Agent skill

Conciseness Editing Guide

by wentorai in wentorai/research-plugins

Eliminate wordiness and redundancy in academic prose for clarity

MITAuto-check passedWriting & Content

Install Conciseness Editing Guide

skills CLI
$ npx skills add wentorai/research-plugins --skill conciseness-editing-guide -a claude-code

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

GitHub CLI
$ gh skill install wentorai/research-plugins conciseness-editing-guide --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/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/writing/polish/conciseness-editing-guide .claude/skills/conciseness-editing-guide && 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
conciseness-editing-guide
GitHub stars
298
Used in
1 other repo
Token cost
~2.1k tokens
SKILL.md length
265 words
Files
1
Skills in repo
405
Repo updated
First seen
Licence
MIT

At a glance

Eliminate wordiness and redundancy in academic prose for clarity

  • Writing & Content work in your project
  • SKILL.md covers Why Conciseness Matters in…, Common Wordiness Patterns, Sentence-Level Compression… and Paragraph-Level Strategies, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Conciseness Editing Guide is an agent skill from wentorai/research-plugins. Eliminate wordiness and redundancy in academic prose for clarity

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Writing & Content. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.

When your agent uses it

  • Writing & Content work in your project

Example prompts

  • “/conciseness-editing-guide”

What it can do on your machine

Read from SKILL.md and the folder at commit bf44b3c. 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

Conciseness Editing Guide loads about 2.1k tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 265 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~23
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

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 wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 265 words, ~2,067 tokens.

Download SKILL.mdSave it as .claude/skills/conciseness-editing-guide/SKILL.md (or your agent's skills folder).
name
conciseness-editing-guide
description
Eliminate wordiness and redundancy in academic prose for clarity

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.

© wentorai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/writing/polish/conciseness-editing-guide of wentorai/research-plugins.

Open the folder on GitHubat commit bf44b3c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Questions about Conciseness Editing Guide

What does Conciseness Editing Guide do?

Eliminate wordiness and redundancy in academic prose for clarity. Conciseness Editing Guide is an agent skill from wentorai/research-plugins.

When should I use Conciseness Editing Guide?

Conciseness Editing Guide fits situations like: writing & Content work in your project.

How do I install Conciseness Editing Guide in Claude Code?

Run `npx skills add wentorai/research-plugins --skill conciseness-editing-guide -a claude-code`. Or copy the skill folder (skills/writing/polish/conciseness-editing-guide in wentorai/research-plugins) into .claude/skills/conciseness-editing-guide in your project. Claude Code loads it when a task matches its description.

How do I install Conciseness Editing Guide in Codex?

Run `npx skills add wentorai/research-plugins --skill conciseness-editing-guide -a codex`. Or copy the skill folder (skills/writing/polish/conciseness-editing-guide in wentorai/research-plugins) into .agents/skills/conciseness-editing-guide in your project. Codex loads it when a task matches its description.

Can I use Conciseness Editing Guide 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 wentorai/research-plugins --skill conciseness-editing-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/conciseness-editing-guide, .gemini/skills/conciseness-editing-guide, .github/skills/conciseness-editing-guide and .opencode/skills/conciseness-editing-guide in your project.

What does Conciseness Editing Guide need to run?

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

Does Conciseness Editing Guide 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 Conciseness Editing Guide 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 Conciseness Editing Guide use?

Conciseness Editing Guide 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 Conciseness Editing Guide use?

About 2.1k tokens (SKILL.md is roughly 8.3k 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 Conciseness Editing Guide?

Skills that share tags, products or a category with Conciseness Editing Guide: Social (coreyhaines31/marketingskills, 54k stars), Humanizer (Azure-Samples/interview-coach-agent-framework, 172 stars), Avoid AI Writing (conorbronsdon/avoid-ai-writing, 4.9k stars) and JavaScript Concept Fact Checker (leonardomso/33-js-concepts, 67k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Conciseness Editing Guide?

wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.

Source: wentorai/research-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.