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reviewer
A full pre-submission peer review that finds the weaknesses real reviewers will flag, before they do.
$9
reviewer
Example session with this skill installed
Use reviewer to do a pre-submission review of my manuscript on few-shot object detection before I submit it.
- Read your context and instructions
- Compiled the reviewer
- Generated the document
Reviewed the manuscript against 10 dimensions. Overall: revise before submitting. Two major weaknesses (experimental rigor, missing ablations) and three minor issues, with concrete fixes.
Scorecard
| Dimension | Score | Notes |
|---|---|---|
| Novelty | 7/10 | Solid, but positioned against 2 missing baselines |
| Clarity | 8/10 | Method section is clear; intro is dense |
| Contribution significance | 7/10 | Impact understated in intro |
| Methodological rigor | 5/10 | No significance testing; single seed reported |
| Experimental validity | 5/10 | Missing cross-dataset generalization |
| Threats to validity | 6/10 | Discussed but no mitigation plan |
| Reproducibility | 7/10 | Code promised, no configs shown |
| Figures and tables | 7/10 | Fig. 3 crowded; add a summary table |
| References | 8/10 | Complete, 2 self-citations borderline |
| Structure | 8/10 | Follows IMRaD |
Top 3 fixes (do these first)
- Add baselines: compare against the two strongest recent methods, since reviewers will ask.
- Add rigor: report the mean ± std over 5 seeds and a significance test (McNemar or paired t-test).
- Add a cross-dataset experiment to preempt the overfit-to-one-benchmark criticism.
Likely reviewer concerns (and your answers)
- Why not method X? Cite it and explain the fair-comparison rationale.
- Results are marginal. Add effect sizes and the significance test above.
Next steps
- Apply the top 3 fixes, then re-run
reviewerto confirm the score rises above 7/10 across the board.
reviewer.pdf
PDF · document
Example file from a real run - the skill writes it into your workspace.
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
The problem
Reviewers find the same weaknesses every time: weak baselines, missing ablations, unsupported claims, and unclear figures. Finding them yourself before submission is far cheaper than a rejection. This skill performs a comprehensive pre-submission review.
What it does
- Evaluates novelty, clarity, contribution significance, methodological rigor, and experimental validity.
- Checks threats to validity, reproducibility, figure and table quality, and reference completeness.
- Identifies the weaknesses real reviewers would flag and suggests concrete fixes.
- Produces a scored report with a prioritized fix list.
Why this beats prompting it yourself
General prompts return polite, vague feedback. This skill scores the paper across ten dimensions, separates critical from minor issues, and simulates the exact questions a reviewer will ask, with suggested answers.
Use cases
- Running a pre-submission review before submitting.
- Preparing for resubmission after a rejection.
- Doing a friendly internal review before sharing with collaborators.
- Quality assurance before posting a preprint.
Known limitations
It is a pre-submission triage, not a substitute for real peer review. It works only with the draft you provide, and some judgments, such as novelty, remain partly subjective.
Important
It reviews and scores the manuscript; it does not rewrite it for you. Apply the fixes, then re-run it to confirm the score rises, as the final step of the Polish Pack.
Why buy it
Use it before submitting to anticipate and address reviewer concerns. It is the cheapest second opinion you can get and the final step of the Polish Pack.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
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- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
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