conciseness-editing-guide
Eliminate wordiness and redundancy in academic prose for clarity
Best use case
conciseness-editing-guide is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Eliminate wordiness and redundancy in academic prose for clarity
Teams using conciseness-editing-guide should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/conciseness-editing-guide/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How conciseness-editing-guide Compares
| Feature / Agent | conciseness-editing-guide | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Eliminate wordiness and redundancy in academic prose for clarity
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Conciseness Editing Guide
A skill for systematically eliminating wordiness, redundancy, and unnecessary complexity in academic writing. Covers common verbosity patterns, sentence-level compression techniques, paragraph restructuring strategies, and methods for reducing word count while preserving meaning and nuance.
## Why Conciseness Matters in Academia
Academic papers face strict word or page limits. Reviewers read hundreds of papers and reward clarity. Verbose writing obscures arguments, frustrates readers, and often signals muddled thinking. A concise paper communicates more ideas per page, leaving room for additional analysis, examples, or discussion. Journals frequently reject manuscripts that exceed length limits, and reviewers regularly cite "needs tightening" as a criticism.
## Common Wordiness Patterns
### Expletive Constructions
Expletive constructions begin sentences with "It is" or "There are" followed by a delayed subject. They add words without adding meaning.
```
Pattern: "It is/was... that/who..."
Before: "It is well established that climate change affects
biodiversity in tropical regions."
After: "Climate change affects biodiversity in tropical regions
(Smith, 2019; Jones, 2020)."
Saved: 5 words
Before: "There are several factors that contribute to the
observed variance in student performance."
After: "Several factors contribute to the observed variance
in student performance."
Saved: 2 words
Before: "It was found that the treatment group showed a
significant improvement in test scores."
After: "The treatment group showed a significant improvement
in test scores."
Saved: 4 words
```
### Nominalizations
Nominalizations convert verbs into nouns, requiring additional supporting verbs and prepositions. They make prose heavy and indirect.
```
Pattern: Verb -> Noun + "of/for/in"
Before: "We performed an investigation of the relationship
between temperature and reaction rate."
After: "We investigated the relationship between temperature
and reaction rate."
Saved: 3 words
Before: "The implementation of the algorithm resulted in an
improvement of processing speed."
After: "Implementing the algorithm improved processing speed."
Saved: 6 words
Before: "The utilization of machine learning for the
classification of cell types has increased."
After: "Using machine learning to classify cell types has
become more common."
Saved: 3 words
Common nominalizations to avoid:
- utilization -> use
- implementation -> implementing
- investigation -> investigating
- establishment -> establishing
- demonstration -> demonstrating
- facilitation -> facilitating
```
### Redundant Pairs and Phrases
```
Redundant pairs (drop one):
- "each and every" -> "each" or "every"
- "first and foremost" -> "first"
- "various and diverse" -> "various" or "diverse"
- "completely and totally" -> "completely" or "totally"
Redundant modifiers:
- "past history" -> "history"
- "future plans" -> "plans"
- "end result" -> "result"
- "final outcome" -> "outcome"
- "basic fundamentals" -> "fundamentals"
- "advance planning" -> "planning"
- "true fact" -> "fact"
- "consensus of opinion" -> "consensus"
```
## Sentence-Level Compression Techniques
### Prepositional Phrase Reduction
Long chains of prepositional phrases ("of the", "in the", "for the") inflate word counts and reduce readability.
```
Before: "The analysis of the distribution of the data from
the experiment on the effects of temperature on
the growth rate of the bacteria showed..."
After: "Analyzing the experimental data on temperature's
effect on bacterial growth rate showed..."
Saved: 10 words
Strategy: Convert "of the X" to possessive or adjective form
- "the results of the experiment" -> "the experimental results"
- "the behavior of the system" -> "the system's behavior"
- "the members of the committee" -> "the committee members"
```
### Wordy Phrases to Concise Alternatives
```
Wordy Concise
--------------------------------- ----------------
"in order to" "to"
"due to the fact that" "because"
"in spite of the fact that" "although"
"at the present time" "currently" / "now"
"a large number of" "many"
"a small number of" "few"
"in the event that" "if"
"has the ability to" "can"
"is able to" "can"
"it is necessary that" "must"
"for the purpose of" "to" / "for"
"with regard to" "regarding" / "about"
"in the vicinity of" "near"
"on a daily basis" "daily"
"the majority of" "most"
"a sufficient amount of" "enough"
"in close proximity to" "near"
"take into consideration" "consider"
"has an impact on" "affects"
"conduct an analysis of" "analyze"
"make a decision" "decide"
"give an indication of" "indicate"
"is in agreement with" "agrees with"
"on the basis of" "based on"
```
## Paragraph-Level Strategies
### Eliminating Throat-Clearing
Many paragraphs begin with one or two sentences that announce what the paragraph will say rather than saying it. Cut these.
```
Before: "In this section, we will now turn our attention to the
results of the statistical analysis. The results are
presented below and discussed in detail. Table 3 shows
the regression coefficients for Model 1."
After: "Table 3 shows the regression coefficients for Model 1."
Saved: 27 words (the table speaks for itself)
```
### Merging Short Paragraphs
Multiple short paragraphs covering the same point should be consolidated. Each paragraph should develop one idea fully.
```
Before:
"We used logistic regression.
The dependent variable was binary.
We included age, gender, and income as covariates.
The model was estimated using maximum likelihood."
After:
"We estimated a logistic regression with a binary dependent
variable, including age, gender, and income as covariates,
using maximum likelihood estimation."
```
## Systematic Editing Workflow
### The Three-Pass Method
```
Pass 1 - Word Level (search and replace):
1. Search for "in order to" -> replace with "to"
2. Search for "due to the fact" -> replace with "because"
3. Search for "it is" at sentence starts -> restructure
4. Search for "-tion of" -> consider converting to verb form
5. Search for "very", "really", "quite" -> delete or find precise word
Pass 2 - Sentence Level (read each sentence):
1. Can any sentence be split or merged?
2. Does every clause add information?
3. Are there unnecessary qualifiers?
4. Can passive be converted to active (saving 1-2 words)?
Pass 3 - Paragraph Level (read each paragraph):
1. Does the first sentence do real work?
2. Is anything repeated from the previous paragraph?
3. Can two paragraphs be merged?
4. Does the paragraph earn its place in the paper?
```
### Word Count Targets
```
Typical reductions achievable:
First draft -> Second draft: 15-25% reduction
Second draft -> Final: 5-10% reduction
Total achievable: 20-30% reduction without losing content
If your paper is 8,000 words and the limit is 6,000:
You need a 25% reduction -- achievable with systematic editing.
Focus on the introduction and discussion first (most verbose).
Methods and results tend to be already concise.
```
By applying these techniques systematically, researchers can typically cut 20 to 30 percent of their word count without removing any substantive content, resulting in clearer, more impactful manuscripts that reviewers and readers appreciate.Related Skills
thuthesis-guide
Write Tsinghua University theses using the ThuThesis LaTeX template
thesis-writing-guide
Templates, formatting rules, and strategies for thesis and dissertation writing
thesis-template-guide
Set up LaTeX templates for PhD and Master's thesis documents
sjtuthesis-guide
Write SJTU theses using the SJTUThesis LaTeX template with full compliance
novathesis-guide
LaTeX thesis template supporting multiple universities and formats
graphical-abstract-guide
Create SVG graphical abstracts for journal paper submissions
beamer-presentation-guide
Guide to creating academic presentations with LaTeX Beamer
plagiarism-detection-guide
Use plagiarism detection tools and ensure manuscript originality
paper-polish-guide
Review and polish LaTeX research papers for clarity and style
grammar-checker-guide
Use grammar and style checking tools to polish academic manuscripts
academic-translation-guide
Academic translation, post-editing, and Chinglish correction guide
academic-tone-guide
Adjust writing tone and register for academic audiences and venues