FRED Macro Time Series
kansoku-trade/kansoku
Looks up US and global macro series from St. Louis Fed FRED, such as CPI, GDP, Fed funds, yields, M2 and the dollar index, and reports them with units and dates.
A skill your agent uses when building or auditing Journal of Human Resources (JHR) empirical pipelines — sample construction, design-based causal estimates with correct clustering, robustness…
Install Jhr Data Analysis
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jhr-data-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jhr-data-analysis --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-Human-Resources-Skills/skills/jhr-data-analysis .claude/skills/jhr-data-analysis && 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 "jhr-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Human-Resources-Skills/skills/jhr-data-analysis into .claude/skills/jhr-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jhr-data-analysis", 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-Human-Resources-Skills/skills/jhr-data-analysisType 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 jhr-data-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jhr-data-analysis --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-Human-Resources-Skills/skills/jhr-data-analysis .agents/skills/jhr-data-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "jhr-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Human-Resources-Skills/skills/jhr-data-analysis into .agents/skills/jhr-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jhr-data-analysis", 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 jhr-data-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jhr-data-analysis --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-Human-Resources-Skills/skills/jhr-data-analysis .cursor/skills/jhr-data-analysis && 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 "jhr-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Human-Resources-Skills/skills/jhr-data-analysis into .cursor/skills/jhr-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jhr-data-analysis", 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-Human-Resources-Skills/skills/jhr-data-analysis--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 jhr-data-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jhr-data-analysis --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-Human-Resources-Skills/skills/jhr-data-analysis .gemini/skills/jhr-data-analysis && 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 "jhr-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Human-Resources-Skills/skills/jhr-data-analysis into .gemini/skills/jhr-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jhr-data-analysis", 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 jhr-data-analysisInstalls 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 jhr-data-analysis -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-Human-Resources-Skills/skills/jhr-data-analysis .github/skills/jhr-data-analysis && 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 "jhr-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Human-Resources-Skills/skills/jhr-data-analysis into .github/skills/jhr-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jhr-data-analysis", 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 jhr-data-analysis -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 jhr-data-analysis --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-Human-Resources-Skills/skills/jhr-data-analysis .opencode/skills/jhr-data-analysis && 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 "jhr-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Human-Resources-Skills/skills/jhr-data-analysis into .opencode/skills/jhr-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jhr-data-analysis", 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
jhr-data-analysis- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 636 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when building or auditing Journal of Human Resources (JHR) empirical pipelines — sample construction, design-based causal estimates with correct clustering, robustness…
- Works in 4 steps: Sample: 1.9M births, 12 adopting and 19… → Main estimate: Callaway-Sant'Anna ATT of… → Reconciliation: prior single-state… → …
- Auditing Journal of Human Resources (JHR) empirical pipelines — sample construction
- SKILL.md covers When to trigger, Applied-micro analysis checklist, JHR-specific constraints and Comparative-estimate workflow, plus 7 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Jhr Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when building or auditing Journal of Human Resources (JHR) empirical pipelines — sample construction, design-based causal estimates with correct clustering, robustness, comparative estimation against prior published work, online appendix material, and reproducible analysis.
Its SKILL.md is about 1.6k 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 Data & Analytics, covering Data analysis and Recruiting and HR. 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 Journal of Human Resources (JHR) empirical pipelines — sample construction
- Design-based causal estimates with correct clustering
- Comparative estimation against prior published work
- Online appendix material
Example prompts
- “/jhr-data-analysis”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Sample: 1.9M births, 12 adopting and 19 comparison states; attrition table
- Main estimate: Callaway-Sant'Anna ATT of -1.3 severe-morbidity events per
- Reconciliation: prior single-state estimate of -3.0 shrinks to -1.6 when its
- Archive: scripts run end-to-end from a clean clone; restricted birth-record
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
Jhr Data Analysis loads about 1.6k tokens when it runs. Until then it costs about 74 tokens; SKILL.md has 636 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). 636 words, ~1,587 tokens.
Download SKILL.mdSave it as
.claude/skills/jhr-data-analysis/SKILL.md (or your agent's skills folder).- name
- jhr-data-analysis
- description
- Use when building or auditing Journal of Human Resources (JHR) empirical pipelines — sample construction, design-based causal estimates with correct clustering, robustness, comparative estimation against prior published work, online appendix material, and reproducible analysis.
Data Analysis (jhr-data-analysis)
When to trigger
- You are preparing the empirical pipeline for a JHR paper
- Sample construction, reconciliation, or robustness is still unsettled
- The paper needs a replication-ready workflow before acceptance
Applied-micro analysis checklist
- Define unit, population, period, treatment, comparison group, and outcome.
- Show sample attrition and merge rules.
- Report baseline balance or pre-treatment comparability when relevant.
- Estimate main effects with the right clustering and fixed effects.
- Add reconciliation estimates against the closest prior published work.
- Add robustness for sample windows, functional form, controls, treatment definitions, and outlier handling.
JHR-specific constraints
- Keep main tables inside the page limit; move overflow to Online Appendix.
- Prepare a data-archive plan from the start, especially for restricted data.
- For RCTs, track pre-analysis plan registration and deviations.
Comparative-estimate workflow
Build one reconciliation table before submission:
| Column | Purpose |
|---|---|
| Prior published estimate | Reproduce or quote the closest estimate with sample/design notes |
| Prior specification on your data | Shows whether the difference is data or specification |
| Your preferred specification | Shows the incremental design or measurement change |
| Sensitivity bridge | Changes one assumption at a time: sample, controls, weights, clustering, outcome |
This table can live in the Online Appendix, but the introduction should summarize the lesson in one sentence. Without it, a JHR referee can ask for reconciliation late in the process.
Estimator defaults JHR referees assume
| Design | Default estimator | Diagnostics referees expect alongside |
|---|---|---|
| Staggered DID | Callaway-Sant'Anna, Sun-Abraham, or imputation (Borusyak-Jaravel-Spiess); never TWFE alone with heterogeneous timing | Event study with pre-period coefficients, Goodman-Bacon style decomposition when TWFE is reported |
| Sharp/fuzzy RDD | Local linear with MSE-optimal bandwidth and robust bias-corrected CIs | Density/manipulation test, covariate continuity, bandwidth and donut sensitivity |
| IV | 2SLS plus weak-IV-robust inference when first stage is marginal | First-stage table per endogenous variable, effective F, Anderson-Rubin CI |
| Lottery / admissions experiment | ITT plus LATE via lottery-fixed-effects 2SLS | Balance within randomization strata, compliance and attrition by arm |
| RCT | PAP-aligned ITT with randomization-inference check where feasible | Balance, attrition, multiple-testing adjustment |
Inference choices that draw referee fire
- Cluster at the level of treatment assignment (state policy → state clusters), not at the individual or county level just because N is larger.
- With few treated clusters, add wild cluster bootstrap or randomization inference; report how many clusters drive identification.
- Survey-weight decisions must match the estimand: weighted for population parameters, unweighted (with justification) for design-based comparisons.
- Show that significance survives the correct clustering before any heterogeneity cuts are interpreted.
Show full SKILL.md (244 more words)Show less
Linked-data hygiene
- Document match rates for administrative-survey linkages and show that match quality does not differ by treatment status; differential linkage is a selection story referees raise unprompted.
- Date-stamp policy adoption variables from primary legal sources; miscoded effective dates are a classic catch in JHR rollout papers.
Worked numbers: postpartum-coverage pipeline
Illustrative pipeline for a Medicaid postpartum-coverage extension paper using linked birth records (numbers invented for the walkthrough):
- Sample: 1.9M births, 12 adopting and 19 comparison states; attrition table shows 4 percent lost to cross-state moves.
- Main estimate: Callaway-Sant'Anna ATT of -1.3 severe-morbidity events per 1,000 births, SE clustered on 31 states, wild-bootstrap p reported.
- Reconciliation: prior single-state estimate of -3.0 shrinks to -1.6 when its specification is run on the multi-state sample — difference is sample, not specification; one sentence in the introduction states this.
- Archive: scripts run end-to-end from a clean clone; restricted birth-record access documented for the waiver request.
Robustness ledger to maintain
Check | Spec changed | Estimate | SE | Verdict | Exhibit
pre-trends | event study, t-4..t-1 | ... | ... | flat/violated | Fig 2
alt control group | never-treated only | ... | ... | stable/moved | App T3
clustering | state vs state-by-year | ... | ... | robust/fragile| App T4
sample window | drop early adopters | ... | ... | stable/moved | App T5
prior-spec bridge | prior paper's controls | ... | ... | reconciled | App T6Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. JHR is labor/education economics — program evaluation with selection; DiD/IV/RDD and the selection objection are central.
- 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.
Output format
[Sample] unit + population + period
[Design] ...
[Main estimates] ...
[Reconciliation tests] ...
[Archive-readiness gaps] ...
[Next step] jhr-contribution-framing© 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-Human-Resources-Skills/skills/jhr-data-analysis of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Jhr Data Analysis 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 |
|---|---|---|---|---|---|---|
| Jhr Data Analysis this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| FRED Macro Time Serieskansoku-trade/kansoku | 327 | 1 repos | ~1.1k | Automated safety check: Notes | Custom licence | |
| Business Metrics Calculatornimrodfisher/data-analytics-skills | 465 | — | ~668 | Automated safety check: Pass | MIT | |
| Afa Dashboardafadtc/afa-dtc-skills | 168 | — | ~1.8k | Automated safety check: Pass | Custom licence | |
| Business Intelligenceborghei/Claude-Skills | 881 | — | ~3.1k | Automated safety check: Pass | MIT | |
| Car Tables Figuresfranklee16/academic-research-skills | 223 | 1 repos | ~997 | Automated safety check: Pass | None |
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Questions about Jhr Data Analysis
What does Jhr Data Analysis do?
A skill your agent uses when building or auditing Journal of Human Resources (JHR) empirical pipelines — sample construction, design-based causal estimates with correct clustering, robustness…. Jhr Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when building or auditing Journal of Human Resources (JHR) empirical pipelines — sample construction, design-based causal estimates with correct clustering, robustness, comparative estimation against prior published work, online appendix material, and reproducible analysis.
When should I use Jhr Data Analysis?
Jhr Data Analysis fits situations like: auditing Journal of Human Resources (JHR) empirical pipelines — sample construction; design-based causal estimates with correct clustering; comparative estimation against prior published work; online appendix material.
How do I install Jhr Data Analysis in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jhr-data-analysis -a claude-code`. Or copy the skill folder (Journal-of-Human-Resources-Skills/skills/jhr-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/jhr-data-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Jhr Data Analysis in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jhr-data-analysis -a codex`. Or copy the skill folder (Journal-of-Human-Resources-Skills/skills/jhr-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/jhr-data-analysis in your project. Codex loads it when a task matches its description.
Can I use Jhr Data Analysis 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 jhr-data-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jhr-data-analysis, .gemini/skills/jhr-data-analysis, .github/skills/jhr-data-analysis and .opencode/skills/jhr-data-analysis in your project.
What does Jhr Data Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Jhr Data Analysis is instructions for the agent only.
Does Jhr Data Analysis 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 Jhr Data Analysis 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 Jhr Data Analysis use?
Jhr Data Analysis 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 Jhr Data Analysis use?
About 1.6k tokens (SKILL.md is roughly 6.3k 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 Jhr Data Analysis?
Skills that share tags, products or a category with Jhr Data Analysis: FRED Macro Time Series (kansoku-trade/kansoku, 327 stars), Business Metrics Calculator (nimrodfisher/data-analytics-skills, 465 stars), Afa Dashboard (afadtc/afa-dtc-skills, 168 stars) and Business Intelligence (borghei/Claude-Skills, 881 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Jhr Data Analysis?
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.