Amr Data Analysis
franklee16/academic-research-skills
A skill your agent uses when stress-testing the LOGIC of an Academy of Management Review (AMR) theory manuscript — checking logical coherence, running thought experiments and counterfactuals…
A skill your agent uses when planning or stress-testing the analysis behind a Journal of Financial Intermediation (JFI) paper — bank/loan-level panel work, demand-absorbing specifications, and the…
Install Jfi Data Analysis
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jfi-data-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jfi-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-Financial-Intermediation-Skills/skills/jfi-data-analysis .claude/skills/jfi-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 "jfi-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Financial-Intermediation-Skills/skills/jfi-data-analysis into .claude/skills/jfi-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jfi-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-Financial-Intermediation-Skills/skills/jfi-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 jfi-data-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jfi-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-Financial-Intermediation-Skills/skills/jfi-data-analysis .agents/skills/jfi-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 "jfi-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Financial-Intermediation-Skills/skills/jfi-data-analysis into .agents/skills/jfi-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jfi-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 jfi-data-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jfi-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-Financial-Intermediation-Skills/skills/jfi-data-analysis .cursor/skills/jfi-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 "jfi-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Financial-Intermediation-Skills/skills/jfi-data-analysis into .cursor/skills/jfi-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jfi-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-Financial-Intermediation-Skills/skills/jfi-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 jfi-data-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jfi-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-Financial-Intermediation-Skills/skills/jfi-data-analysis .gemini/skills/jfi-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 "jfi-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Financial-Intermediation-Skills/skills/jfi-data-analysis into .gemini/skills/jfi-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jfi-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 jfi-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 jfi-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-Financial-Intermediation-Skills/skills/jfi-data-analysis .github/skills/jfi-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 "jfi-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Financial-Intermediation-Skills/skills/jfi-data-analysis into .github/skills/jfi-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jfi-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 jfi-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 jfi-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-Financial-Intermediation-Skills/skills/jfi-data-analysis .opencode/skills/jfi-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 "jfi-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Financial-Intermediation-Skills/skills/jfi-data-analysis into .opencode/skills/jfi-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jfi-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
jfi-data-analysis- GitHub stars
- 1.2k
- Token cost
- ~1.7k tokens
- SKILL.md length
- 737 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when planning or stress-testing the analysis behind a Journal of Financial Intermediation (JFI) paper — bank/loan-level panel work, demand-absorbing specifications, and the…
- Stress-testing the analysis behind a Journal of Financial Intermediation (JFI) paper — bank/loan-level panel work
- SKILL.md covers When to trigger, Empirical track (banking data), Theory track (numerical… and Data sharing (both tracks), plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Demand-absorbing specifications
What it does
Jfi Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when planning or stress-testing the analysis behind a Journal of Financial Intermediation (JFI) paper — bank/loan-level panel work, demand-absorbing specifications, and the robustness battery for empirics, or numerical examples and calibrated illustrations for theory. It guides the analysis plan; it does not replace running the code.
Its SKILL.md is about 1.7k 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 Load testing. 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
- Stress-testing the analysis behind a Journal of Financial Intermediation (JFI) paper — bank/loan-level panel work
- Demand-absorbing specifications
- The robustness battery for empirics
- Numerical examples and calibrated illustrations for theory
Example prompts
- “/jfi-data-analysis”
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
Jfi Data Analysis loads about 1.7k tokens when it runs. Until then it costs about 89 tokens; SKILL.md has 737 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). 737 words, ~1,661 tokens.
Download SKILL.mdSave it as
.claude/skills/jfi-data-analysis/SKILL.md (or your agent's skills folder).- name
- jfi-data-analysis
- description
- Use when planning or stress-testing the analysis behind a Journal of Financial Intermediation (JFI) paper — bank/loan-level panel work, demand-absorbing specifications, and the robustness battery for empirics, or numerical examples and calibrated illustrations for theory. It guides the analysis plan; it does not replace running the code.
Data Analysis (jfi-data-analysis)
When to trigger
- Building the empirical analysis on bank/firm/loan data, or its robustness battery
- Building a numerical example or calibration that illustrates a model's mechanism
Empirical track (banking data)
- Sample construction: document the universe (e.g., Call Reports / FR Y-9C banks, DealScan loans, HMDA mortgages), merge keys, and every filter; intermediation samples are sensitive to mergers, charter changes, and reporting breaks.
- Variables: define balance-sheet and credit quantities precisely (levels vs. growth, winsorizing, deflation); state timing relative to the shock to avoid mechanical reverse causality.
- Specifications: high-dimensional fixed effects (reghdfe / fixest); for credit-supply questions, use firm×time effects in matched lender–borrower panels to absorb demand.
- Robustness: alternative samples and windows, placebo periods, leave-one-out by large institutions, alternative clustering, and a balance/parallel-trends check for DID. The expected battery is substantial but there is no fixed robustness-table count; keep the main text compact and push secondary checks to appendices.
Theory track (numerical illustration)
When the paper is a model, "data analysis" is lighter and means reproducible computation:
- A numerical example or calibrated figure showing the mechanism and comparative statics — illustrative, not estimation.
- Keep the code clean and deterministic (fixed seeds/parameters) so a reader can regenerate every figure.
Data sharing (both tracks)
Prepare a Data Statement and link datasets via Editorial Manager; cite data with the [dataset] tag
(see jfi-replication-and-data-policy). Under Elsevier Option C, deposit/cite/link research data where
possible or explain why sharing is restricted.
Dataset-to-mechanism decision table
Pick data for the intermediation mechanism, not the other way around — JFI referees notice when the dataset cannot carry the claimed channel:
| Mechanism under study | Workhorse data | What the merge must support |
|---|---|---|
| Relationship lending / information capture | Credit register or DealScan loan-level | Multi-bank firms, so firm×time absorption is feasible |
| Capital / regulation transmission | Call Reports, FR Y-9C, stress-test exposures | Bank-level shock measured before announcement |
| Deposit competition / franchise value | FDIC Summary of Deposits, branch-level rates | Market-level (county/MSA) shares and pricing |
| Runs, liquidity, interbank stress | Supervisory or payment-system records (typically restricted) | Daily/weekly frequency around the stress window |
| Fintech displacement of banks | Platform loan tapes plus bank comparators | Comparable borrower-risk controls across lender types |
Worked robustness pass: a capital-shock battery (illustrative)
A hypothetical JFI paper estimates that a 1pp rise in required capital cuts loan growth to the same firm by 2.1pp (s.e. 0.6, firm×time FE, clustered by bank). The battery a JFI referee expects, each row tied to a named threat:
- OLS without firm×time FE gives −3.0pp; report both, so the reader sees demand absorption moves the estimate by roughly a third — evidence the design bites, and a sorting fact worth a paragraph.
- Drop the three largest banking groups: −1.9pp — the channel is not one institution.
- Placebo reform date two years earlier: +0.2pp, insignificant — supports timing.
- Extensive margin (relationship termination) rises 1.4pp — the intermediation mechanism shows up beyond intensive-margin amounts.
- Few-cluster check: wild-cluster bootstrap p ≈ 0.03 with 31 banks.
- Multi-bank vs. full sample: re-estimate firm-FE-only specs on both, since the within-firm identifying sample skews toward larger, less bank-dependent borrowers.
Show full SKILL.md (247 more words)Show less
Analysis probes specific to this venue
- Referees here routinely ask for the exposure-weighted firm-level aggregation when real outcomes (investment, employment) are claimed — firm×time FE cannot be used there, so pre-shock bank shares must carry the identification.
- Magnitude sanity: convert the loan-level coefficient into aggregate credit terms and benchmark it against the range in the lending-channel literature; an estimate ten times the consensus invites a measurement question before a citation.
- For the theory track, a calibration table listing every parameter, its value, and its source (moment matched, literature, normalization) is the JFI-credible substitute for a robustness battery.
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. JFI is banking and financial intermediation — typically corporate / bank causal designs built around regulation and shocks.
- Many outcomes / specifications:
romano_wolf(step-down FWER, accounts for cross-test correlation) orbenjamini_hochberg— report the adjusted threshold. - OVB sensitivity:
oster_delta/sensemakr— the confounder strength that would overturn the headline. - Inference:
wild_cluster_bootstrap(few clusters),twoway_cluster/conley. - Re-fit off one handle:
audit_result(result_id)lists the missing checks and the exactsuggest_functionfor each — no guessing the battery. - Exhibits:
etable/did_summary_to_latexfrom the handle — no retyped numbers.
Keep the decisive checks in the body and the exhaustive (now actually-run) battery in the appendix. See the executed chain in the JF execution walkthrough.
Anti-patterns
- Undocumented sample filters that drive the result
- Mixing credit supply and demand without firm×time absorption
- A theory "calibration" presented as if it were estimation
- Non-reproducible figures (random seeds, manual steps)
Output format
【Track】empirical / theory
【Sample / parameters】<universe + filters, or calibration>
【Core spec / example】<FE structure, or the numerical illustration>
【Robustness】<the battery, or seed/determinism notes>
【Next skill】jfi-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-Financial-Intermediation-Skills/skills/jfi-data-analysis of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Jfi 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 |
|---|---|---|---|---|---|---|
| Jfi Data Analysis this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.7k | Automated safety check: Pass | MIT | |
| Amr Data Analysisfranklee16/academic-research-skills | 223 | 1 repos | ~1.5k | Automated safety check: Pass | None | |
| Amr Theory Developmentfranklee16/academic-research-skills | 223 | 1 repos | ~1.4k | Automated safety check: Pass | None | |
| Isr Methodsfranklee16/academic-research-skills | 223 | 1 repos | ~1.1k | Automated safety check: Pass | None | |
| Jcr Methodsfranklee16/academic-research-skills | 223 | 1 repos | ~1.2k | Automated safety check: Pass | None | |
| Jme Data Analysisfranklee16/academic-research-skills | 223 | 1 repos | ~885 | Automated safety check: Pass | None |
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Related
Categories
Questions about Jfi Data Analysis
What does Jfi Data Analysis do?
A skill your agent uses when planning or stress-testing the analysis behind a Journal of Financial Intermediation (JFI) paper — bank/loan-level panel work, demand-absorbing specifications, and the…. Jfi Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when planning or stress-testing the analysis behind a Journal of Financial Intermediation (JFI) paper — bank/loan-level panel work, demand-absorbing specifications, and the robustness battery for empirics, or numerical examples and calibrated illustrations for theory.
When should I use Jfi Data Analysis?
Jfi Data Analysis fits situations like: stress-testing the analysis behind a Journal of Financial Intermediation (JFI) paper — bank/loan-level panel work; demand-absorbing specifications; the robustness battery for empirics; numerical examples and calibrated illustrations for theory.
How do I install Jfi Data Analysis in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jfi-data-analysis -a claude-code`. Or copy the skill folder (Journal-of-Financial-Intermediation-Skills/skills/jfi-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/jfi-data-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Jfi Data Analysis in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jfi-data-analysis -a codex`. Or copy the skill folder (Journal-of-Financial-Intermediation-Skills/skills/jfi-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/jfi-data-analysis in your project. Codex loads it when a task matches its description.
Can I use Jfi 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 jfi-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/jfi-data-analysis, .gemini/skills/jfi-data-analysis, .github/skills/jfi-data-analysis and .opencode/skills/jfi-data-analysis in your project.
What does Jfi Data Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Jfi Data Analysis is instructions for the agent only.
Does Jfi 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 Jfi 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 Jfi Data Analysis use?
Jfi 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 Jfi Data Analysis use?
About 1.7k tokens (SKILL.md is roughly 6.6k 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 Jfi Data Analysis?
Skills that share tags, products or a category with Jfi Data Analysis: Amr Data Analysis (franklee16/academic-research-skills, 223 stars), Amr Theory Development (franklee16/academic-research-skills, 223 stars), Isr Methods (franklee16/academic-research-skills, 223 stars) and Jcr Methods (franklee16/academic-research-skills, 223 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Jfi 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.