ASE-Skills/skills/ase-experiments .opencode/skills/ase-experiments && 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 "ase-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ASE-Skills/skills/ase-experiments into .opencode/skills/ase-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ase-experiments", 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
ase-experiments- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 513 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when designing or auditing the evaluation of an ASE (IEEE/ACM Automated Software Engineering) paper, covering real subject systems, fair runnable tool baselines, task-matched…
- Auditing the evaluation of an ASE (IEEE/ACM Automated Software Engineering) paper
- SKILL.md covers Start from the claim shape, Real subject systems, Fair, runnable tool baselines and Ablations that isolate the…, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Covering real subject systems
What it does
Ase Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the evaluation of an ASE (IEEE/ACM Automated Software Engineering) paper, covering real subject systems, fair runnable tool baselines, task-matched effectiveness metrics, ablations that isolate a learned component, oracle and correctness validation, contamination-aware LLM handling, and provenance for mining.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- Auditing the evaluation of an ASE (IEEE/ACM Automated Software Engineering) paper
- Covering real subject systems
- Fair runnable tool baselines
- Task-matched effectiveness metrics
Example prompts
- “/ase-experiments”
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. 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
Ase Experiments loads about 1.3k tokens when it runs. Until then it costs about 89 tokens; SKILL.md has 513 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 brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 513 words, ~1,330 tokens.
Download SKILL.mdSave it as
.claude/skills/ase-experiments/SKILL.md (or your agent's skills folder).- name
- ase-experiments
- description
- Use when designing or auditing the evaluation of an ASE (IEEE/ACM Automated Software Engineering) paper, covering real subject systems, fair runnable tool baselines, task-matched effectiveness metrics, ablations that isolate a learned component, oracle and correctness validation, contamination-aware LLM handling, and provenance for mining.
ASE Experiments
Match the evidence to the automation's claim. ASE evaluations are judged on whether a tool or technique actually does what it claims on real subjects, compared fairly against the closest runnable automation. This is the axis reviewers weight most, and the one that most often becomes a Revision criterion.
Start from the claim shape
Different automations demand different evidence:
| Automation claim | Evidence that matches | Common failure |
|---|---|---|
| Detection (bugs, smells, vulnerabilities) | Precision/recall/F on real defects with a defined ground truth | Synthetic-only defects; unclear ground truth |
| Generation / synthesis (tests, code, patches) | Validity of the produced artifact (compiles, passes, holds the property) | Similarity-to-reference proxy instead of validity |
| Repair | Verified behavior change: re-run + oracle; assertion/spec preservation | "Plausible patch" without an overfitting check |
| Localization / ranking | Rank-based effectiveness on real faults vs. alternatives | Cherry-picked programs; one metric only |
| Scalability / performance | Real-system sizes, wall-clock with a fair config | Toy inputs; unequal baseline budget |
Real subject systems
- Use real software — open-source projects, real bug/defect datasets, real CI logs — not toy programs you constructed to make the tool look good.
- Report subject provenance: names, versions/commit SHAs, sizes, and the extraction date. Reviewers reproduce from this.
- Justify subject selection and disclose exclusions; self-selected subjects are the classic external-validity threat.
Fair, runnable tool baselines
- Compare against the closest runnable automation, configured at an equal, documented budget (time, iterations, tuning, seeds). ASE reviewers routinely rerun or scrutinize baselines.
- Pin baseline versions/commits and note reimplementation vs. original.
- If no tool baseline exists, construct a defensible non-trivial baseline (a static rewrite, a random or heuristic variant) rather than comparing only to "nothing."
Ablations that isolate the automation
If a learned or LLM component is involved, run an ablation that removes it and keeps the rest, so the marginal value of the design is visible. This is what defeats the "the model did it, not your technique" objection and keeps the paper ASE-shaped rather than ML-shaped.
Show full SKILL.md (200 more words)Show less
Oracles and correctness
- State the oracle explicitly: how do you know a generated test is meaningful, or a repair is correct? Re-execution, differential testing, formal checks, or human audit — name it.
- For repair/synthesis, guard against overfitting to the evaluation oracle (e.g., patches that pass the given tests but break behavior): report a held-out or manual correctness check.
Statistics and effect sizes
- Report effect sizes and dispersion (confidence intervals, non-parametric tests where appropriate), not just point estimates or a single accuracy number.
- For randomized techniques (search-based, sampling, LLM temperature > 0), report repeated runs with variance and fix/seed the randomness for the artifact.
Contamination-aware LLM handling
- Record model identifiers and dates; a model updated between runs invalidates comparisons.
- Consider training-data contamination: benchmarks the model may have seen inflate results — report on held-out or post-cutoff subjects where feasible, and say so.
- Cache raw model outputs so the artifact reproduces rather than re-samples a live API.
Mining and dataset provenance
- Pin repository SHAs, the corpus extraction date, query/filter criteria, and any labeling protocol with inter-rater agreement for manually coded data.
- Version the dataset and describe how to regenerate it; a package that needs live scraping re-samples a moving target.
Evaluation audit checklist
[Claim-evidence] each claim -> a matching metric on real subjects (not a proxy)
[Subjects] real, provenance-pinned, selection justified, exclusions disclosed
[Baselines] closest runnable tool, version pinned, equal documented budget
[Ablation] learned/LLM component isolated; marginal value of the design shown
[Oracle] correctness defined; overfitting-to-oracle checked
[Stats] effect sizes + dispersion; repeated runs for randomized methods
[LLM] model IDs/dates recorded; contamination considered; outputs cached
[Repro] provenance pinned; dataset/tool versioned for the artifactOutput format
[Automation claim] detection / generation / repair / localization / scalability
[Evidence match] metric(s) that fit the claim, on real subjects
[Baseline fairness] closest tool, budget parity, versions
[Ablation + oracle] learned-component ablation present; correctness oracle stated
[Threats] subject selection / oracle validity / baseline fairness / contamination — bounded how?© brycewang-stanford, 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 ASE-Skills/skills/ase-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Ase Experiments 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 |
|---|---|---|---|---|---|---|
| Ase Experiments this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Design Audit Against Rams' Principlesthedotmack/claude-mem | 98k | — | ~4.6k | Automated safety check: Pass | Apache-2.0 | |
| Experiment Auditwanshuiyin/Auto-claude-code-research-in-sleep | 17k | 1 repos | ~2.7k | Automated safety check: Notes | MIT | |
| Experiment Auditwanshuiyin/Auto-claude-code-research-in-sleep | 17k | — | ~3.2k | Automated safety check: Notes | MIT | |
| Experiment Designeralirezarezvani/claude-skills | 28k | 1 repos | ~783 | Automated safety check: Pass | MIT | |
| OpenClaw Design Auditopenclaw/clawhub | 9.5k | — | ~498 | Automated safety check: Pass | MIT |
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Questions about Ase Experiments
What does Ase Experiments do?
A skill your agent uses when designing or auditing the evaluation of an ASE (IEEE/ACM Automated Software Engineering) paper, covering real subject systems, fair runnable tool baselines, task-matched…. Ase Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the evaluation of an ASE (IEEE/ACM Automated Software Engineering) paper, covering real subject systems, fair runnable tool baselines, task-matched effectiveness metrics, ablations that isolate a learned component, oracle and correctness validation, contamination-aware LLM handling, and provenance for mining.
When should I use Ase Experiments?
Ase Experiments fits situations like: auditing the evaluation of an ASE (IEEE/ACM Automated Software Engineering) paper; covering real subject systems; fair runnable tool baselines; task-matched effectiveness metrics.
How do I install Ase Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ase-experiments -a claude-code`. Or copy the skill folder (ASE-Skills/skills/ase-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/ase-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Ase Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ase-experiments -a codex`. Or copy the skill folder (ASE-Skills/skills/ase-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/ase-experiments in your project. Codex loads it when a task matches its description.
Can I use Ase Experiments 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 brycewang-stanford/Awesome-Journal-Skills --skill ase-experiments -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ase-experiments, .gemini/skills/ase-experiments, .github/skills/ase-experiments and .opencode/skills/ase-experiments in your project.
What does Ase Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Ase Experiments is instructions for the agent only.
Does Ase Experiments 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 Ase Experiments 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 Ase Experiments use?
Ase Experiments 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 Ase Experiments use?
About 1.3k tokens (SKILL.md is roughly 5.3k 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 Ase Experiments?
Skills that share tags, products or a category with Ase Experiments: Design Audit Against Rams' Principles (thedotmack/claude-mem, 98k stars), Experiment Audit (wanshuiyin/Auto-claude-code-research-in-sleep, 17k stars), Experiment Audit (wanshuiyin/Auto-claude-code-research-in-sleep, 17k stars) and Experiment Designer (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Ase Experiments?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,219 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.