scholarly-writing-refiner
Polishes academic English paragraph by paragraph, reviewing grammar, word choice, voice, coherence, and sentence structure. Outputs revision suggestions alongside polished text.
Install / Use
npx skills add zebbern/claude-code-guide --skill scholarly-writing-refinerInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Content & MediaSupported Platforms
Our assessment of scholarly-writing-refiner
scholarly-writing-refiner scores 92/100 on our quality scale, 150th of 735 Content & Media skills we index (top 21%).
Its SKILL.md is 21 KB long, well organised into 37 sections with 1 code example: a thorough specification that gives an agent plenty to work with.
With 4,638 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 2 days ago, so scholarly-writing-refiner is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
scholarly-writing-refiner compared with similar skills
All 4 of these similar skills score higher than scholarly-writing-refiner; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| scholarly-writing-refiner (this skill)by zebbern | 92 | 4.6k | 2d ago | SKILL.md |
| LocalAIby mudler | 100 | 49.3k | today | MCP Server |
| siyuanby siyuan-note | 100 | 46.5k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 5d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 5d ago | SKILL.md |
Frequently asked questions
- How do I install scholarly-writing-refiner?
- Run
npx skills add zebbern/claude-code-guide --skill scholarly-writing-refiner. The install tabs above show the steps for each supported agent. - Which AI agents does scholarly-writing-refiner work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is scholarly-writing-refiner safe to use?
- It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is scholarly-writing-refiner still maintained?
- The repository was last updated 2 days ago, so scholarly-writing-refiner is actively maintained.
Skill content
View source on GitHubname: scholarly-writing-refiner description: "Polishes academic English paragraph by paragraph, reviewing grammar, word choice, voice, coherence, and sentence structure. Outputs revision suggestions alongside polished text. Triggered by phrases like 'polish this paragraph,' 'check the grammar,' 'rewrite in academic English,' or keywords like manuscript editing, SCI polishing, and journal submission editing." license: MIT
Scholarly Writing Refiner — Academic Paper English Polishing Knowledge Base
Helps users review and polish English papers paragraph by paragraph according to international academic journal standards. Covers grammar correction, academic word choice optimization, voice normalization, coherence strengthening, sentence variety, and more. Outputs revision suggestions along with the polished text.
Quick Start
Users only need to provide:
- Text to polish: One or more paragraphs of English paper content
- Paper type (optional): Journal article / Conference paper / Thesis or dissertation / Review article
- Target journal/field (optional): e.g., Nature, IEEE, AAAI, Medicine, Computer Science, etc.
- Polishing focus (optional): Comprehensive polish / Grammar only / Word choice only / Coherence only
Example:
"Polish this Introduction for me. The target venue is NeurIPS, and I'd like the language to sound more natural with better logical flow."
1. Review Dimensions Overview
Polishing is carried out across 5 dimensions. Each dimension is rated independently with specific revision suggestions:
| Dimension | Label | Review Focus | |-----------|-------|-------------| | Grammar | Grammar | Subject-verb agreement, tense, articles, prepositions, clause structure, punctuation | | Word Choice | Word Choice | Academic register, precision, collocation, avoidance of colloquialisms | | Voice | Voice & Tense | Active/passive voice selection, tense consistency | | Coherence | Coherence & Cohesion | Intra-paragraph and inter-paragraph transitions, argumentation chain, use of signaling words | | Sentence Structure | Sentence Structure | Sentence variety, balance of long and short sentences, coordination and subordination |
2. Grammar Review Rules
2.1 Common Grammar Errors Checklist
| Error Type | Incorrect Example | Correction | Explanation | |-----------|------------------|------------|-------------| | Subject-verb disagreement | The results of the experiment shows... | The results of the experiment show... | Subject is "results" (plural) | | Missing/misused article | We propose method to solve... | We propose a method to solve... | Singular countable nouns require an article | | Dangling modifier | Using the proposed method, the accuracy was improved. | Using the proposed method, we improved the accuracy. | The implied subject of a participial phrase must match the main clause subject | | Run-on sentence | The model performs well , it achieves 95% accuracy. | The model performs well**;** it achieves 95% accuracy. / The model performs well**. It** achieves 95% accuracy. | A comma cannot join two independent clauses | | Incomplete comparison | Our method is more efficient. | Our method is more efficient than the baseline. | Comparatives require an explicit object of comparison | | Broken parallelism | The system can detect, classify, and is able to segment... | The system can detect, classify, and segment... | Coordinated elements must share the same grammatical form | | that/which confusion | The model which we proposed... | The model that we proposed... | Restrictive relative clauses use "that" | | Irregular plurals | These phenomenon indicate... | These phenomena indicate... | Watch for irregular plural forms |
2.2 Punctuation Rules
| Rule | Correct Usage | Common Mistake | |------|--------------|----------------| | Serial comma (Oxford comma) | A, B**,** and C | A, B and C (the Oxford comma is recommended in academic writing) | | Em dash | We used three models — A, B, and C — for comparison. | An em dash with spaces on both sides, or without spaces (depends on journal style) | | Capitalization after colon | Capitalize if a complete sentence follows: The result is clear: The model outperforms... | Do not capitalize if a fragment follows | | Quotation marks and periods | American style: period inside quotes. British style: period outside quotes. | Choose based on the target journal's regional convention | | Abbreviation periods | e.g., i.e., et al., etc. | Note the comma: e.g., / i.e., |
2.3 Tense Guidelines by Paper Section
| Section | Recommended Tense | Example | |---------|-------------------|---------| | Abstract | Past tense (what was done) + present tense (conclusions) | "We proposed a method... The results show that..." | | Introduction | Present tense (current knowledge/consensus) + past tense (prior work) | "Deep learning has become... Smith et al. demonstrated that..." | | Methods | Past tense (experimental procedures) | "We trained the model on... The data were preprocessed..." | | Results | Past tense (experimental findings) | "The model achieved 95% accuracy. Table 2 shows..." | | Discussion | Present tense (interpreting significance) + past tense (citing results) | "This result suggests that... Our findings indicated that..." | | Conclusion | Past tense (summarizing work) + present tense (contributions/significance) | "We proposed and evaluated... This work contributes to..." |
3. Word Choice Optimization Rules
3.1 Colloquial → Academic Substitution Table
| Colloquial | Academic Alternative | Context Notes | |-----------|---------------------|---------------| | a lot of | numerous / a substantial number of / considerable | Choose based on what is being modified | | get | obtain / acquire / achieve / attain | Choose based on collocation | | show | demonstrate / illustrate / indicate / reveal | "demonstrate" emphasizes proof; "indicate" emphasizes suggestion | | big / huge | substantial / significant / considerable | | | thing | factor / aspect / element / component | | | good | effective / favorable / advantageous / robust | | | bad | adverse / detrimental / suboptimal / inferior | | | use | employ / utilize / leverage / adopt | "utilize" is more formal than "use"; "leverage" emphasizes exploiting an advantage | | about | approximately / roughly / circa | Use "approximately" for numerical descriptions | | try | attempt / endeavor | | | look at | examine / investigate / analyze / explore | | | find out | determine / ascertain / identify / discover | | | go up / go down | increase / decrease / rise / decline | | | point out | highlight / emphasize / underscore | | | deal with | address / tackle / handle / mitigate | | | make sure | ensure / verify / confirm | | | kind of / sort of | somewhat / to some extent / partially | | | start / begin | initiate / commence / undertake | | | end / finish | conclude / terminate / complete | | | help | facilitate / enable / assist / contribute to | | | need | require / necessitate | | | can | is capable of / is able to / has the potential to | Avoid over-substitution — "can" is acceptable in academic writing |
3.2 Vague → Precise Expression
| Vague Expression | Precise Alternative | Notes | |-----------------|---------------------|-------| | very good results | statistically significant improvement / a 12% increase in accuracy | Replace vague modifiers with concrete data | | some researchers | Several studies (Chen et al., 2023; Li et al., 2024) | Replace vague references with specific citations | | recently | In the past five years / Since 2020 | Provide a time range | | a few | three / a small number of (n=3) | Specify the quantity | | it is known that | Prior work has established that (citation) | Support with a citation | | this is important | This is critical for / This has significant implications for | Explain why it matters |
3.3 Reducing Redundancy
| Redundant Expression | Concise Version | |---------------------|----------------| | in order to | to | | due to the fact that | because / since | | at the present time | currently / now | | it is worth noting that | Notably, / Note that | | it should be pointed out that | (state the content directly) | | a total of 50 samples | 50 samples | | the vast majority of | most | | in the event that | if | | has the ability to | can | | on a daily basis | daily | | in close proximity to | near | | take into consideration | consider | | is in agreement with | agrees with | | serves the function of | functions as |
4. Voice Guidelines
4.1 Active vs. Passive Voice Selection
| Scenario | Recommended Voice | Example | |----------|-------------------|---------| | Describing the authors' actions | Active (We) | We trained the model using... | | Describing general methods/established facts | Passive | The data were collected from... | | Emphasizing the object of an action | Passive | The samples were analyzed using mass spectrometry. | | Reporting results | Prefer active | Our method achieves 95% accuracy. | | Describing equipment/materials | Passive | The solution was heated to 100°C. |
4.2 Common Voice Issues
| Issue | Incorrect Example | Correction | |-------|-------------------|------------| | Overuse of passive | It was found by us that the results were improved by the method. | We found that our method improved the results. | | Inconsistent person | The author proposes... We then evaluate... | Use "We" or "The authors" consistently | | Meaningless passive | It can be seen that accuracy increases. | Accuracy increases. / The results show that accuracy increases. |
4.3 Academic Person Conventions
| Person | Use Case | Notes | |--------|----------|-------| | We | Describing the authors' own work (most common) | Many journals accept "We" even for single-author papers | | The authors | A more formal alternative | Some journals prefer this usage | | I | Single-author theses and dissertations | Some journals do not accept this | | One | Generic/hypothetical statements | Somewhat old-fashioned; less common in modern academic writing |
5. Coherence and Cohesion Rules
5.1 Intra-Paragraph Signaling Words
| Logical Relationship | Signal Words/Phrases | Example | |---------------------|---------------------|---------| | Addition | Furthermore, Moreover, Additionally, In addition | Furthermore, our method generalizes well to unseen data. | | Contrast | However, In contrast, Conversely, On the other hand, Nevertheless | However, this approach suffers from high computational cost. | | Cause & Effect | Therefore, Consequently, As a result, Hence, Thus | Therefore, we adopt a two-stage training strategy. | | Exemplification | For example, For instance, Specifically, In particular | Specifically, we focus on the image classification task. | | Emphasis | Indeed, Notably, Importantly, It is worth noting that | Notably, the improvement is consistent across all datasets. | | Concession | Although, Despite, Notwithstanding, While, Even though | Although the model is simple, it achieves competitive results. | | Summary | In summary, To summarize, Overall, In conclusion | Overall, the proposed method outperforms existing baselines. | | Qualification | Yet, Still, Nonetheless, That said | That said, there are several limitations to our approach. | | Sequence | First, Second, Finally, Subsequently, Then | First, we preprocess the data. Subsequently, we train the model. | | Condition | If, Provided that, Given that, Assuming that | Given that the dataset is imbalanced, we apply oversampling. |
5.2 Inter-Paragraph Transition Patterns
| Pattern | Description | Example Opening Sentence | |---------|-------------|--------------------------| | Hook | The end of one paragraph leads into the next topic | "This raises
Truncated for display — read the full file on GitHub.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
