Video Understand
calesthio/OpenMontage
Understand video content locally using ffmpeg frame extraction and Whisper transcription.
A skill your agent uses to understand how the Journal of Public Administration Research and Theory (JPART) evaluates a manuscript — double-blind review, desk screening on theory and fit, the reject…
MITAuto-check passed
Install Jpart Review Process
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jpart-review-process -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jpart-review-process --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-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process .claude/skills/jpart-review-process && 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 "jpart-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process into .claude/skills/jpart-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jpart-review-process", 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-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-processType 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 jpart-review-process -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jpart-review-process --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-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process .agents/skills/jpart-review-process && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "jpart-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process into .agents/skills/jpart-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jpart-review-process", 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 jpart-review-process -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jpart-review-process --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-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process .cursor/skills/jpart-review-process && 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 "jpart-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process into .cursor/skills/jpart-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jpart-review-process", 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-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process--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 jpart-review-process -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jpart-review-process --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-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process .gemini/skills/jpart-review-process && 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 "jpart-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process into .gemini/skills/jpart-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jpart-review-process", 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 jpart-review-processInstalls 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 jpart-review-process -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-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process .github/skills/jpart-review-process && 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 "jpart-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process into .github/skills/jpart-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jpart-review-process", 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 jpart-review-process -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 jpart-review-process --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-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process .opencode/skills/jpart-review-process && 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 "jpart-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process into .opencode/skills/jpart-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jpart-review-process", 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
jpart-review-process- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 543 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses to understand how the Journal of Public Administration Research and Theory (JPART) evaluates a manuscript — double-blind review, desk screening on theory and fit, the reject…
- Works in 5 steps: Double-blind. Reviewers do not know the… → Desk screening first. The editors screen… → External review. Papers passing the desk… → …
- Understand how the Journal of Public Administration Research and Theory (JPART) evaluates a manuscript — double-blind review
- SKILL.md covers When to trigger, How JPART review works, Shape the paper to pass and Desk-screen ledger, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Jpart Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use to understand how the Journal of Public Administration Research and Theory (JPART) evaluates a manuscript — double-blind review, desk screening on theory and fit, the reject / R&R / accept decision categories, and the PMRA/OUP editorial context. Sets expectations and shapes the paper to survive review; it does not contact editors.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
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
- Understand how the Journal of Public Administration Research and Theory (JPART) evaluates a manuscript — double-blind review
- Desk screening on theory and fit
- The reject / R&R / accept decision categories
- The PMRA/OUP editorial context
Example prompts
- “/jpart-review-process”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Double-blind. Reviewers do not know the authors and authors do not know reviewers. Anonymize the
- Desk screening first. The editors screen for fit before external review. The decisive grounds are
- External review. Papers passing the desk go to expert public-management reviewers.
- Decision categories: reject, revise and resubmit (R&R), or accept (acceptance after
- Detailed, developmental reviews. JPART describes its reviews as providing the basis for the
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
Jpart Review Process loads about 1.3k tokens when it runs. Until then it costs about 89 tokens; SKILL.md has 543 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). 543 words, ~1,252 tokens.
Download SKILL.mdSave it as
.claude/skills/jpart-review-process/SKILL.md (or your agent's skills folder).- name
- jpart-review-process
- description
- Use to understand how the Journal of Public Administration Research and Theory (JPART) evaluates a manuscript — double-blind review, desk screening on theory and fit, the reject / R&R / accept decision categories, and the PMRA/OUP editorial context. Sets expectations and shapes the paper to survive review; it does not contact editors.
Review Process (jpart-review-process)
Knowing how JPART screens and decides lets you pre-empt the failure modes before submitting. JPART runs a double-blind review and screens hard for a theory contribution and field fit before sending a paper out. Its detailed reviews report perceived strengths/weaknesses, the basis for the decision, and advice on how to proceed.
When to trigger
- Before submitting, to stress-test against desk-rejection grounds
- Deciding whether the paper is really a JPART paper vs. PAR/JPAM/Governance
- Interpreting a decision letter and setting expectations
- Understanding what reviewers are instructed to weigh
How JPART review works
- Double-blind. Reviewers do not know the authors and authors do not know reviewers. Anonymize the
manuscript accordingly (see
jpart-submission): cite your own work in the third person, keep acknowledgments/funding on the cover sheet only. - Desk screening first. The editors screen for fit before external review. The decisive grounds are
typically:
- Theory — no public-management theory contribution; a finding with no mechanism or "implications for theory." JPART's abstract template makes the theory slot explicit; an empty slot is a red flag.
- Fit — really a PAR (broad/practitioner) or JPAM (policy-analysis) paper, or comparative institutions better suited to Governance.
- Rigor / completeness — design cannot support the claim; missing a key element of a research article.
- External review. Papers passing the desk go to expert public-management reviewers.
- Decision categories: reject, revise and resubmit (R&R), or accept (acceptance after one or more R&R rounds is the norm). Decisions rest on the editors' read of the reviews.
- Detailed, developmental reviews. JPART describes its reviews as providing the basis for the
decision and advice on how to proceed — read them as a roadmap, not a verdict (see
jpart-rebuttal).
Shape the paper to pass
- Make the theoretical contribution explicit up front (avoids the "atheoretical" desk reject).
- Confirm JPART fit vs. siblings before submitting (avoids the wrong-venue desk reject).
- Engage the specific PA conversation you claim to advance (see
jpart-literature-positioning). - Address the PA-specific threats (common-method bias, selection) in the design, not just in a footnote.
- Stage the public data-and-code package; it is a condition of publication (see
jpart-transparency-and-data).
Show full SKILL.md (198 more words)Show less
Desk-screen ledger
Before submission, fill this ledger in one sitting. Empty cells predict desk rejection or a painful first round.
| Screen | Evidence in manuscript | Failure signal |
|---|---|---|
| Theory contribution | Intro names the PA theory, mechanism, and contribution type | "Public sector setting" substitutes for theory |
| Venue fit | Literature review locates the paper inside a JPART conversation | Main payoff is a policy estimate, practice essay, or institutions paper |
| Design credibility | Identification, measurement, and scope conditions match the claim | Threats are deferred to limitations or appendix only |
| Mechanism evidence | Exhibits or qualitative/process evidence distinguish rival explanations | Results section reports only average treatment/correlation |
| Transparency readiness | Data/code release path and restrictions are staged | Replication plan begins after acceptance |
Treat the ledger as an editorial simulation: if a skeptical editor can summarize the paper as "interesting
result, unclear PA theory," route back to jpart-theory-building before submission.
Anti-patterns
- Submitting a strong-empirics, no-theory paper to a theory-and-research journal (theory desk reject)
- Mis-filing a PAR or JPAM paper as JPART (fit desk reject)
- Expecting acceptance without an R&R round — developmental R&R is the normal path
- Treating the detailed review as an attack rather than a revision roadmap
Output format
【Desk-rejection check】theory / fit / rigor — any red flags?
【Desk-screen ledger】theory / venue / design / mechanism / transparency all filled? [Y/N]
【Theory contribution explicit?】[Y/N]
【JPART fit vs PAR/JPAM/Governance】[Y/N]
【Realistic outcome】reject / R&R / (rare) accept
【Materials staged】public data + code package? [Y/N]
【Next】jpart-submission (or jpart-rebuttal if decided)Supplementary resources
../../resources/official-source-map.md— double-blind review, why-submit page, decision process
© 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-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Jpart Review Process 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 |
|---|---|---|---|---|---|---|
| Jpart Review Process this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Video Understandcalesthio/OpenMontage | 66k | — | ~841 | Automated safety check: Pass | AGPL-3.0 | |
| Understand ExplainEgonex-AI/Understand-Anything | 86k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Understand Issuemastra-ai/mastra | 29k | — | ~3.1k | Automated safety check: Pass | Custom licence | |
| Understanding by Design PlannerTHU-MAIC/OpenMAIC | 40k | — | ~548 | Automated safety check: Pass | MIT | |
| Understand Diff AnalysisEgonex-AI/Understand-Anything | 86k | — | ~1.4k | Automated safety check: Pass | MIT |
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Questions about Jpart Review Process
What does Jpart Review Process do?
A skill your agent uses to understand how the Journal of Public Administration Research and Theory (JPART) evaluates a manuscript — double-blind review, desk screening on theory and fit, the reject…. Jpart Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use to understand how the Journal of Public Administration Research and Theory (JPART) evaluates a manuscript — double-blind review, desk screening on theory and fit, the reject / R&R / accept decision categories, and the PMRA/OUP editorial context.
When should I use Jpart Review Process?
Jpart Review Process fits situations like: understand how the Journal of Public Administration Research and Theory (JPART) evaluates a manuscript — double-blind review; desk screening on theory and fit; the reject / R&R / accept decision categories; the PMRA/OUP editorial context.
How do I install Jpart Review Process in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jpart-review-process -a claude-code`. Or copy the skill folder (Journal-of-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/jpart-review-process in your project. Claude Code loads it when a task matches its description.
How do I install Jpart Review Process in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jpart-review-process -a codex`. Or copy the skill folder (Journal-of-Public-Administration-Research-and-Theory-Skills/skills/jpart-review-process in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/jpart-review-process in your project. Codex loads it when a task matches its description.
Can I use Jpart Review Process 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 jpart-review-process -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jpart-review-process, .gemini/skills/jpart-review-process, .github/skills/jpart-review-process and .opencode/skills/jpart-review-process in your project.
What does Jpart Review Process need to run?
SKILL.md names no scripts, command-line tools or credentials: Jpart Review Process is instructions for the agent only.
Does Jpart Review Process 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 Jpart Review Process 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 Jpart Review Process use?
Jpart Review Process 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 Jpart Review Process use?
About 1.3k tokens (SKILL.md is roughly 5k 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 Jpart Review Process?
Skills that share tags, products or a category with Jpart Review Process: Video Understand (calesthio/OpenMontage, 66k stars), Understand Explain (Egonex-AI/Understand-Anything, 86k stars), Understand Issue (mastra-ai/mastra, 29k stars) and Understanding by Design Planner (THU-MAIC/OpenMAIC, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Jpart Review Process?
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.