Wp Performance Review
elvismdev/claude-wordpress-skills
WordPress performance code review and optimization analysis.
Agent skill
Cjms Numerical Experiments
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when designing the numerical experiments and 算例 of a 《中国管理科学》 (Chinese Journal of Management Science) manuscript — grounded parameter calibration, an experiment matrix…
Install Cjms Numerical Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cjms-numerical-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cjms-numerical-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/Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments .claude/skills/cjms-numerical-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 "cjms-numerical-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments into .claude/skills/cjms-numerical-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cjms-numerical-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/Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-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 cjms-numerical-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cjms-numerical-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/Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments .agents/skills/cjms-numerical-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 "cjms-numerical-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments into .agents/skills/cjms-numerical-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cjms-numerical-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 cjms-numerical-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cjms-numerical-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/Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments .cursor/skills/cjms-numerical-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 "cjms-numerical-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments into .cursor/skills/cjms-numerical-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cjms-numerical-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 Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-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 cjms-numerical-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cjms-numerical-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/Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments .gemini/skills/cjms-numerical-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 "cjms-numerical-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments into .gemini/skills/cjms-numerical-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cjms-numerical-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 cjms-numerical-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 cjms-numerical-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/Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments .github/skills/cjms-numerical-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 "cjms-numerical-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments into .github/skills/cjms-numerical-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cjms-numerical-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 cjms-numerical-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 cjms-numerical-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/Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments .opencode/skills/cjms-numerical-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 "cjms-numerical-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments into .opencode/skills/cjms-numerical-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cjms-numerical-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
cjms-numerical-experiments- GitHub stars
- 1.2k
- Token cost
- ~595 tokens
- SKILL.md length
- 80 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when designing the numerical experiments and 算例 of a 《中国管理科学》 (Chinese Journal of Management Science) manuscript — grounded parameter calibration, an experiment matrix…
- Works in 4 steps: 有效性：新方法 vs 基线（衔接 cjms-solution-algorithm… → 敏感性：核心参数逐一扫区间，其余固定在基准值；关键交互参数做双向网格。 → 边界：找到方法失效或优势逆转的参数区域——审稿人最信任报告自身边界的论文。 → …
- Designing the numerical experiments and 算例 of a 《中国管理科学》 (Chinese Journal of Management Science) manuscript — grounded parameter calibration
- SKILL.md covers 触发时机, 核心：算例是论证，不是演示, 参数标定的三个合法来源 and 实验矩阵设计, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Cjms Numerical Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing the numerical experiments and 算例 of a 《中国管理科学》 (Chinese Journal of Management Science) manuscript — grounded parameter calibration, an experiment matrix, sensitivity analysis, and mechanism-level reading of results. For simulation and case computation; real-data method validation belongs to cjms-empirical-validation.
Its SKILL.md is about 600 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 Business, Finance & HR, covering Performance reviews. 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
- Designing the numerical experiments and 算例 of a 《中国管理科学》 (Chinese Journal of Management Science) manuscript — grounded parameter calibration
- An experiment matrix
- Sensitivity analysis
- Mechanism-level reading of results
Example prompts
- “/cjms-numerical-experiments”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- 有效性：新方法 vs 基线（衔接 cjms-solution-algorithm 的对比设计），报解质量与时间。
- 敏感性：核心参数逐一扫区间，其余固定在基准值；关键交互参数做双向网格。
- 边界：找到方法失效或优势逆转的参数区域——审稿人最信任报告自身边界的论文。
- 情境还原：至少一个贴近真实规模/取值的算例，支撑管理启示。
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
Cjms Numerical Experiments loads about 595 tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 80 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). 80 words, ~595 tokens.
Download SKILL.mdSave it as
.claude/skills/cjms-numerical-experiments/SKILL.md (or your agent's skills folder).- name
- cjms-numerical-experiments
- description
- Use when designing the numerical experiments and 算例 of a 《中国管理科学》 (Chinese Journal of Management Science) manuscript — grounded parameter calibration, an experiment matrix, sensitivity analysis, and mechanism-level reading of results. For simulation and case computation; real-data method validation belongs to cjms-empirical-validation.
数值实验与算例分析（cjms-numerical-experiments）
触发时机
- 只有一组参数、一张图，审稿说"数值实验单薄"
- 参数取值说不出来源，被问"为什么 λ=0.5"
- 结果只描述曲线走向，没有机制解释与管理含义
核心：算例是论证，不是演示
本刊的应用建模传统里，算例承担双重责任：验证方法性质（收敛、优势、边界）+ 把抽象结论翻译回管理情境。一组"跑通了"的数字不构成算例分析。
参数标定的三个合法来源
| 来源 | 做法 | 示例做法 |
|---|---|---|
| 真实场景 | 企业/行业公开数据折算 | 用上市公司年报或行业协会统计折算成本参数 |
| 已发表文献 | 沿用同型研究的参数区间并引用 | 引用文献算例并说明调整项 |
| 制度事实 | 政策文件、市场规则中的显性数字 | 手续费率、碳配额基准线 |
拍脑袋参数只允许出现在"结构性质与取值无关"已被证明的场合，且需声明。教学示意数字必须标注"示意"，不得伪装成标定值。
实验矩阵设计
按"要回答的问题"组织实验，而非按"能画的图"：
- 有效性：新方法 vs 基线（衔接
cjms-solution-algorithm的对比设计），报解质量与时间。 - 敏感性：核心参数逐一扫区间，其余固定在基准值；关键交互参数做双向网格。
- 边界：找到方法失效或优势逆转的参数区域——审稿人最信任报告自身边界的论文。
- 情境还原：至少一个贴近真实规模/取值的算例，支撑管理启示。
随机实验固定种子并报告重复次数与均值±标准差；实验环境（CPU、内存、软件版本）在脚注或表注写明。
从结果到机制的写法
每个实验小节按三句式收尾：现象（曲线/表格显示什么）→ 机制（模型里哪股力量导致）→ 含义（对决策者意味着什么）。只有第一句的段落是图注，不是分析。
自检清单
- 每个参数能指认三类来源之一，或已声明为示意
- 实验矩阵覆盖有效性/敏感性/边界/情境还原四类
- 随机实验有种子、重复次数与离散度报告
- 每个实验有机制解释，不止现象描述
- 报告了方法失效或优势逆转的边界区域
- 实验环境与运行时间可复现
本刊算例节的外审期待
| 退稿信号（审稿常用语） | 根因 | 本刊期望的修法 |
|---|---|---|
| "数值实验不够充分" | 只有有效性对比，缺敏感性与边界 | 按四类实验矩阵补齐 |
| "参数设置缺乏依据" | 标定来源缺失 | 逐参数注来源；示意值明示"示意" |
| "结论的一般性存疑" | 实验只在窄参数带内做 | 扫到结论反转处，报告边界 |
| "图表多但分析少" | 现象描述堆积 | 每个实验补机制句与含义句 |
| "实验规模与实际差距大" | 玩具算例 | 补一个真实规模的情境还原算例 |
微型走查：敏感性矩阵的组织
沿用应急预置虚构稿件，敏感性节的实验矩阵（示意数字仅作演示）：
E1 有效性：CCG-C vs 基线（见算法节），主表
E2 单参数扫：预算 ∈ [400, 1200] 万元，步长 100 —— 缺货惩罚拐点出现
在 640 万元附近 → 机制：覆盖率约束由松变紧 → 含义：预算低于拐点时
增仓不如提额
E3 双参数网格：Wasserstein 半径 × 需求相关系数，热力图 —— 高相关 +
大半径区域鲁棒解退化为均匀预置 → 报告为方法边界
E4 情境还原：以东南沿海某省 87 个县、14 次历史台风标定 —— 支撑启示节
的"预算-覆盖率"参照区间写法要点：E2 的"拐点"句式（现象→机制→含义三连）是本刊算例分析的标准动作；E3 主动报告退化区域，抢在审稿人前面画出适用边界。
反模式
- "一组参数打天下"：所有结论出自单一参数点
- 敏感性分析只扫不解释，八张图无一句机制
- 参数区间恰好避开结论反转的区域
- 与真实情境规模差几个量级的"玩具算例"支撑宏大启示
- 重复实验不报离散度，把偶然优势当稳定结论
输出格式
【参数标定】<参数→来源> × n（示意项已标注）
【实验矩阵】有效性<…> 敏感性<…> 边界<…> 情境还原<…>
【机制解读】<实验→现象→机制→含义> × n
【边界发现】<方法失效/逆转区域>
【下一步】cjms-managerial-insights© 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 Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Cjms Numerical 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 |
|---|---|---|---|---|---|---|
| Cjms Numerical Experiments this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~595 | Automated safety check: Pass | MIT | |
| Wp Performance Reviewelvismdev/claude-wordpress-skills | 235 | 1 repos | ~4.5k | Automated safety check: Pass | MIT | |
| Align Humanagentscope-ai/OpenJudge | 870 | — | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| Run Mv Hoi Reconstructionnvidia-isaac/video_to_data | 856 | — | ~1.5k | Automated safety check: Pass | Custom licence | |
| Company Analysiszhu1090093659/dsh-trading | 234 | — | ~4.2k | Automated safety check: Pass | Custom licence | |
| Windbg Diagnostic Methodmicrosoft/win-dev-skills | 465 | — | ~1.9k | Automated safety check: Pass | MIT |
Similar skills
Align Human
agentscope-ai/OpenJudge
A skill your agent uses when the user has a judge/grader and human-labeled data, and wants to measure how well the judge agrees with humans, detect systematic biases, determine whether automatic…
Run Mv Hoi Reconstruction
nvidia-isaac/video_to_data
Run and validate the repository-local multi-view camera calibration and human-object reconstruction pipelines.
Company Analysis
zhu1090093659/dsh-trading
A skill your agent uses when the user wants to analyze a listed company, stock, business, or investment target; challenge or revise an existing company report; compare A/H or primary-listing/ADR…
- Official
Windbg Diagnostic Method
microsoft/win-dev-skills
Use with every WinDbg plugin investigation to apply evidence-first reasoning, confidence calibration, contrarian review, structured reporting, and deterministic validation.
AI Index
mizchi/skills
Method and tooling for measuring how AI-generated a piece of prose reads, in Japanese or English.
More from brycewang-stanford/Awesome-Journal-Skills
All 2,387 skills in this repoAaag Data Analysis
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when running and reporting the analysis for an Annals of the American Association of Geographers manuscript — spatial statistics and modeling, remote-sensing accuracy, or…
Aaag Literature Positioning
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when positioning an Annals of the American Association of Geographers manuscript in the literature — engaging geographic scholarship across the relevant area and the…
Aaag Rebuttal
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when responding to an Annals of the American Association of Geographers decision letter (major/minor revision) — building a point-by-point response to the subject editor and…
Aaag Research Design
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when defending the research design of an Annals of the American Association of Geographers manuscript — spatial/quantitative analysis and GIScience, remote-sensing and…
Aaag Review Process
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when you need to understand how the Annals of the American Association of Geographers evaluates a manuscript — double-anonymous review routed through a subject editor by…
Aaag Submission
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when running the final pre-submission preflight for the Annals of the American Association of Geographers via ScholarOne Manuscripts — area/article-type selection…
Related
Categories
Questions about Cjms Numerical Experiments
What does Cjms Numerical Experiments do?
A skill your agent uses when designing the numerical experiments and 算例 of a 《中国管理科学》 (Chinese Journal of Management Science) manuscript — grounded parameter calibration, an experiment matrix…. Cjms Numerical Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing the numerical experiments and 算例 of a 《中国管理科学》 (Chinese Journal of Management Science) manuscript — grounded parameter calibration, an experiment matrix, sensitivity analysis, and mechanism-level reading of results.
When should I use Cjms Numerical Experiments?
Cjms Numerical Experiments fits situations like: designing the numerical experiments and 算例 of a 《中国管理科学》 (Chinese Journal of Management Science) manuscript — grounded parameter calibration; an experiment matrix; sensitivity analysis; mechanism-level reading of results.
How do I install Cjms Numerical Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cjms-numerical-experiments -a claude-code`. Or copy the skill folder (Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/cjms-numerical-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Cjms Numerical Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cjms-numerical-experiments -a codex`. Or copy the skill folder (Chinese-Journal-of-Management-Science-Skills/skills/cjms-numerical-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/cjms-numerical-experiments in your project. Codex loads it when a task matches its description.
Can I use Cjms Numerical 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 cjms-numerical-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/cjms-numerical-experiments, .gemini/skills/cjms-numerical-experiments, .github/skills/cjms-numerical-experiments and .opencode/skills/cjms-numerical-experiments in your project.
What does Cjms Numerical Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Cjms Numerical Experiments is instructions for the agent only.
Does Cjms Numerical 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 Cjms Numerical 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 Cjms Numerical Experiments use?
Cjms Numerical 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 Cjms Numerical Experiments use?
About 595 tokens (SKILL.md is roughly 2.4k 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 Cjms Numerical Experiments?
Skills that share tags, products or a category with Cjms Numerical Experiments: Wp Performance Review (elvismdev/claude-wordpress-skills, 235 stars), Align Human (agentscope-ai/OpenJudge, 870 stars), Run Mv Hoi Reconstruction (nvidia-isaac/video_to_data, 856 stars) and Company Analysis (zhu1090093659/dsh-trading, 234 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Cjms Numerical Experiments?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,228 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.