Agent Skills
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psci-review-process
GitHub解析《Psychological Science》审稿流程，涵盖匿名评审、透明度权重及拒稿模式。用于投稿前压力测试、解读决定信或评估注册报告路线，帮助作者优化稿件以符合期刊对稳健性和透明度的高要求。
Trigger Scenarios
投稿前压力测试
决定是否使用注册报告路线
解读决定信
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill psci-review-process -g -y
SKILL.md
Frontmatter
{
"name": "psci-review-process",
"description": "Use when you need to understand how Psychological Science evaluates a manuscript — anonymized peer review, editorial weighting of robustness, transparency, and preregistration quality, desk-reject and decline-without-review patterns, and the Registered Reports route. Use when stress-testing a paper before submission or interpreting a decision letter. Sets expectations and shapes the paper to survive review; it does not contact editors."
}
Review Process (psci-review-process)
Psychological Science combines high-impact selectivity with strong credibility checks. Reviewers and editors weigh not only whether the finding is interesting, but whether it is robust, adequately powered, and transparent. Knowing this lets you pre-empt the common rejection reasons.
When to trigger
- Before submitting, to stress-test the manuscript
- Deciding whether to use the Registered Reports route
- Interpreting a decision letter and setting expectations
How review works
- Anonymized review. Initial submissions are anonymized; keep author identity out of the
manuscript and out of repository links (see
psci-submission). - Editorial triage. Editors assess impact, breadth, robustness, and fit; the very tight format means weak-fit or thin papers may be declined without full review.
- External review assesses theoretical contribution, design and power, analysis and disclosure, and the strength of the claim relative to the evidence.
- Transparency is graded. The Research Transparency Statement is shared with reviewers, and "limits on transparency will be a factor in editorial decisions"; preregistration quality is also weighed.
- Decisions. Reject, revise and resubmit, or accept; expect substantive revision and frequent requests for added robustness, disclosure, or analyses.
Registered Reports route (strongest for confirmatory claims)
- Stage 1: theory + design + analysis plan reviewed before data; in-principle acceptance commits the journal regardless of outcome if you follow the plan. Stage 2 reports the results. This route protects against publication bias and is well suited to confirmatory and replication work (and RR with Existing Data for prior-collected data).
Shape the paper to pass
- Make impact and breadth explicit early; show the result is robust and well-powered.
- Disclose fully and share data/materials (or justify exemptions) — credibility signals matter here.
- Separate confirmatory from exploratory analyses honestly.
- Fit the format — reviewers notice when a paper fights the word limit.
Desk-reject and decline-without-review patterns
The tight format and credibility screen mean many manuscripts never reach external review. Confirm current categories and limits against the journal's submission guidelines, but recognize these shapes:
| Pattern an editor sees | Likely outcome | Pre-empt it by |
|---|---|---|
| Surprising effect, single small study, no preregistration | declined or RR suggestion | add internal replication; preregister; report power |
| Narrow-paradigm result, no broad-relevance argument | desk reject (fit) | state who outside the subarea inherits the claim |
| "Data available on request," no DOIs | returned for compliance | deposit with persistent IDs before submitting |
| Over the word format, exhibits dumped at the end | returned to author | design to the format; embed exhibits |
| p-values and stars, no effect sizes/CIs | thin-evidence flag | estimation-first reporting |
Worked micro-example (illustrative triage)
Manuscript: two preregistered attention studies (N = 240; N = 300),
open data + materials with DOIs, effect sizes + CIs.
Editor read: impact (load-bearing premise), breadth (clinical inheritance),
robustness (internal replication), transparency (graded — strong).
Likely route: external review, probable R&R for added robustness/disclosure.
Counter-case: same finding, one N = 45 study, no prereg, request-only data
→ likely declined without full review.
How reviewers weigh the evidence (calibration anchors)
- A powered internal replication is the single strongest signal you can send; it converts "interesting but fragile" into "credible."
- Transparency is graded, not pass/fail — a candid exemption with an access path reads better than silent opacity. Preregistration quality (specific, dated, followed) matters more than its presence.
- Registered Reports are the venue's structural answer to publication bias; choosing the route after data exist defeats its purpose and reviewers will say so.
Anti-patterns
- A surprising but underpowered, single-study effect
- Weak or absent transparency (counts against the paper)
- Exploratory results dressed as confirmatory
- Expecting acceptance without a robustness/disclosure-heavy R&R
- Choosing a Registered Report after results exist
Output format
【Impact + breadth】clear early? [Y/N]
【Robustness + power】adequate? [Y/N]
【Transparency】data/materials + statement + preregistration strong? [Y/N]
【Confirmatory vs exploratory】honest? [Y/N]
【Route】Research Article vs Registered Report
【Realistic outcome】reject / R&R / accept
【Next】psci-submission (or psci-rebuttal if decided)
Supplementary resources
../../resources/official-source-map.md— review model, transparency weighting, Registered Reports
Version History
- 1839142 Current 2026-07-05 14:15
