A skill your agent uses when running the final delivery preflight for a commissioned Annual Review of Psychology (ARPsych) review via the Annual Reviews production system — disclosures…

MITAuto-check passed

Install Arpsych Submission

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

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

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills arpsych-submission --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/Annual-Review-of-Psychology-Skills/skills/arpsych-submission .claude/skills/arpsych-submission && 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
arpsych-submission
GitHub stars
1.2k
Token cost
~1.4k tokens
SKILL.md length
543 words
Files
2
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when running the final delivery preflight for a commissioned Annual Review of Psychology (ARPsych) review via the Annual Reviews production system — disclosures…

  • Reference/format compliance
  • SKILL.md covers When to trigger, Process facts (检索于…, Preflight checklist and Anti-patterns, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Figure permissions

What it does

Arpsych Submission is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when running the final delivery preflight for a commissioned Annual Review of Psychology (ARPsych) review via the Annual Reviews production system — disclosures, reference/format compliance, figure permissions, length, and the transparency of any embedded meta-analysis. Final checks; it does not draft content or handle the post-review revision (arpsych-revision).

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `templates/checklist.md`).

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

  • Reference/format compliance
  • Figure permissions
  • The transparency of any embedded meta-analysis

Example prompts

  • “/arpsych-submission”

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

Arpsych Submission loads about 1.4k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 543 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

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, ~1,393 tokens.

Download SKILL.mdSave it as .claude/skills/arpsych-submission/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
arpsych-submission
description
Use when running the final delivery preflight for a commissioned Annual Review of Psychology (ARPsych) review via the Annual Reviews production system — disclosures, reference/format compliance, figure permissions, length, and the transparency of any embedded meta-analysis. Final checks; it does not draft content or handle the post-review revision (arpsych-revision).

Delivery Preflight (arpsych-submission)

When to trigger

  • "Delivering soon" — last check before handing the commissioned review to Annual Reviews
  • Unsure which files, declarations, and permissions the production system expects
  • Confirming length, reference completeness, and figure specs are Annual Reviews-ready
  • Verifying transparency obligations for any quantitative synthesis the review reports

Process facts (检索于 2026-06;以官网为准 — re-confirm on the Annual Reviews author pages)

  • Publisher / venue. ARPsych is published by Annual Reviews (nonprofit), founded 1950, as an annual volume, co-edited by Susan T. Fiske (since 2000) and Daniel L. Schacter (co-editors listed for Volume 77, 2026; web-verified 2026-06-22, re-verify before relying); it is a review series, distinct from Psychological Bulletin (submitted reviews/meta-analyses), Annual Review of Clinical Psychology (clinical sister), and Perspectives on Psychological Science (essays). Articles are commissioned by the Editorial Committee; there is no cold-submission portal for unsolicited manuscripts — delivery happens within the invited-article workflow (检索于 2026-06;以官网为准).
  • Open access. Volumes are published open access under the Subscribe-to-Open (S2O) model (since 2023), under a Creative Commons license — there is no author-facing APC under S2O (检索于 2026-06;以官网为准). Do not treat S2O as a pay-to-publish APC.
  • Length. Each article has a length assigned in the invitation letter, including figures and tables; keep to it (检索于 2026-06;以官网为准). There is no single journal-wide word limit — it is per-invitation.
  • Manuscript prep. Annual Reviews asks for material double spaced in 12-point type; references must be complete and accurate (检索于 2026-06;以官网为准). House reference/format style is applied at production copyediting, so the delivered draft need not pre-conform — but reference data must be complete.
  • Disclosure (required). Annual Reviews requires authors to disclose potential sources of bias / conflicts of interest; funding sources are stated. Prepare per the author pages (检索于 2026-06;以官网为准).
  • Transparency of the review itself. A pure review reports no new data; the obligation bites on the documented search (from arpsych-literature-synthesis) and on any meta-analysis the review contributes — its data and code should be reproducible and depositable (检索于 2026-06;以官网为准).
  • Figures / permissions. Confirm figure specs and secure permission for any reproduced/adapted exhibit (检索于 2026-06;以官网为准).
Show full SKILL.md (214 more words)Show less

Preflight checklist

Article & files
  • This is a commissioned/invited article delivered in the invited workflow (not a cold submission)
  • Manuscript within the assigned length (figures and tables included)
  • Double-spaced, 12-point; references complete and accurate (house style applied at production)
  • Title page: title, complete author affiliations, keywords; review-style abstract
  • Figures meet current specs; reproduced exhibits have permission and attribution
Transparency
  • Search account documented (databases, terms, dates, in/out) — near-PRISMA where applicable
  • Any meta-analysis: effect data + code reproducible and depositable (OSF DOI)
Declarations
  • Conflict-of-interest / potential-bias disclosure prepared per Annual Reviews policy
  • Funding sources stated
  • AI not listed as an author
Volatile re-confirms
  • Assigned length, current reference style, figure specs, disclosure format, S2O/OA status — re-checked on the Annual Reviews author pages (检索于 2026-06)

Anti-patterns

  • Treating ARPsych like a journal with a cold-submission portal — it is invited; deliver through the commissioned workflow
  • Treating S2O open access as a pay-to-publish APC (it is not author-funded under S2O)
  • Over-running the assigned length or omitting figures/tables from the length count
  • Omitting the conflict-of-interest / bias disclosure Annual Reviews requires
  • Asserting a length limit, fee, or editor name from memory rather than the live author pages
  • Delivering a meta-analysis with no reproducible data/code, or a review with no documented search

Output format

text
【Article type】commissioned/invited review (not cold submission)? Y/N
【Length】within the assigned length (figures/tables included)? Y/N
【Manuscript prep】double-spaced 12pt; references complete + accurate? Y/N
【Abstract + front matter】review-style abstract, keywords, affiliations? Y/N
【Transparency】search documented; meta-analysis (if any) reproducible? Y/N
【Disclosure】COI / bias disclosure + funding prepared? Y/N
【Figures】specs met; permissions secured? Y/N
【Volatile re-confirms】length / style / OA / disclosure checked on Annual Reviews pages? Y/N
【Next step】deliver to Annual Reviews → arpsych-revision when the editor/peer-review letter arrives

Supplementary resources

© 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

SKILL.md and 1 other file in Annual-Review-of-Psychology-Skills/skills/arpsych-submission of brycewang-stanford/Awesome-Journal-Skills.

  • SKILL.md
  • templates/checklist.md

Open the folder on GitHubat commit 932eb23

Compare with similar skills

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Finalize Agent Promptgithub/awesome-copilot40k1 repos~224Automated safety check: PassMIT
Azure Deployment Preflightgithub/awesome-copilot40k1 repos~1.9kAutomated safety check: PassMIT
Implementation Final Reviewopenai/openai-agents-python30k—~2kAutomated safety check: PassMIT

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Questions about Arpsych Submission

What does Arpsych Submission do?

A skill your agent uses when running the final delivery preflight for a commissioned Annual Review of Psychology (ARPsych) review via the Annual Reviews production system — disclosures…. Arpsych Submission is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when running the final delivery preflight for a commissioned Annual Review of Psychology (ARPsych) review via the Annual Reviews production system — disclosures, reference/format compliance, figure permissions, length, and the transparency of any embedded meta-analysis.

When should I use Arpsych Submission?

Arpsych Submission fits situations like: reference/format compliance; figure permissions; the transparency of any embedded meta-analysis.

How do I install Arpsych Submission in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill arpsych-submission -a claude-code`. Or copy the skill folder (Annual-Review-of-Psychology-Skills/skills/arpsych-submission in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/arpsych-submission in your project. Claude Code loads it when a task matches its description.

How do I install Arpsych Submission in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill arpsych-submission -a codex`. Or copy the skill folder (Annual-Review-of-Psychology-Skills/skills/arpsych-submission in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/arpsych-submission in your project. Codex loads it when a task matches its description.

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

What does Arpsych Submission need to run?

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

Does Arpsych Submission 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 Arpsych Submission 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 Arpsych Submission use?

Arpsych Submission 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 Arpsych Submission use?

About 1.4k tokens (SKILL.md is roughly 5.6k 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 Arpsych Submission?

Skills that share tags, products or a category with Arpsych Submission: Delivery Gate (affaan-m/ECC, 276k stars), Running CI Preflight (PostHog/posthog, 40k stars), Finalize Agent Prompt (github/awesome-copilot, 40k stars) and Azure Deployment Preflight (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Arpsych Submission?

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.