🎁 Get the FREE AI Skills Starter Guide β€” Subscribe β†’
BytesAgainBytesAgain
πŸ¦€ ClawHub

Jason Academic Writing

by @ithacajason

Complete academic paper writing pipeline with integrity checks and multi-agent review system. Optimized prompts for Methods/Results/Discussion sections. Feat...

Versionv1.0.1
Downloads387
TERMINAL
clawhub install jason-academic-writing

πŸ“– About This Skill


name: jason-academic-writing description: "Complete academic paper writing pipeline with integrity checks and multi-agent review system. Optimized prompts for Methods/Results/Discussion sections. Features self-counterargument framework, bias matrix, and overclaim self-audit. Use when writing research papers, need citation verification, anti-hallucination checks, multi-perspective review, or auditable process records." version: 1.0.1 requires: env: - OPENAI_API_KEY - OPENAI_BASE_URL

Academic Writing Pipeline

End-to-end academic paper production with built-in quality gates and multi-agent review.

Pipeline Overview

Research β†’ Write β†’ Integrity Check β†’ Review β†’ Revise β†’ Summary

Each stage has defined inputs/outputs and quality gates. The pipeline is non-linear: stages may loop (Review β†’ Revise β†’ Re-Review) until quality threshold met.

Stage Details

Stage 1: Research

Goal: Gather and organize evidence.

Actions: 1. Literature search via Semantic Scholar API 2. Filter by relevance score β‰₯ 0.5 3. Grade evidence level (A: meta-analysis, B: RCT, C: observational, D: opinion) 4. Output: research/evidence.json

Script: scripts/research.py

Stage 2: Write

Goal: Generate structured manuscript.

Actions: 1. Build argument chain from evidence 2. Generate sections: Abstract, Introduction, Methods, Results, Discussion 3. Track citation markers for each claim 4. Output: draft/manuscript.md

Script: scripts/write.py

Stage 3: Integrity Check (CRITICAL)

Goal: Anti-hallucination verification.

Check types:

  • Citation verification: DOI exists? Authors match? Year correct?
  • Data verification: Numbers match tables/figures?
  • Claim verification: Evidence supports assertion?
  • Threshold: Must pass 100% of checks to proceed.

    Script: scripts/integrity_check.py

    APIs used:

  • Semantic Scholar (https://api.semanticscholar.org)
  • CrossRef DOI (https://api.crossref.org/works/)
  • Stage 4: Review (5-Person Panel)

    Agents: | Role | Focus | Score Weight | |------|-------|--------------| | Editor-in-Chief | Contribution, journal fit | 30% | | Methodology | Methods, stats, reproducibility | 25% | | Domain Expert | Related work, theory | 20% | | Devil's Advocate | Strongest counter-arguments | 15% | | Synthesizer | Merge opinions, roadmap | 10% |

    Decision mapping:

  • β‰₯80: Accept
  • 65-79: Minor Revision
  • 50-64: Major Revision
  • <50: Reject
  • Script: scripts/review.py

    Stage 5: Revise

    Goal: Address reviewer feedback.

    Actions: 1. Parse Synthesizer roadmap 2. Generate revision plan with priorities 3. Rewrite affected sections 4. Re-run Integrity Check

    Script: scripts/revise.py

    Stage 6: Process Summary

    Goal: Auditable record.

    Output: summary.json containing:

  • Timeline of each stage
  • Decision points and scores
  • Integrity check results
  • Reviewer scores and comments
  • Revision history
  • Script: scripts/summary.py

    Configuration

    Edit config.yaml for:

  • Model selection (default: qwen3.5-plus)
  • Temperature (default: 0.3 for stability)
  • Review thresholds
  • API keys
  • Usage

    # Full pipeline
    python scripts/main.py --topic "your research topic"

    Single stage

    python scripts/main.py --stage integrity-check --input draft/manuscript.md

    With custom config

    python scripts/main.py --config custom_config.yaml

    Quality Gates

    | Gate | Requirement | Action on Fail | |------|-------------|----------------| | Evidence | β‰₯5 Grade A/B sources | Return to Research | | Integrity | 100% verification | Return to Write | | Review | β‰₯65 score | Loop Revise | | Final Integrity | 100% verification | Block submission |

    Key Principles

    1. Integrity First: Citation verification is non-negotiable 2. Quantified Review: Scores enable objective decisions 3. Loopable Pipeline: Revision cycles until threshold met 4. Auditable Output: Process Summary for journal submission

    Reference Files

  • references/review_rubric.md - Detailed scoring criteria
  • references/evidence_levels.md - Evidence grading standards
  • references/citation_styles.md - Journal formatting guides
  • πŸ’‘ Examples

    # Full pipeline
    python scripts/main.py --topic "your research topic"

    Single stage

    python scripts/main.py --stage integrity-check --input draft/manuscript.md

    With custom config

    python scripts/main.py --config custom_config.yaml

    βš™οΈ Configuration

    Edit config.yaml for:

  • Model selection (default: qwen3.5-plus)
  • Temperature (default: 0.3 for stability)
  • Review thresholds
  • API keys