Academic Grill
Exekiel179/psyclaw
Stress-test an academic research question, proposal, study design, analysis plan, manuscript claim, review protocol, or AI research project through a one-question-at-a-time interview until its…
A skill your agent uses when the empirical identification strategy is the bottleneck for an Economic-Research manuscript — quasi-experimental designs (DID, IV, RDD, DML, event study).
Install Er Identification
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill er-identification -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills er-identification --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/Economic-Research-Journal-Skills/skills/er-identification .claude/skills/er-identification && 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 "er-identification" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Economic-Research-Journal-Skills/skills/er-identification into .claude/skills/er-identification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "er-identification", 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/Economic-Research-Journal-Skills/skills/er-identificationType 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 er-identification -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills er-identification --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/Economic-Research-Journal-Skills/skills/er-identification .agents/skills/er-identification && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "er-identification" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Economic-Research-Journal-Skills/skills/er-identification into .agents/skills/er-identification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "er-identification", 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 er-identification -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills er-identification --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/Economic-Research-Journal-Skills/skills/er-identification .cursor/skills/er-identification && 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 "er-identification" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Economic-Research-Journal-Skills/skills/er-identification into .cursor/skills/er-identification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "er-identification", 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 Economic-Research-Journal-Skills/skills/er-identification--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 er-identification -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills er-identification --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/Economic-Research-Journal-Skills/skills/er-identification .gemini/skills/er-identification && 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 "er-identification" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Economic-Research-Journal-Skills/skills/er-identification into .gemini/skills/er-identification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "er-identification", 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 er-identificationInstalls 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 er-identification -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/Economic-Research-Journal-Skills/skills/er-identification .github/skills/er-identification && 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 "er-identification" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Economic-Research-Journal-Skills/skills/er-identification into .github/skills/er-identification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "er-identification", 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 er-identification -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 er-identification --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/Economic-Research-Journal-Skills/skills/er-identification .opencode/skills/er-identification && 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 "er-identification" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Economic-Research-Journal-Skills/skills/er-identification into .opencode/skills/er-identification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "er-identification", 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
er-identification- GitHub stars
- 1.2k
- Token cost
- ~1.2k tokens
- SKILL.md length
- 297 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when the empirical identification strategy is the bottleneck for an Economic-Research manuscript — quasi-experimental designs (DID, IV, RDD, DML, event study).
- Works in 7 steps: 政策冲击 + DID（含 staggered / continuous… → 断点回归（清晰的政策门槛） → 工具变量（强工具 + 排他性论证） → …
- The empirical identification strategy is the bottleneck for an Economic-Research manuscript — quasi-experimental designs (DID
- SKILL.md covers 触发时机, 设计优先级, 分支 A：交叠（多时点）DID —— ★ 最常见也最易被挑 and 分支 B：IV —— 报告现代弱工具诊断, plus 8 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Er Identification is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when the empirical identification strategy is the bottleneck for an Economic-Research manuscript — quasi-experimental designs (DID, IV, RDD, DML, event study). Stress-tests the design against modern (2019-2024) estimators and reporting standards before drafting tables.
Its SKILL.md is about 1.2k 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 Load testing, Experimental design and Econometrics and empirical research. 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
- The empirical identification strategy is the bottleneck for an Economic-Research manuscript — quasi-experimental designs (DID
- Tasks that involve Load testing
- Tasks that involve Experimental design
Example prompts
- “/er-identification”
Requirements
- Python 3
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- 政策冲击 + DID（含 staggered / continuous treatment）
- 断点回归（清晰的政策门槛）
- 工具变量（强工具 + 排他性论证）
- 倾向得分匹配 + DID
- 合成控制法
- 双重机器学习 / 因果森林
- OLS + 严密内生性讨论（在结构估计 / 理论实证文章中可接受）
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 (its code samples are stata).
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
Er Identification loads about 1.2k tokens when it runs. Until then it costs about 73 tokens; SKILL.md has 297 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). 297 words, ~1,208 tokens.
Download SKILL.mdSave it as
.claude/skills/er-identification/SKILL.md (or your agent's skills folder).- name
- er-identification
- description
- Use when the empirical identification strategy is the bottleneck for an Economic-Research manuscript — quasi-experimental designs (DID, IV, RDD, DML, event study). Stress-tests the design against modern (2019-2024) estimators and reporting standards before drafting tables.
因果识别策略（er-identification）
配套代码：resources/code/stata/03_did_modern.do（DID）、04_iv.do（IV）、05_rdd.do（RDD）、06_dml.do（DML）。
触发时机
- 实证主体仅有 OLS + 控制变量
- DID 用了 TWFE 但没回应近年异质性处理效应批评
- IV 第一阶段弱 / 工具变量内生性疑虑
- 准备用双重机器学习但不确定怎么报告
设计优先级
《经济研究》编委的偏好排序（强 → 弱）：
- 政策冲击 + DID（含 staggered / continuous treatment）
- 断点回归（清晰的政策门槛）
- 工具变量（强工具 + 排他性论证）
- 倾向得分匹配 + DID
- 合成控制法
- 双重机器学习 / 因果森林
- OLS + 严密内生性讨论（在结构估计 / 理论实证文章中可接受）
该刊明确反对"唯定量倾向"：识别策略再漂亮，也要回到理论与中国制度问题。识别是手段，不是卖点。
分支 A：交叠（多时点）DID —— ★ 最常见也最易被挑
交叠 DID 不能只报 TWFE。标准流程四步：
- TWFE 基准——读者熟悉的起点（但交叠下可能有偏）。
- Goodman-Bacon (2021) 分解（
bacondecomp）——展示"坏比较 / 负权重"问题。 - 异质性稳健估计量做主结果（下表任选其一为主，其余作稳健性）：
| 估计量 | 论文 | Stata | R |
|---|---|---|---|
| group-time ATT | Callaway & Sant'Anna (2021) | csdid | did::att_gt |
| 交互加权 IW | Sun & Abraham (2021) | eventstudyinteract | fixest::sunab |
| 插补（最有效率） | Borusyak, Jaravel & Spiess (2024) | did_imputation | didimputation |
| 两阶段 | Gardner (2022) | did2s | did2s |
| 非二值/可逆处理 | de Chaisemartin & D'Haultfœuille (2020/24) | did_multiplegt_dyn | DIDmultiplegtDYN |
* Callaway-Sant'Anna：gvar = 首次受处理年份，从不处理者 = 0
csdid Y X, ivar(id) time(year) gvar(gvar) method(dripw)
estat simple // 总体 ATT
estat event // 动态效应- 事件研究图检验平行趋势与动态效应（处理前一期为基准、95% CI、处理时点垂直虚线）。
- 安慰剂：随机指派处理时点/对象 500–1000 次，看真实系数是否落在分布尾部（见
er-robustness）。
避坑：平行趋势"只看图不检验"；预期效应/提前反应；用 TWFE 事件研究当交叠下的动态主结果（也可能有偏，主结果用 CS / SA）。
分支 B：IV —— 报告现代弱工具诊断
不要只报"F>10"。标准报告四要素：
- 第一阶段 Kleibergen-Paap rk Wald F（异方差/聚类下有效，取代 Cragg-Donald F）。
- 对照 Stock-Yogo (2005) 临界值。
- 有效 F（Montiel Olea & Pflueger 2013，
weakivtest），单内生变量更稳妥。 - 弱工具稳健推断：Anderson-Rubin 检验与置信区间（
weakiv）；恰好识别时 AR 对弱工具完全稳健。
ivreg2 Y X (D = Z1 Z2), robust first // 自动报告 KP rk F、Hansen J
weakivtest // 有效 F
weakiv ivreg2 Y X (D = Z1 Z2), robust // AR / CLR / K 稳健区间排他性论证至少三段：理论 / 制度 / 安慰剂；并报告 reduced form。 范文对标（确属《经济研究》）：王永钦、董雯《机器人的兴起如何影响中国劳动力市场？》（2020 年第 10 期）——以美国行业机器人渗透趋势构造 Bartik / shift-share 工具变量，论证外生性与排他性。
分支 C：RDD
rdplot Y X, c(0) p(1) kernel(triangular)
rdrobust Y X, c(0) p(1) kernel(triangular) bwselect(mserd) // 报告 Robust 行
rddensity X, c(0) // CJM 操纵检验- 主估计报告 稳健偏差校正 CI（Calonico-Cattaneo-Titiunik 2014 的核心贡献），不要只报常规 CI。
- 操纵检验用
rddensity（Cattaneo-Jansson-Ma，已取代 McCrary 2008）。 - 稳健性：协变量连续性、≥3 个带宽、donut RD、安慰剂断点。
- 范文对标（确属《经济研究》）：刘生龙、周绍杰、胡鞍钢《义务教育法与中国城镇教育回报：基于断点回归设计》（2016 年第 2 期）。
分支 D：DML 双重机器学习
报告：模型类型（偏线性 PLR / 交互式）、交叉拟合折数 K（5 或 10）、干扰函数学习器（lasso / 随机森林 / 梯度提升）+ 学习器稳健性对比、Neyman 正交得分标准误（Chernozhukov et al. 2018）。Stata ddml+pystacked；Python DoubleML。
分支 E：结构估计 / 理论实证
微观基础是否清晰？识别假设是否明确列出？参数估计是否提供反事实分析？
标准误
| 场景 | 做法 | 命令 |
|---|---|---|
| 组内相关 | 聚类稳健 | reghdfe ..., vce(cluster id) |
| 两维相关 | 双向聚类 | vce(cluster firm year) |
| 聚类数过少（<~40） | wild cluster bootstrap | boottest（见 er-robustness） |
| 空间相关 | Conley 空间 HAC | acreg |
执行桥（StatsPAI / Stata MCP）
把设计跑出来并审计，而不是只做描述。完整映射见
execution-with-mcp。《经济研究》是中文经济学顶刊，识别可信度通常是约束；交错 DID、弱工具稳健 IV、RDD 与机制检验。
detect_design→recommend→ 用as_handle=true拟合 →audit_result列出尚欠的检查。- **观察性因果：**交错 DID（
callaway_santanna/sun_abraham+bacon_decomposition+honest_did_from_result）；IV（effective_f_test+anderson_rubin_ci）；RDD（rdrobust+mccrary_test）。 - **实验：**随机化推断 +
romano_wolf做多结果族错误率控制。 - 敏感性：
oster_delta/sensemakr。
正文报告经济量级，完整 battery 进附录；每个数字都能复现。端到端真跑示例见
JF 执行 walkthrough。若 StatsPAI/Stata 未连接，改用 resources/code/ 并标注未验证数字。
必查清单
- 交叠 DID：Bacon 分解 + 至少一种异质性稳健估计量 + 事件研究图
- 平行趋势 / 平滑性 / 弱工具 检验都做了（不是只看图）
- 安慰剂检验（处理时点随机 / 处理对象随机）
- IV：KP rk F + 有效 F + AR 稳健区间 + reduced form + 排他性三段论证
- RDD：报告 Robust 行 CI + rddensity 操纵检验 + 多带宽
- 标准误聚类层次合理；少聚类时 wild bootstrap
- 回应了"被处理者预期 / 提前反应"问题
反模式
- TWFE + staggered 但不讨论异质性处理偏误
- IV 用"外生事件 × 上一期内生变量"——审稿人会问"为何上一期不影响当期"
- "我们认为该政策外生于公司决策"但没给证据
- RDD 用了截断带宽但不汇报带宽敏感性
- 把识别策略当卖点，脱离理论与中国制度问题
输出格式
【识别策略】交叠DID / IV / RDD / DML / 结构估计 / 其他
【交叠DID 主估计量】TWFE only（需升级）/ CS / SA / BJS / dCDH
【已完成检验】[Bacon分解, 平行趋势, 安慰剂, KP F, 有效F, AR, rddensity, ...]
【缺失检验】[...]
【聚类层次】...
【下一步】er-mechanism© 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 Economic-Research-Journal-Skills/skills/er-identification of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Er Identification 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 |
|---|---|---|---|---|---|---|
| Er Identification this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.2k | Automated safety check: Pass | MIT | |
| Academic GrillExekiel179/psyclaw | 103 | — | ~2k | Automated safety check: Pass | MIT | |
| Econometric Research Writingfranklee16/academic-research-skills | 223 | — | ~2.4k | Automated safety check: Pass | None | |
| Causalai-analyst-lab/ai-analyst | 304 | — | ~1.8k | Automated safety check: Pass | MIT | |
| Fin Experiment Designcsmar432/finai-research | 109 | — | ~4.2k | Automated safety check: Pass | MIT | |
| Judea PearlK-Dense-AI/mimeo | 282 | — | ~1.7k | Automated safety check: Pass | MIT |
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Econometric Research Writing
franklee16/academic-research-skills
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Causal
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Causal inference toolkit for when experiments are not possible: estimate treatment effects from observational data with assumption checks and mandatory caveats.
Fin Experiment Design
csmar432/finai-research
经济金融实证方法设计。根据研究想法和REFINEDDESIGN.md，生成完整的实证研究设计方案，覆盖识别策略选择、样本构建、变量定义、稳健性检验清单和内生性处理方案。
Judea Pearl
K-Dense-AI/mimeo
Applies Judea Pearl's causal reasoning frameworks to distinguish correlation from causation, evaluate AI capabilities, and make counterfactual decisions.
Academic Paper Verify
brycewang-stanford/Auto-Empirical-Research-Skills
Thoroughly verify all code, tables, figures, modeling decisions, and quantitative claims in an academic paper against its source R scripts and output files.
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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…
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Questions about Er Identification
What does Er Identification do?
A skill your agent uses when the empirical identification strategy is the bottleneck for an Economic-Research manuscript — quasi-experimental designs (DID, IV, RDD, DML, event study). Er Identification is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when the empirical identification strategy is the bottleneck for an Economic-Research manuscript — quasi-experimental designs (DID, IV, RDD, DML, event study).
When should I use Er Identification?
Er Identification fits situations like: the empirical identification strategy is the bottleneck for an Economic-Research manuscript — quasi-experimental designs (DID; tasks that involve Load testing; tasks that involve Experimental design.
How do I install Er Identification in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill er-identification -a claude-code`. Or copy the skill folder (Economic-Research-Journal-Skills/skills/er-identification in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/er-identification in your project. Claude Code loads it when a task matches its description.
How do I install Er Identification in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill er-identification -a codex`. Or copy the skill folder (Economic-Research-Journal-Skills/skills/er-identification in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/er-identification in your project. Codex loads it when a task matches its description.
Can I use Er Identification 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 er-identification -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/er-identification, .gemini/skills/er-identification, .github/skills/er-identification and .opencode/skills/er-identification in your project.
What does Er Identification need to run?
SKILL.md names no scripts, command-line tools or credentials: Er Identification is instructions for the agent only. Our summary lists: Python 3.
Does Er Identification 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 Er Identification 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 Er Identification use?
Er Identification 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 Er Identification use?
About 1.2k tokens (SKILL.md is roughly 4.8k 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 Er Identification?
Skills that share tags, products or a category with Er Identification: Academic Grill (Exekiel179/psyclaw, 103 stars), Econometric Research Writing (franklee16/academic-research-skills, 223 stars), Causal (ai-analyst-lab/ai-analyst, 304 stars) and Fin Experiment Design (csmar432/finai-research, 109 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Er Identification?
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.