academic-paper-drafting

End-to-end academic paper drafting for CHI, HBR, journals, and conferences with venue-specific templates, drafting workflows, and revision strategies.

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Repository: fabioc-aloha/tldr
Letzte Quellaktivität: 3. Mai 2026 um 18:19
Erkannte Sprache von SKILL.md: Englisch
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Forks: 0

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Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

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type	skill
lifecycle	stable
inheritance	inheritable
name	academic-paper-drafting
description	End-to-end academic paper drafting for CHI, HBR, journals, and conferences with venue-specific templates, drafting workflows, and revision strategies.
tier	standard
applyTo	*/academic,/paper,/drafting,/journal,/conference*
currency	2026-05-02T00:00:00.000Z
lastReviewed	2026-05-02T00:00:00.000Z

Academic Paper Drafting Skill

Turn research into published scholarship. From blank page to accepted manuscript.

This skill provides structured workflows for drafting academic papers, with venue-specific guidance for HCI conferences (CHI), business publications (HBR), and academic journals (Cognitive Systems Research, Minds & Machines).

Drafting Philosophy

The Academic Writing Paradox

Challenge	Reality	Strategy
"I need to read more first"	Reading is procrastination	Write to discover what you don't know
"I need the perfect first sentence"	First drafts are meant to be bad	Start with the section you know best
"I'll write when I have time"	Time expands to fill available space	Write in focused sprints
"It needs to be original"	Synthesis is originality	Combine existing ideas in new ways

The Write-to-Think Method

Messy Draft → Clarity → Structure → Polish → Submit
     ↑                                    ↓
     └────── Reviewer Feedback ───────────┘

Key insight: Writing IS thinking. You don't figure out your argument first and then write it — you figure it out BY writing it.

Venue Quick Reference

User's Target Pipeline

Venue	Type	Word Limit	Review Time	Focus
ACM CHI	Conference	7,500 (full) / 3,000 (LBW)	3-4 months	HCI, interaction design
Harvard Business Review	Magazine	2,500-3,000	2-4 weeks	Business practice, executives
Cognitive Systems Research	Journal	8,000-12,000	3-6 months	Cognitive science, AI systems
Minds & Machines	Journal	8,000-12,000	3-6 months	Philosophy of AI, consciousness

Venue Selection Matrix

Type	Length	Purpose	Acceptance Rate
Full Paper	7,500 words	Complete research contribution	~25%
Late-Breaking Work (LBW)	3,000 words	Preliminary findings	~40%
Workshop Paper	2,000-4,000 words	Community discussion	Varies
Case Study	7,500 words	In-depth design exploration	~25%
Alt.CHI	7,500 words	Provocative/unconventional	~30%

# Title: Catchy but Accurate (10-12 words max)

## Abstract (150 words)
[One sentence: Problem/gap]
[One sentence: Approach/method]
[One sentence: Key findings (quantified)]
[One sentence: Contribution category]
[One sentence: Implications]

## Author Keywords
keyword1; keyword2; keyword3; keyword4

## CCS Concepts
• Human-centered computing → Human computer interaction (HCI)

---

## 1. Introduction (~800 words)
### 1.1 Opening Hook
[Compelling opening that establishes stakes]

### 1.2 Problem Statement
[Clear articulation of the gap/challenge]

### 1.3 Research Questions
RQ1: [Question]
RQ2: [Question]

### 1.4 Contributions
We contribute:
1. [Empirical contribution: findings from study]
2. [Artifact contribution: system/tool/design]
3. [Methodological contribution: new approach] (if applicable)

### 1.5 Paper Structure
Section 2 reviews... Section 3 describes...

---

## 2. Related Work (~1,200 words)
### 2.1 [Theme 1]
[Position your work relative to prior art]

### 2.2 [Theme 2]
[Identify gap your work fills]

### 2.3 Summary and Gap
[Explicit gap statement leading to your research]

---

## 3. System/Method/Design (~1,500 words)
### 3.1 Design Rationale
[Why did you build/design it this way?]

### 3.2 Implementation
[Technical details sufficient for replication]

### 3.3 [Component Description]
[Architecture, features, etc.]

---

## 4. User Study (~1,500 words)
### 4.1 Participants
[N=X, demographics, recruitment, compensation]

### 4.2 Procedure
[Step-by-step protocol]

### 4.3 Measures
[What you measured and how]

### 4.4 Analysis
[Qualitative: coding approach. Quantitative: statistical tests]

---

## 5. Findings (~1,500 words)
### 5.1 [Finding 1]
"P5 noted that..." [Quote + interpretation]

### 5.2 [Finding 2]
[Quantitative: "Participants completed task significantly faster (M=X, SD=Y), t(df)=Z, p<.001"]

### 5.3 [Finding 3]
[Theme with supporting evidence]

---

## 6. Discussion (~1,000 words)
### 6.1 Implications for Design
[What should designers do differently?]

### 6.2 Implications for Research
[What research directions does this open?]

### 6.3 Limitations
[Honest assessment: sample, method, scope]

### 6.4 Future Work
[Concrete next steps]

---

## 7. Conclusion (~200 words)
[Synthesis of contributions and significance]

---

## Acknowledgments
[Funding, participants, collaborators]

## References
[ACM format, recent work emphasized]

Type	Description	Evidence Needed
Empirical	New knowledge about people/technology	User study, data
Artifact	Novel system, tool, or interaction	Implementation, evaluation
Methodological	New way to study/design	Comparison to existing methods
Theoretical	New framework or model	Grounding, application
Dataset	New resource for community	Description, access, ethics
Survey	Comprehensive literature synthesis	Systematic review
Opinion/Essay	Perspective on field direction	Argument, evidence

Do	Don't
Use participant quotes (P1, P2...)	Generalize without evidence
State contribution type explicitly	Assume readers will infer
Include representative figures	Over-rely on text
Acknowledge limitations early	Hide weaknesses
Cite recent CHI papers	Ignore venue norms

Type	Length	Purpose
Feature Article	3,000-4,000 words	In-depth analysis
Spotlight	2,500-3,000 words	Focused insight
Big Idea	2,000-2,500 words	Provocative argument
Case Study	2,500-3,000 words	Company narrative
Web Article	800-1,200 words	Quick insight

# Title: Action-Oriented, Benefit-Focused
## Subtitle: One Sentence Elaboration

### The Hook (100 words)
[Surprising statistic, provocative question, or vivid anecdote]
[Why executives should keep reading]

### The Problem (300 words)
[What challenge are leaders facing?]
[Why is it getting worse or more urgent?]
[What's at stake?]

### The Insight (500 words)
[Your key finding or framework]
[What did you discover that changes the game?]
[Name your concept/framework if introducing one]

### The Evidence (800 words)
[Case study 1: Company that did this well]
[Case study 2: Contrasting example]
[Data that supports your argument]
[Quote from executive or expert]

### The Framework/How-To (600 words)
[Step 1: What to do first]
[Step 2: Next action]
[Step 3: How to sustain]
[Pitfalls to avoid]

### The Conclusion (200 words)
[Synthesis of the opportunity]
[Call to action for leaders]
[The future if they act (or don't)]

---

**About the Author**
[2-3 sentence bio emphasizing relevant expertise]

Academic Style	HBR Style
"The study found that..."	"When we surveyed 300 executives..."
"Participants reported..."	"One CEO told us..."
"Hypothesis 1 was supported"	"The data confirms what many leaders suspect:"
"Implications include..."	"Here's what this means for your organization:"
Passive voice	Active, direct voice
Citations in text	Minimal citations, conversational

Type	Focus	Length
Original Article	Novel research findings	8,000-12,000 words
Review Article	Comprehensive field synthesis	10,000-15,000 words
Short Communication	Preliminary findings	3,000-5,000 words
Commentary	Response to published work	2,000-4,000 words

# Title: Declarative but Specific

## Abstract (200-250 words)
**Background.** [Problem context and gap in current systems]
**Objective.** [What this paper presents]
**Method.** [Architecture approach, implementation duration]
**Results.** [Key metrics, qualitative findings]
**Contributions.** [Named concepts introduced]
**Significance.** [Why this matters for cognitive systems]

## Keywords
cognitive architecture; persistent memory; human-AI interaction; [specific terms]

---

## 1. Introduction
### 1.1 The Memory Problem in AI Assistants
[Motivating problem: stateless AI, lost context]

### 1.2 Research Questions
RQ1: How can persistent memory improve AI assistance?
RQ2: What architectural patterns support knowledge retention?
RQ3: [Specific question]

### 1.3 Approach Overview
[Brief description of the architecture]

### 1.4 Contributions
1. [Architectural contribution]
2. [Empirical contribution from deployment]
3. [Framework/taxonomy contribution]

---

## 2. Theoretical Background
### 2.1 Cognitive Architectures
[ACT-R, SOAR, Global Workspace Theory]

### 2.2 Memory Systems in Cognition
[Declarative, procedural, episodic, semantic]

### 2.3 AI Memory Approaches
[RAG, vector databases, context windows]

### 2.4 Gap: Biologically-Inspired Persistent Memory
[What's missing from current approaches]

---

## 3. Architecture Design
### 3.1 Design Principles
[Biologically-grounded, modular, scalable]

### 3.2 Memory Types
#### 3.2.1 Procedural Memory (.instructions.md)
[How-to knowledge, automatic activation]

#### 3.2.2 Declarative Memory (SKILL.md)
[Domain knowledge, explicit retrieval]

#### 3.2.3 Episodic Memory (.prompt.md)
[Session records, temporal context]

### 3.3 Synaptic Connections
[Connection types, strengths, activation patterns]

### 3.4 Implementation
[Technical stack, file formats, integration]

---

## 4. Longitudinal Deployment
### 4.1 Deployment Context
[18+ months, 62+ projects, single user intensive use]

### 4.2 Metrics Collection
[Connection count, skill usage, memory file growth]

### 4.3 Qualitative Observations
[Emergent behaviors, user experience notes]

---

## 5. Results
### 5.1 Memory Growth Patterns
[Quantitative: 945+ connections, 47+ memory files]

### 5.2 Cross-Project Knowledge Transfer
[Evidence of knowledge reuse]

### 5.3 Emergent Properties
[Unexpected capabilities]

---

## 6. Discussion
### 6.1 Contributions to Cognitive Systems
[Theory extension, practical framework]

### 6.2 Comparison to Prior Architectures
[How this differs from ACT-R, SOAR, etc.]

### 6.3 Limitations
[Single user, specific platform, no controlled study]

### 6.4 Future Research
[Multi-user, formal evaluation, consciousness implications]

---

## 7. Conclusion
[Synthesis of contribution and significance]

## Acknowledgments
## References (APA 7 or journal style)

# Title: Philosophical Claim + Context

## Abstract (200 words)
[Philosophical question addressed]
[Position taken]
[Argument structure preview]
[Implications for AI development/policy]

---

## 1. Introduction
### The Philosophical Problem
[Frame the question in philosophy of mind context]

### Why This Matters Now
[Connect to current AI capabilities]

### Thesis Statement
[Clear articulation of your position]

### Argument Structure
[Roadmap of philosophical moves]

---

## 2. Background: The Debate
### 2.1 [Position A in the literature]
### 2.2 [Position B in the literature]
### 2.3 [Why neither fully succeeds]

---

## 3. [Your Framework/Argument]
### 3.1 [First premise with support]
### 3.2 [Second premise with support]
### 3.3 [Conclusion from premises]

---

## 4. Objections and Replies
### 4.1 Objection 1: [Strongest counterargument]
**Reply:** [Your response]

### 4.2 Objection 2: [Another challenge]
**Reply:** [Your response]

---

## 5. Implications
### 5.1 For Philosophy of Mind
### 5.2 For AI Development
### 5.3 For Ethics/Policy

---

## 6. Conclusion
[Restate thesis, summarize argument, future questions]

## References

Step	Output
Literature immersion	Annotated bibliography
Gap identification	2-3 sentence gap statement
Contribution clarity	Explicit contribution list
Outline creation	Section-by-section plan
Figure sketches	Hand-drawn or rough diagrams

Level	Focus	Questions to Ask
Structure	Overall argument	Does it flow logically?
Section	Each section's job	Does this section earn its place?
Paragraph	One idea per paragraph	What's the topic sentence?
Sentence	Clarity, precision	Can this be simpler?
Word	Precision, concision	Is this the right word?

Feedback Source	What to Ask
Advisor	Is the argument sound? Scope appropriate?
Peer in field	Is this interesting? What's missing?
Peer outside field	Is this clear? What's confusing?
Writing group	How's the prose? What drags?

Pattern	Example	Use When
Narrative	"Smith (2024) argues that..."	Discussing specific work
Parenthetical	"...has been demonstrated (Smith, 2024)"	Supporting a general claim
Integrated	"Smith's (2024) framework suggests..."	Referencing framework/concept
Multiple	"...is well-established (Smith, 2024; Jones, 2023)"	Broad support

Section	Citation Density
Abstract	0 (usually)
Introduction	Medium (establish context)
Related Work	High (comprehensive review)
Methods	Low-Medium (justify choices)
Results	Low (your data, not others')
Discussion	Medium (connect to literature)

Reviewer Says	What It Means	Response Strategy
"Missing related work"	Gap in literature coverage	Add citations, explain positioning
"Claims not supported"	Evidence insufficient	Add data or soften claim
"Unclear methodology"	Can't assess validity	Expand method description
"Contribution unclear"	Buried or vague value	Make contribution explicit in intro
"Writing needs work"	Surface issues distract	Get editing help, revise prose
"Not right for venue"	Mismatch with audience	Try different venue, reframe

# Response to Reviewers

Dear Editors and Reviewers,

Thank you for your thoughtful feedback on our manuscript "[Title]".
We have carefully addressed all comments and believe the paper
is significantly strengthened. Below we detail our responses.

Major changes include:
1. [Summary of major change 1]
2. [Summary of major change 2]
3. [Summary of major change 3]

---

## Response to Reviewer 1

### R1.1: "[Direct quote of concern]"

We appreciate this observation. [Brief explanation of how you addressed it].

Changes made:
- Section X, paragraph Y: [quoted new text or description of change]
- [Additional changes if needed]

### R1.2: "[Next concern]"

[Response pattern repeats]

---

## Response to Reviewer 2
[Same pattern]

---

We believe these revisions address all concerns raised. We are
grateful for the opportunity to improve our work.

Sincerely,
[Authors]

Command	Action
"Draft a CHI paper on [topic]"	Generate CHI template with content
"Help me write the related work for [topic]"	Literature synthesis assistance
"Structure my HBR pitch about [finding]"	HBR framing guidance
"Turn dissertation chapter into journal paper"	Restructure and condense

Command	Action
"Review this abstract for CHI"	Venue-specific feedback
"Strengthen my contribution statement"	Clarify and sharpen
"Help me respond to reviewer concern: [quote]"	Response drafting
"Is my related work comprehensive for [topic]?"	Gap identification