Agent skill

Jse Tju Algorithm Computation

by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills

A skill your agent uses when designing, reporting, or auditing an exact, decomposition, heuristic, simulation, or learning-based solution route for 《系统工程学报》 (Journal of Systems Engineering, Tianjin…

MITAuto-check passed

Install Jse Tju Algorithm Computation

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jse-tju-algorithm-computation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jse-tju-algorithm-computation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Journal-of-Systems-Engineering-Skills/skills/jse-tju-algorithm-computation .claude/skills/jse-tju-algorithm-computation && rm -rf skills-src

Use ~/.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/

Facts

Skill name
jse-tju-algorithm-computation
GitHub stars
1.2k
Token cost
~768 tokens
SKILL.md length
103 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when designing, reporting, or auditing an exact, decomposition, heuristic, simulation, or learning-based solution route for 《系统工程学报》 (Journal of Systems Engineering, Tianjin…

  • Works in 6 steps: 从结构推导算法 → 写可执行伪代码 → 给理论或诊断保证 → …
  • Auditing an exact
  • SKILL.md covers 触发时机, 输入诊断, 求解路线选择 and 处理步骤, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Jse Tju Algorithm Computation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing, reporting, or auditing an exact, decomposition, heuristic, simulation, or learning-based solution route for 《系统工程学报》 (Journal of Systems Engineering, Tianjin University), including pseudocode, convergence or complexity, baselines, ablations, parameter settings, computing environment, scalability, and reproducible computational evidence.

Its SKILL.md is about 770 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 an exact
  • Learning-based solution route for 《系统工程学报》 (Journal of Systems Engineering
  • Tianjin University)
  • Including pseudocode

Example prompts

  • “/jse-tju-algorithm-computation”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. 从结构推导算法
  2. 写可执行伪代码
  3. 给理论或诊断保证
  4. 设计基线
  5. 做消融与参数实验
  6. 报告规模和环境

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

Jse Tju Algorithm Computation loads about 768 tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 103 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~768

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). 103 words, ~768 tokens.

Download SKILL.mdSave it as .claude/skills/jse-tju-algorithm-computation/SKILL.md (or your agent's skills folder).
name
jse-tju-algorithm-computation
description
Use when designing, reporting, or auditing an exact, decomposition, heuristic, simulation, or learning-based solution route for 《系统工程学报》 (Journal of Systems Engineering, Tianjin University), including pseudocode, convergence or complexity, baselines, ablations, parameter settings, computing environment, scalability, and reproducible computational evidence.

《系统工程学报》算法与计算(jse-tju-algorithm-computation)

触发时机

当模型已定义但求解路线、算法增量或计算证据仍不完整时使用。算法必须回应系统结构带来的困难, 不能因为换用一个热门元启发式就自动成为贡献。本刊近年样本包含优化、网络、仿真和预测研究; 内容画像见 source-basis.md,可复现接口见 code/README.md。

输入诊断

提供数学模型或计算任务、输入输出、实例规模、结构性质、精度/时间目标、候选算法、已有代码与结果。 先判定:

  • 难点来自组合规模、非凸性、动态不确定、分布式信息还是仿真成本?
  • 是否存在可作为小规模真值的精确方法或解析解?
  • 新算法利用了哪项系统结构?
  • 输出用于解释机制、求最优策略、预测还是支持工程决策?
  • 失败、超时或不可行实例是否被保留?

没有明确计算任务时,不先写伪代码;模型若尚未闭合,返回 jse-tju-system-modeling。

求解路线选择

问题结构首选路线必须说明
小中规模线性/整数模型商用或开源求解器、精确算法最优间隙、时间限制、求解状态
可分结构Benders、列生成、拉格朗日或 ADMM分解依据、上下界、停止准则
动态/随机决策动态规划、近似 DP、滚动优化状态、情景、非预见性与误差
大规模组合问题启发式/元启发式可行性保持、基线、重复与统计
网络/动力系统数值积分、事件仿真、谱/迭代方法步长、稳定、初值和误差
数据驱动任务统计/机器学习模型数据切分、泄漏防控、强基线

复杂方法不是优先级;能用精确或标准方法回答问题时,不添加无必要的算法层。

处理步骤

1. 从结构推导算法

把模型结构与算法模块一一对应:耦合约束为何需要分解,网络稀疏性如何利用,动态状态如何更新, 异质主体如何并行。若模块删除后算法仍等同通用模板,谨慎声称算法创新。

2. 写可执行伪代码

列出输入、初始化、循环/递归、可行性修复、随机操作、终止条件和输出。符号与模型一致;每一步 能在实现中定位。不要用“更新解”“优化参数”掩盖关键过程。

3. 给理论或诊断保证

精确/分解方法报告有限收敛、界或最优性间隙;迭代方法报告收敛条件或经验残差;启发式无法给 全局保证时明确性质,并用小规模最优解、上下界和多次重复评价误差。

4. 设计基线

至少覆盖:简单决策规则、领域常用方法、最接近方法、可行时的小规模精确真值。统一数据、预算、 停止条件与硬件;不能让本方法获得更多时间或调参信息而不披露。

5. 做消融与参数实验

每个声称有贡献的模块至少一个消融。参数实验区分算法超参数与系统参数:前者检验稳定和调参成本, 后者解释系统机制。避免把超参数敏感性写成管理结论。

6. 报告规模和环境

列实例数、变量/约束/节点/时期规模、随机种子、重复次数、语言与版本、求解器与版本、CPU/GPU、 内存、时间限制、容差和并行设置。动态要求回查官方格式;计算环境本身按研究可复现性完整报告。

伪代码最小模板

text
Algorithm: [名称]
Input: instance I, system parameters θ, tolerance ε, budget B, seed s
Initialize: feasible state/solution x0; incumbent; bounds/residuals
while stopping rule is false:
    update the system state or subproblem
    generate and evaluate candidate decisions
    preserve/repair feasibility
    update incumbent, bounds, residuals, or model
return decision x*, objective/trajectory, status, diagnostics

计算证据矩阵

主张最低证据
解质量更高强基线、同预算、间隙/统计区间
速度更快多规模、同环境、时间与失败率
可扩展规模梯度、内存、超时边界
模块有效消融、交互消融、代价分析
结构有价值与不利用结构的算法比较
结果稳定多随机种子、分布、参数敏感性

微型示例

对动态应急配送,若提出“改进遗传算法”,需要说明滚动状态和公平约束如何进入编码、交叉与修复; 小规模与 MIP 最优解比较,大规模与滚动贪心和标准遗传算法同预算比较;报告中断强度、网络规模、 重复分布和超时。仅给一条收敛曲线不能支持优越性。

反模式

  • 以算法名称新、参数多或曲线平滑证明创新。
  • 基线过弱,或给本方法更多运行时间和调参机会。
  • 只报告平均值,不报告波动、失败和不可行率。
  • 伪代码与模型符号、实际实现不一致。
  • 用单一实例声称可扩展。
  • 不区分系统参数与算法超参数。

期刊专属拒稿风险

算法稿若不能解释系统结构为何要求该求解设计,会被视为通用算法套用;若只有计算改善而没有 系统级含义,也难以建立本刊专属性。算法证据与稿件类型的总体验证应交给 jse-tju-validation, 随机性和环境复现交给 jse-tju-robustness-reproducibility。

输出格式

text
【计算任务与结构难点】
【路线选择及被排除方案】
【算法输入—步骤—输出】
【收敛 / 复杂度 / 诊断保证】
【基线与公平预算】
【消融与参数设计】
【规模梯度与失败边界】
【计算环境和复现清单】
【系统级解释】
【最大拒稿风险】

© 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 Journal-of-Systems-Engineering-Skills/skills/jse-tju-algorithm-computation of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

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Questions about Jse Tju Algorithm Computation

What does Jse Tju Algorithm Computation do?

A skill your agent uses when designing, reporting, or auditing an exact, decomposition, heuristic, simulation, or learning-based solution route for 《系统工程学报》 (Journal of Systems Engineering, Tianjin…. Jse Tju Algorithm Computation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing, reporting, or auditing an exact, decomposition, heuristic, simulation, or learning-based solution route for 《系统工程学报》 (Journal of Systems Engineering, Tianjin University), including pseudocode, convergence or complexity, baselines, ablations, parameter settings, computing environment, scalability, and reproducible computational evidence.

When should I use Jse Tju Algorithm Computation?

Jse Tju Algorithm Computation fits situations like: auditing an exact; learning-based solution route for 《系统工程学报》 (Journal of Systems Engineering; tianjin University); including pseudocode.

How do I install Jse Tju Algorithm Computation in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jse-tju-algorithm-computation -a claude-code`. Or copy the skill folder (Journal-of-Systems-Engineering-Skills/skills/jse-tju-algorithm-computation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/jse-tju-algorithm-computation in your project. Claude Code loads it when a task matches its description.

How do I install Jse Tju Algorithm Computation in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jse-tju-algorithm-computation -a codex`. Or copy the skill folder (Journal-of-Systems-Engineering-Skills/skills/jse-tju-algorithm-computation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/jse-tju-algorithm-computation in your project. Codex loads it when a task matches its description.

Can I use Jse Tju Algorithm Computation 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 jse-tju-algorithm-computation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jse-tju-algorithm-computation, .gemini/skills/jse-tju-algorithm-computation, .github/skills/jse-tju-algorithm-computation and .opencode/skills/jse-tju-algorithm-computation in your project.

What does Jse Tju Algorithm Computation need to run?

SKILL.md names no scripts, command-line tools or credentials: Jse Tju Algorithm Computation is instructions for the agent only.

Does Jse Tju Algorithm Computation 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 Jse Tju Algorithm Computation 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 Jse Tju Algorithm Computation use?

Jse Tju Algorithm Computation 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 Jse Tju Algorithm Computation use?

About 768 tokens (SKILL.md is roughly 3.1k 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 Jse Tju Algorithm Computation?

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Who maintains Jse Tju Algorithm Computation?

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.