A skill your agent uses when choosing and justifying the research design for an Organization Studies (OS) manuscript — qualitative/ethnographic, process, historical, or quantitative — and setting…

MITAuto-check passedData & Analytics

Install Orgstud Methods

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill orgstud-methods -a claude-code

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

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills orgstud-methods --agent claude-code

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

Manual copy
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Organization-Studies-Skills/skills/orgstud-methods .claude/skills/orgstud-methods && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
orgstud-methods
GitHub stars
1.2k
Token cost
~1.7k tokens
SKILL.md length
725 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when choosing and justifying the research design for an Organization Studies (OS) manuscript — qualitative/ethnographic, process, historical, or quantitative — and setting…

  • Choosing and justifying the research design for an Organization Studies (OS) manuscript — qualitative/ethnographic
  • SKILL.md covers When to trigger, Method follows the theoretical…, Branch A — Qualitative /… and Branch B — Quantitative…, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Quantitative — and setting the rigor bar OS reviewers expect

What it does

Orgstud Methods is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when choosing and justifying the research design for an Organization Studies (OS) manuscript — qualitative/ethnographic, process, historical, or quantitative — and setting the rigor bar OS reviewers expect. Designs the study; it does not run the analysis (see orgstud-data-analysis).

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. 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

  • Choosing and justifying the research design for an Organization Studies (OS) manuscript — qualitative/ethnographic
  • Quantitative — and setting the rigor bar OS reviewers expect

Example prompts

  • “/orgstud-methods”

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

Orgstud Methods loads about 1.7k tokens when it runs. Until then it costs about 76 tokens; SKILL.md has 725 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~76
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

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). 725 words, ~1,711 tokens.

Download SKILL.mdSave it as .claude/skills/orgstud-methods/SKILL.md (or your agent's skills folder).
name
orgstud-methods
description
Use when choosing and justifying the research design for an Organization Studies (OS) manuscript — qualitative/ethnographic, process, historical, or quantitative — and setting the rigor bar OS reviewers expect. Designs the study; it does not run the analysis (see orgstud-data-analysis).

Methods & Research Design (orgstud-methods)

When to trigger

  • You are choosing between a qualitative/process design and a quantitative one
  • The design is chosen but its rigor and transparency are not yet defensible to OS reviewers
  • A qualitative study lacks a sampling logic, immersion account, or trustworthiness safeguards
  • A quantitative study leads with the estimator instead of the organizational mechanism it reveals

Method follows the theoretical question — and OS leans qualitative

At OS, no method is privileged in principle, but the journal's center of gravity is qualitative, ethnographic, process, and historical research, and such work is genuinely first-class here — not a tolerated minority. The non-negotiable is that the design fits the question (see orgstud-theory-development) and is executed with craft. A sophisticated estimator cannot rescue a thin theory, and a single immersive case can carry an OS paper if the theoretical insight is deep — a different bar from venues where a clean identification design is itself treated as the contribution. OS reviewers ask, above all, does this design let you see the organizing process you claim to theorize?

Branch A — Qualitative / process / ethnographic / historical

Use for how/why organizing unfolds: emergence, becoming, contestation, meaning, identity, institutional dynamics.

  • Theoretical (not convenience) sampling. Cases/sites/informants chosen to illuminate the process or construct; state the logic — polar/extreme cases, theoretical replication, revelatory case, longitudinal window.
  • Access and immersion. Specify duration, depth, and your role (participant vs. non-participant); for ethnography, time in the field; for historical work, the archive and its limits.
  • Triangulated data sources. Interviews (count, who, when, guide), observation, internal/archival documents, secondary sources — and how they corroborate.
  • Process design. If the contribution is a process model, build in the temporal leverage: real-time and/or retrospective data, event sequences, turning points (Langley's process strategies — narrative, temporal bracketing, visual mapping — are the standard idiom).
  • Trustworthiness. Credibility, transferability, dependability, confirmability: member checks, prolonged engagement, audit trail, investigator triangulation, negative-case analysis.
  • Reflexivity. State your standpoint and how it shaped access and interpretation — expected at a European, critically-aware journal, not optional.

Branch B — Quantitative organization theory

Use for whether/how much/under what conditions across many cases — welcome at OS when it does organization-theoretic work.

  • Sample and unit of analysis justified by the theory (organizations, fields, events, dyads, individuals nested in units).
  • Identification in service of theory. Be explicit about the causal claim and its threat (panel FE, event-history/survival, matching, natural experiments, DiD with modern staggered-adoption caveats). At OS, identification is a means to a theoretical end; a flawless quasi-experiment that yields no new understanding of organizing is still rejected. Lead with the mechanism, not the estimator.
  • Measurement validity. Operationalizations defended; multi-item reliability; common-method bias addressed if same-source.
  • Multilevel structure. If the theory is cross-level, use appropriate models and justify aggregation.
Show full SKILL.md (280 more words)Show less

Either branch

  • The design must let you see the mechanism / process, not just the endpoints.
  • Pre-empt the obvious alternative explanations at the design stage, not only in robustness.
  • Plan the data-to-theory link now — it feeds orgstud-data-analysis and orgstud-tables-figures.

Execution bridge (StatsPAI / Stata MCP)

For the empirical / causal lane, estimate and audit rather than only specify. Full map: execution-with-mcp. Organization Studies is largely qualitative/theoretical; use the chain below only for its quantitative-empirical papers, and say so when a study is interpretive.

  • detect_design → recommend → fit with as_handle=true → audit_result to enumerate the checks the design owes.
  • Panel / staggered DiD: callaway_santanna / sun_abraham + bacon_decomposition
    • honest_did_from_result. IV: effective_f_test + anderson_rubin_ci. RDD: rdrobust + mccrary_test.
  • Experiments: randomization-based inference and romano_wolf for the many-outcome family-wise correction reviewers expect.

Match the toolchain to the reviewer pool, and report the effect size the venue wants. A run end-to-end (synthetic data, real returns) is in the JF execution walkthrough.

Checklist

  • Design matches the theoretical form (process → qualitative; variance → quantitative)
  • Qualitative: theoretical sampling logic stated; access/immersion specified
  • Qualitative: multiple triangulated sources; trustworthiness safeguards named; reflexivity addressed
  • Process work: temporal leverage built in (real-time/retrospective; turning points)
  • Quantitative: identification explicit and subordinated to the organizational mechanism
  • Quantitative: measurement validity and (if needed) multilevel structure handled
  • Obvious alternative explanations are designed against, not just discussed later

Anti-patterns

  • Convenience sampling dressed up as theoretical sampling
  • Qualitative work with no transparency about coding, sources, or fieldwork depth
  • Treating a fancy estimator as the contribution when the question needs none
  • A quantitative paper that reads as applied econometrics with organizational variables bolted on
  • A design that can show that something happens but never how/why organizing produces it
  • Omitting reflexivity in interpretive work at a journal that expects it

Output format

text
【Design】qualitative (ethnographic/process/historical) / quantitative (type)
【Why it fits】link to the theoretical question and process/mechanism
【Sampling/identification】logic + key threat addressed
【Data sources】list + triangulation / measurement plan
【Temporal leverage】how the design captures process (if applicable)
【Rigor safeguards】trustworthiness + reflexivity, or identification checks
【Next skill】orgstud-data-analysis

© 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 Organization-Studies-Skills/skills/orgstud-methods of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Orgstud Methods 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.

Orgstud Methods compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Orgstud Methods this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~1.7kAutomated safety check: PassMIT
Exploratory Data Analysisspacering-net/codeg3.8k15 repos~3.6kAutomated safety check: PassMIT
Statistical Data Analysislingzhi227/agent-research-skills383—~886Automated safety check: PassNone
Q-EDA Exploratory AnalysisTyrealQ/q-skills108—~1.1kAutomated safety check: PassMIT
Diagnostic Study Quality Assessment Quadasaipoch/medical-research-skills2k—~1.4kAutomated safety check: PassMIT
PyMC Bayesian Modelingdavila7/claude-code-templates32k12 repos~3.9kAutomated safety check: PassMIT

Similar skills

  • Exploratory Data Analysis

    spacering-net/codeg

    Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats.

    3.8k GitHub starsUsed in 15 repos~3.6k tokens
    Data & AnalyticsAuto-check passed
  • Statistical Data Analysis

    lingzhi227/agent-research-skills

    Writes statistical analysis code for experimental data, runs it through a four-round review, and reports effect sizes, p-values and confidence intervals.

    383 GitHub stars~886 tokensUpdated 7 mo ago
    Data & AnalyticsAuto-check passed
  • Runs exploratory data analysis on tabular data after you confirm each column's measurement level, then writes CSV tables and a narrative summary.

    108 GitHub stars~1.1k tokensUpdated 14 days ago
    Data & AnalyticsAuto-check passed
  • Diagnostic Study Quality Assessment Quadas

    aipoch/medical-research-skills

    Analyzes clinical diagnostic accuracy studies for bias using the QUADAS-2 tool.

    2k GitHub stars~1.4k tokensUpdated 20 days ago
    Data & AnalyticsAuto-check passed
  • PyMC Bayesian Modeling

    davila7/claude-code-templates

    Builds, fits, checks and compares Bayesian models in PyMC, from priors and NUTS sampling to variational inference, LOO and WAIC comparison, and diagnostics.

    32k GitHub starsUsed in 12 repos~3.9k tokens
    Data & AnalyticsAuto-check passed
  • openFDA Regulatory Data Queries

    davila7/claude-code-templates

    Queries the openFDA API from Python for drug, device, food and veterinary data: adverse events, recalls, labels, approvals, NDC and UNII lookups.

    32k GitHub starsUsed in 12 repos~3.6k tokens
    Data & AnalyticsAuto-check passed

More from brycewang-stanford/Awesome-Journal-Skills

All 2,387 skills in this repo
  • Aaag Data Analysis

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when running and reporting the analysis for an Annals of the American Association of Geographers manuscript — spatial statistics and modeling, remote-sensing accuracy, or…

    1.2k GitHub stars~1.3k tokensUpdated 10 days ago
    Auto-check passed
  • Aaag Literature Positioning

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when positioning an Annals of the American Association of Geographers manuscript in the literature — engaging geographic scholarship across the relevant area and the…

    1.2k GitHub stars~1.3k tokensUpdated 10 days ago
    Auto-check passed
  • Aaag Rebuttal

    brycewang-stanford/Awesome-Journal-Skills

    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…

    1.2k GitHub stars~1.4k tokensUpdated 10 days ago
    Auto-check passed
  • 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…

    1.2k GitHub stars~1.4k tokensUpdated 10 days ago
    Auto-check passed
  • 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…

    1.2k GitHub stars~1.3k tokensUpdated 10 days ago
    Auto-check passed
  • 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…

    1.2k GitHub stars~1.6k tokensUpdated 10 days ago
    Auto-check passed

Questions about Orgstud Methods

What does Orgstud Methods do?

A skill your agent uses when choosing and justifying the research design for an Organization Studies (OS) manuscript — qualitative/ethnographic, process, historical, or quantitative — and setting…. Orgstud Methods is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when choosing and justifying the research design for an Organization Studies (OS) manuscript — qualitative/ethnographic, process, historical, or quantitative — and setting the rigor bar OS reviewers expect.

When should I use Orgstud Methods?

Orgstud Methods fits situations like: choosing and justifying the research design for an Organization Studies (OS) manuscript — qualitative/ethnographic; quantitative — and setting the rigor bar OS reviewers expect.

How do I install Orgstud Methods in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill orgstud-methods -a claude-code`. Or copy the skill folder (Organization-Studies-Skills/skills/orgstud-methods in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/orgstud-methods in your project. Claude Code loads it when a task matches its description.

How do I install Orgstud Methods in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill orgstud-methods -a codex`. Or copy the skill folder (Organization-Studies-Skills/skills/orgstud-methods in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/orgstud-methods in your project. Codex loads it when a task matches its description.

Can I use Orgstud Methods 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 orgstud-methods -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/orgstud-methods, .gemini/skills/orgstud-methods, .github/skills/orgstud-methods and .opencode/skills/orgstud-methods in your project.

What does Orgstud Methods need to run?

SKILL.md names no scripts, command-line tools or credentials: Orgstud Methods is instructions for the agent only.

Does Orgstud Methods 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 Orgstud Methods 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 Orgstud Methods use?

Orgstud Methods 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 Orgstud Methods use?

About 1.7k tokens (SKILL.md is roughly 6.8k 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 Orgstud Methods?

Skills that share tags, products or a category with Orgstud Methods: Exploratory Data Analysis (spacering-net/codeg, 3.8k stars), Statistical Data Analysis (lingzhi227/agent-research-skills, 383 stars), Q-EDA Exploratory Analysis (TyrealQ/q-skills, 108 stars) and Diagnostic Study Quality Assessment Quadas (aipoch/medical-research-skills, 2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Orgstud Methods?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,216 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.