Hypothesis Generation
spacering-net/codeg
Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.
A skill your agent uses when results for a Journal of Economic Geography (JEG) manuscript may be sensitive to spatial scale, the weight matrix, spatial autocorrelation, sample, or specification.
Install Jegeo Robustness
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jegeo-robustness -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jegeo-robustness --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/Journal-of-Economic-Geography-Skills/skills/jegeo-robustness .claude/skills/jegeo-robustness && 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 "jegeo-robustness" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Economic-Geography-Skills/skills/jegeo-robustness into .claude/skills/jegeo-robustness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jegeo-robustness", 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/Journal-of-Economic-Geography-Skills/skills/jegeo-robustnessType 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 jegeo-robustness -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jegeo-robustness --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/Journal-of-Economic-Geography-Skills/skills/jegeo-robustness .agents/skills/jegeo-robustness && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "jegeo-robustness" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Economic-Geography-Skills/skills/jegeo-robustness into .agents/skills/jegeo-robustness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jegeo-robustness", 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 jegeo-robustness -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jegeo-robustness --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/Journal-of-Economic-Geography-Skills/skills/jegeo-robustness .cursor/skills/jegeo-robustness && 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 "jegeo-robustness" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Economic-Geography-Skills/skills/jegeo-robustness into .cursor/skills/jegeo-robustness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jegeo-robustness", 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 Journal-of-Economic-Geography-Skills/skills/jegeo-robustness--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 jegeo-robustness -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jegeo-robustness --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/Journal-of-Economic-Geography-Skills/skills/jegeo-robustness .gemini/skills/jegeo-robustness && 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 "jegeo-robustness" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Economic-Geography-Skills/skills/jegeo-robustness into .gemini/skills/jegeo-robustness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jegeo-robustness", 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 jegeo-robustnessInstalls 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 jegeo-robustness -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/Journal-of-Economic-Geography-Skills/skills/jegeo-robustness .github/skills/jegeo-robustness && 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 "jegeo-robustness" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Economic-Geography-Skills/skills/jegeo-robustness into .github/skills/jegeo-robustness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jegeo-robustness", 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 jegeo-robustness -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 jegeo-robustness --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/Journal-of-Economic-Geography-Skills/skills/jegeo-robustness .opencode/skills/jegeo-robustness && 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 "jegeo-robustness" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Economic-Geography-Skills/skills/jegeo-robustness into .opencode/skills/jegeo-robustness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jegeo-robustness", 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
jegeo-robustness- GitHub stars
- 1.2k
- Token cost
- ~2.1k tokens
- SKILL.md length
- 1,034 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when results for a Journal of Economic Geography (JEG) manuscript may be sensitive to spatial scale, the weight matrix, spatial autocorrelation, sample, or specification.
- Works in 5 steps: Spatial-scale / MAUP first — if the… → Inference next — Conley SEs and residual… → Spillovers / spatial model — the… → …
- Results for a Journal of Economic Geography (JEG) manuscript may be sensitive to spatial scale
- SKILL.md covers When to trigger, The spatial robustness threats…, Sequencing the robustness… and The two robustness checks JEG…, plus 7 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Jegeo Robustness is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when results for a Journal of Economic Geography (JEG) manuscript may be sensitive to spatial scale, the weight matrix, spatial autocorrelation, sample, or specification. Organizes robustness by spatial threat; it does not invent results.
Its SKILL.md is about 2.1k 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. 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
- Results for a Journal of Economic Geography (JEG) manuscript may be sensitive to spatial scale
- The weight matrix
- Spatial autocorrelation
Example prompts
- “/jegeo-robustness”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Spatial-scale / MAUP first — if the result is scale-fragile, nothing else matters. Show it holds (or is honestly bounded) across…
- Inference next — Conley SEs and residual Moran's I; this is where overclaiming dies at JEG.
- Spillovers / spatial model — the SDM/SAR/SEM choice should be motivated by the mechanism, not run for completeness; report direct vs…
- Sample / influence — leave-one-region-out, alternative samples, outlier regions.
- Specification — alternative controls, functional form — last, and brief.
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
Jegeo Robustness loads about 2.1k tokens when it runs. Until then it costs about 65 tokens; SKILL.md has 1,034 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). 1,034 words, ~2,097 tokens.
Download SKILL.mdSave it as
.claude/skills/jegeo-robustness/SKILL.md (or your agent's skills folder).- name
- jegeo-robustness
- description
- Use when results for a Journal of Economic Geography (JEG) manuscript may be sensitive to spatial scale, the weight matrix, spatial autocorrelation, sample, or specification. Organizes robustness by spatial threat; it does not invent results.
Robustness Strategy (jegeo-robustness)
When to trigger
- The headline result might flip at a different spatial scale (region vs. commuting zone vs. grid cell)
- A spatial-econometric model's results depend on the chosen spatial weight matrix W
- Standard errors ignore spatial correlation across units, so inference is overstated
- Reviewers may suspect the effect is driven by a few large regions, a boundary artifact, or one definition of the spatial unit
- You have a long appendix of checks with no story about which threat each one answers
The spatial robustness threats unique to JEG
Most JEG robustness work is not generic — it answers threats that arise because the data are spatial. Organize by threat, not by a mechanical list, and lead with the spatial ones because that is where both communities probe hardest.
| Threat | What a referee fears | The check that answers it |
|---|---|---|
| Modifiable Areal Unit Problem (MAUP) | the result is an artifact of how space was carved into units | re-estimate at ≥2 spatial scales / aggregations; show the effect survives |
| Spatial weight matrix sensitivity | W was reverse-engineered to fit | vary W (contiguity, k-nearest, distance-decay, economic distance); report the spread |
| Spatial autocorrelation in errors | inference is overstated; "significance" is spurious | Conley spatial-HAC SEs over a range of cutoff distances; Moran's I on residuals |
| Spatial spillovers / SUTVA | the effect leaks into "control" units | ring/donut specs; spatial-lag or SDM models; bound the leakage |
| Boundary / edge effects | border units behave differently | drop border units; buffer zones; alternative boundary definitions |
| Driven by a few places | one metro or region carries the result | leave-one-region-out; jackknife the largest units |
| Scale-dependent mechanism | the mechanism only "works" at one resolution | show the sign/magnitude pattern is coherent across scales |
Sequencing the robustness section
- Spatial-scale / MAUP first — if the result is scale-fragile, nothing else matters. Show it holds (or is honestly bounded) across aggregations.
- Inference next — Conley SEs and residual Moran's I; this is where overclaiming dies at JEG.
- Spillovers / spatial model — the SDM/SAR/SEM choice should be motivated by the mechanism, not run for completeness; report direct vs. indirect (spillover) effects if you use a spatial-lag model.
- Sample / influence — leave-one-region-out, alternative samples, outlier regions.
- Specification — alternative controls, functional form — last, and brief.
Each robustness exhibit should answer "which threat does this kill?" in its title or note.
The two robustness checks JEG referees ask for most
Across submissions, two requests recur so reliably that strong authors pre-empt them in the first version:
- "Show it at another spatial scale." Have the alternative-aggregation result ready (commuting zone if you used regions, or a finer grid), and report the attenuation honestly. This is the MAUP defense and it is almost always asked.
- "Are your standard errors honest about spatial correlation?" Have Conley SEs over a few cutoff distances plus a residual Moran's I in hand. Reviewers from the economics side treat the absence of this as a reason to discount every t-statistic.
Building both before submission converts two likely R&R demands into evidence of rigor — and, if either weakens the result, you would far rather discover it yourself than have a referee surface it.
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. JEG is spatial economics — spatial dependence and sorting; emphasize identification and Conley/spatial-robust inference.
- Many outcomes / specifications:
romano_wolf(step-down FWER) orbenjamini_hochberg. - OVB sensitivity:
oster_delta/sensemakr. - Inference:
wild_cluster_bootstrap(few clusters),twoway_cluster/conley. - Re-fit off one handle:
audit_result(result_id)lists missing checks + the exactsuggest_functionfor each. - Exhibits:
etable/did_summary_to_latexfrom the handle — no retyped numbers.
Decisive checks in the body, exhaustive battery in the appendix. JF execution walkthrough.
Show full SKILL.md (439 more words)Show less
Checklist
- MAUP confronted: result shown across ≥2 spatial scales or aggregations
- Spatial weight matrix W varied; sensitivity of the estimate reported
- Spatial autocorrelation in errors addressed (Conley SEs over cutoffs; residual Moran's I)
- Spillovers/SUTVA: spatial-lag/SDM or ring spec; direct vs. indirect effects if relevant
- Boundary/edge effects checked
- Leave-one-region-out / influence of the largest units shown
- Every robustness exhibit is labeled by the threat it answers, not "Appendix Table A7"
Anti-patterns
- A single spatial scale with no MAUP check, presented as if the unit were natural
- One spatial weight matrix, never varied, with results that depend on it
- Default or one-way-clustered SEs when residuals are visibly spatially correlated
- A spatial-lag model run only to look sophisticated, with indirect effects never interpreted
- A 15-table robustness appendix with no mapping from check to identifying threat
- Hiding a scale-fragile result by reporting only the scale where it is significant
Worked vignette (illustrative)
A cluster-productivity result is significant at the NUTS-3 region level with region-clustered SEs. A referee asks two spatial questions: does it survive at the commuting-zone scale (MAUP), and are the SEs honest given that adjacent regions co-move? Re-aggregating to commuting zones, the point estimate holds but attenuates ~20%; Conley SEs at a 100km cutoff roughly double the standard error, and the effect remains positive but now marginal. Reporting both — rather than only the favorable NUTS-3/clustered combination — is what earns referee trust at JEG, even though it weakens the headline. Honesty about spatial fragility beats a fragile asterisk.
Referee pushback mapped to the robustness fix
- "How do I know this isn't a MAUP artifact?" → Show the estimate across ≥2 scales/aggregations; report attenuation honestly.
- "You chose W to get this result." → Vary W (contiguity, k-NN, distance-decay, economic distance) and report the spread, not one favorable matrix.
- "Your t-stats assume spatial independence." → Conley SEs over several cutoffs plus residual Moran's I.
- "It's all driven by [the capital region]." → Leave-one-region-out and a jackknife of the largest units.
- "The 'spillover' is just spatial trend." → Distinguish a spatial-lag spillover from a common spatial trend by including the trend and testing the lag separately.
A note on what NOT to over-do
JEG referees value an honest, threat-organized robustness section over a wall of tables. A spatial-Durbin model, a spatial-error model, and three W matrices run "for completeness," with none interpreted, signals fishing rather than rigor. Choose the spatial model that matches the mechanism (does theory predict spillovers? then SDM and interpret the indirect effect; if not, do not bolt one on), and let each remaining check answer one named threat. Candor about a bounded or scale-fragile result reads as strength here; a defended asterisk reads as weakness.
Output format
【Journal】Journal of Economic Geography
【Skill】jegeo-robustness
【Top spatial threat】MAUP / W-sensitivity / spatial autocorrelation / spillovers / boundary / influence
【MAUP check】scales tested + result
【Inference】Conley SEs (cutoffs) + residual Moran's I
【Spillover/spatial-model】spec + direct vs indirect effects
【Influence】leave-one-region-out result
【Honest verdict】robust / bounded / fragile (and where)
【Next skill】jegeo-tables-figures© 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-Economic-Geography-Skills/skills/jegeo-robustness of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Jegeo Robustness 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 |
|---|---|---|---|---|---|---|
| Jegeo Robustness this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~2.1k | Automated safety check: Pass | MIT | |
| Hypothesis Generationspacering-net/codeg | 3.9k | 14 repos | ~3.6k | Automated safety check: Notes | MIT | |
| GitHub Deep Researchbytedance/deer-flow | 84k | 4 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Nature Paper CardYuan1z0825/nature-skills | 47k | 2 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Content Research Writerweapp-tailwindcss/weapp-tailwindcss | 1.9k | 25 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Last30daysmvanhorn/last30days-skill | 64k | — | ~7.9k | Automated safety check: Notes | MIT |
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Categories
Questions about Jegeo Robustness
What does Jegeo Robustness do?
A skill your agent uses when results for a Journal of Economic Geography (JEG) manuscript may be sensitive to spatial scale, the weight matrix, spatial autocorrelation, sample, or specification. Jegeo Robustness is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when results for a Journal of Economic Geography (JEG) manuscript may be sensitive to spatial scale, the weight matrix, spatial autocorrelation, sample, or specification.
When should I use Jegeo Robustness?
Jegeo Robustness fits situations like: results for a Journal of Economic Geography (JEG) manuscript may be sensitive to spatial scale; the weight matrix; spatial autocorrelation.
How do I install Jegeo Robustness in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jegeo-robustness -a claude-code`. Or copy the skill folder (Journal-of-Economic-Geography-Skills/skills/jegeo-robustness in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/jegeo-robustness in your project. Claude Code loads it when a task matches its description.
How do I install Jegeo Robustness in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jegeo-robustness -a codex`. Or copy the skill folder (Journal-of-Economic-Geography-Skills/skills/jegeo-robustness in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/jegeo-robustness in your project. Codex loads it when a task matches its description.
Can I use Jegeo Robustness 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 jegeo-robustness -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jegeo-robustness, .gemini/skills/jegeo-robustness, .github/skills/jegeo-robustness and .opencode/skills/jegeo-robustness in your project.
What does Jegeo Robustness need to run?
SKILL.md names no scripts, command-line tools or credentials: Jegeo Robustness is instructions for the agent only.
Does Jegeo Robustness 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 Jegeo Robustness 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 Jegeo Robustness use?
Jegeo Robustness 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 Jegeo Robustness use?
About 2.1k tokens (SKILL.md is roughly 8.4k 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 Jegeo Robustness?
Skills that share tags, products or a category with Jegeo Robustness: Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars) and Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Jegeo Robustness?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 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.