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12-agent academic paper writing pipeline. 11 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure/rebuttal-audit). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, I got reviewer comments, revision roadmap, should we push back, conference rebuttal, grant panel response, audit my rebuttal, check my response draft, AI disclosure, check citations, citation check, check my references, verify references, look over the refs, 寫論文, 學術論文, 引導我寫論文, 審查意見, 我收到審查意見, 修訂路線圖, 評估回覆, 檢查引用, 引用檢查, 檢查參考文獻, 核對文獻, 논문 작성, 초록 작성, 논문 수정, 논문 계획을 도와줘, 심사 의견을 받았어, 심사 의견 반영, 답변서 점검, AI 사용 고지, 인용 확인, 인용 형식 검사, enmendar mi artículo, redactar artículo, guía mi artículo, analizar reseñas, auditar mi respuesta, verificar borrador de respuesta, verificar citas, divulgación de IA.

Use this Skill: https://skilld.dev/gh/imbad0202/academic-research-skills/academic-paper

This session only. Nothing lands on disk.

referencesacademic_writing_style.md

≈1.9k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Academic Writing Style Guide

Used by draft_writer_agent and peer_reviewer_agent.

Core Principles

1. Precision

  • Use the most specific term available
  • Define technical terms on first use
  • Avoid ambiguous pronouns ("this," "it") without clear antecedents

2. Conciseness

  • Eliminate filler words and redundant phrases
  • One idea per sentence (or clearly connected ideas)
  • Prefer short sentences for complex ideas

3. Objectivity

  • Base claims on evidence, not opinion
  • Use hedging for uncertain claims
  • Acknowledge limitations and alternative interpretations

4. Formality

  • Use full forms ("do not" over "don't")
  • Use formal academic vocabulary; reserve colloquialisms and slang for informal writing
  • Use third person unless discipline conventions allow first person

Register Adjustment by Discipline

Sciences (Natural, Applied)

Register: Formal, impersonal, method-focused
Voice: Passive voice common ("was measured," "were analyzed")
Terminology: Precise measurements, SI units, statistical notation
Example: "The sample was heated to 350°C for 2 hours, yielding a conversion rate of 87.3% (SD = 2.1)."

Social Sciences

Register: Formal, theory-informed, participant-aware
Voice: Active voice encouraged, first person for researcher decisions
Terminology: Theoretical constructs, operationalized variables
Example: "We employed semi-structured interviews to explore how participants understood institutional change (N = 24)."

Humanities

Register: Formal, argument-driven, interpretive
Voice: First person acceptable for arguments, active voice
Terminology: Close reading vocabulary, theoretical language
Example: "I argue that the text's spatial metaphors reveal an underlying anxiety about institutional permanence."

Engineering / CS

Register: Formal, problem-solution oriented, specification-precise
Voice: Passive common for methods, active for contributions
Terminology: Technical specifications, performance metrics
Example: "The proposed algorithm achieves O(n log n) complexity, outperforming the baseline by 34% on the benchmark dataset."

Education

Register: Formal, practice-oriented, stakeholder-aware
Voice: Active voice, first person for reflexive practice
Terminology: Pedagogical concepts, assessment language
Example: "The intervention improved student metacognitive awareness, as evidenced by a significant increase in self-regulation scores (t(45) = 3.21, p = .002, d = 0.72)."

Medicine / Health

Register: Formal, evidence-hierarchy conscious, clinical precision
Voice: Passive for methods, active for findings
Terminology: Clinical terms, diagnostic criteria, statistical reporting
Example: "Patients receiving the intervention showed a 40% reduction in readmission rates (RR = 0.60, 95% CI [0.45, 0.80], p = .001)."

Hedging and Strength Language

Hedging (for uncertain or qualified claims)

Strength Hedging Devices Example
Weak may, might, could, possibly "This may suggest a correlation."
Moderate suggests, indicates, appears "The data suggest a positive trend."
Strong demonstrates, establishes, confirms "The evidence demonstrates a clear link."

When to Hedge

  • Results that need replication
  • Causal claims from correlational data
  • Generalizations from limited samples
  • Interpretations with alternative explanations

When NOT to Hedge

  • Reporting factual data: "The response rate was 78%." (not "appeared to be")
  • Describing methodology: "We used thematic analysis." (not "we attempted to use")
  • Well-established facts: "Earth orbits the Sun." (not "may orbit")

Transition Words and Phrases

Addition

moreover, furthermore, in addition, additionally, similarly, likewise

Contrast

however, nevertheless, in contrast, on the other hand, conversely, whereas

Cause/Effect

therefore, consequently, as a result, thus, hence, accordingly

Example

for example, for instance, specifically, in particular, such as, namely

Sequence

first, second, third, subsequently, finally, meanwhile

Summary

in summary, to conclude, overall, taken together, in short

Concession

although, despite, while, granted that, notwithstanding

Paragraph Construction

A Common Academic Paragraph Shape (TEEL, optional)

  1. Topic sentence — states the paragraph's main point
  2. Evidence — data, citations, examples that support the point
  3. Explanation — interpret the evidence, connect to argument
  4. Link — connect to the next paragraph or back to thesis

Example

[T] AI-assisted quality assurance has shown promise in improving evaluation consistency across institutions. [E] Smith (2024) found that institutions using AI tools reported a 23% reduction in inter-rater variance, while Chen and Wang (2023) documented improved agreement on scoring rubrics (κ = 0.82 vs. 0.64). [E] These findings suggest that algorithmic assistance can mitigate the subjective biases inherent in human evaluation, particularly when assessors have varying levels of experience. [L] However, the reliance on AI tools also raises concerns about the loss of contextual judgment, which the following section addresses.

Common Style Errors

Wordiness

Wordy Concise
in order to to
due to the fact that because
a large number of many
at the present time currently / now
it is important to note that notably
in the event that if
has the ability to can
with regard to regarding / about
in spite of the fact that despite / although
conduct an investigation of investigate

Vague Language

Vague Precise
"many studies" "several studies (e.g., Chen, 2023; Smith, 2024)"
"a significant impact" "a 23% increase in retention rates"
"in recent years" "since 2020" or "over the past five years"
"some researchers" Name them with citations
"it is well known that" Cite the source or remove

Tense Usage

Section Tense Example
Literature review (reporting findings) Past "Smith (2024) found that..."
Literature review (ongoing state) Present "The theory posits that..."
Methodology Past "Data were collected through..."
Results Past "The analysis revealed..."
Discussion (interpreting) Present "These findings suggest..."
Conclusion (implications) Present/Future "This has implications for... / Future research should..."

Chinese Academic Writing (zh-TW) Conventions

Register

  • Use written/formal language; avoid colloquial expressions
  • Prefer active voice (Chinese rarely uses passive)
  • Mainly short sentences; avoid overly long subordinate clauses
  • Use "this study" (ben yan jiu) rather than "we" (wo men)

Common Academic Expressions

English Romanized Chinese
This study aims to Ben Yan Jiu Zhi Zai
The findings indicate Yan Jiu Jie Guo Xian Shi
It is worth noting Zhi De Zhu Yi De Shi
In conclusion Zong Shang Suo Shu
Based on the above analysis Gen Ju Shang Shu Fen Xi
Further research is needed Wei Lai Yan Jiu Ke Jin Yi Bu Tan Tao

Avoiding Translationese

  • Incorrect: "was found to be" (bei fa xian shi) → Correct: "Results show" (jie guo xian shi)
  • Incorrect: "This is because" (zhe shi yin wei) → Correct: "The reason lies in" (yuan yin zai yu)
  • Incorrect: "In the aspect of..." (zai...fang mian) → Correct: State directly
  • Incorrect: "It is worth being pointed out that" (zhi de bei zhi chu de shi) → Correct: "It is worth noting that" (zhi de zhu yi de shi)

Source: SKILL.md on GitHub

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    This skill provides a highly structured 12-agent academic paper writing pipeline. It contains robust internal defenses, including explicit 'instruction-data' boundaries and sanitization of user-provided content. However, the skill's complexity, its reliance on shell command execution for document processing and utility scripts, and its heavy ingestion of untrusted third-party materials (such as reviewer comments and external research content) present a surface for potential misuse and indirect prompt injection.

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Signed by skilld at c5c1b45. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

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Activeupdated 2 days ago
Other metadata
metadata
{
  "version": "3.3.1",
  "last_updated": "2026-08-15",
  "status": "active",
  "data_access_level": "raw",
  "task_type": "open-ended",
  "related_skills": [
    "deep-research",
    "academic-paper-reviewer",
    "academic-pipeline"
  ]
}

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