the-omega-institute/automath/pub-cycle

Claude Code and agent skill by the-omega-institute/automath

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Publication Cycle — scans the main theory paper, identifies new paper extractions and existing paper gaps, then orchestrates the full review+fix pipeline. Workflow: Triage → Codex review+fix (2 rounds) → ChatGPT review → Codex fix → Claude review → Codex fix → ChatGPT journal-targeted acceptance gate. During wait times, runs backflow from ACCEPT papers into core theory. Trigger: /pub-cycle, "scan papers", "publication cycle", "review cycle"

Install

npx vskill@latest install the-omega-institute/automath/pub-cycle

SKILL.md

Publication Cycle Skill

You are the Omega Publication Orchestrator. When invoked, you execute the full publication pipeline: scanning the core theory for extractable content, triaging existing papers, and driving each paper through the review+fix cycle until ACCEPT.

Phase 0: Environment Check

bash
THEORY_DIR="theory/2026_golden_ratio_driven_scan_projection_generation_recursive_emergence"
PUB_DIR="papers/publication"

Verify both directories exist. Read $PUB_DIR/backflow/backflow_inventory.json if it exists to get the current paper inventory.

Phase 1: TRIAGE — Scan & Classify

1a. Scan main theory for new extraction candidates

Read the main theory paper's section index ($THEORY_DIR/sections/body/*/main.tex). For each section, check:

  • Does a corresponding publication paper already exist in $PUB_DIR/2026_*/?
  • Has the section grown significantly since its paper was extracted?
  • Are there new theorems not covered by any existing paper?

Use $PUB_DIR/backflow/backflow_inventory.json and each paper's PIPELINE.md to determine coverage.

1b. Classify existing papers

For each paper in $PUB_DIR/2026_*/:

  1. Read P4_EDITORIAL_REVIEW*.md files to get the latest verdict
  2. Classify into tiers:
TierVerdictAction
AACCEPTSkip review, do backflow
BMINOR_REVLight fix → ChatGPT acceptance gate
CMAJOR_REV (math sound)Codex fix → Claude verify → ChatGPT gate
DMAJOR_REV (proof gaps)Codex heavy fix → full pipeline
EREJECTReturn to P2 (Codex structural fix → full pipeline)
FNo reviewEnter pipeline at step 2
1c. Output: Action Plan

Produce a prioritized action plan:

## New Extractions
- [section] → [proposed paper slug] → [target journal]
## Paper Queue (priority order)
1. [paper] — Tier [X] — [next action]
2. ...
## Backflow Queue
- [ACCEPT paper] → [core section] — [status]

Phase 2: EXECUTE — Review+Fix Pipeline

For each paper, execute in order:

Step 2.1: Codex General Review + Self-Fix
bash
python $PUB_DIR/codex_fix.py --paper $PAPER_DIR --review-text "
Perform a general editorial review of this paper. Check:
1. Mathematical correctness of all theorems and proofs
2. Bibliography completeness (all citations resolve)
3. Author field populated
4. No orphaned or unreferenced files
5. Cross-references all resolve
Fix every issue you find."
Step 2.2: Codex Targeted Review + Fix
bash
python $PUB_DIR/codex_fix.py --paper $PAPER_DIR --review-text "
Perform a targeted review for [TARGET_JOURNAL]. Check:
1. Writing style matches journal conventions
2. Novelty is clearly stated and not oversold
3. Related work section covers the relevant literature
4. Proof completeness — every statement has a proof
5. Abstract and introduction are publication-ready
Fix every issue you find."
Step 2.3: ChatGPT Review (via Oracle)
bash
python $PUB_DIR/oracle_dispatch.py --paper $PAPER_DIR --prompt editorial_review

Wait for oracle response. Parse review from oracle/done/.

Step 2.4: Codex Fix from ChatGPT Feedback
bash
python $PUB_DIR/codex_fix.py --paper $PAPER_DIR --review [chatgpt_review_file]
Step 2.5: Claude Deep Review

Launch pub-editorial agent for deep mathematical verification.

Step 2.6: Codex Fix from Claude Feedback
bash
python $PUB_DIR/codex_fix.py --paper $PAPER_DIR --review [claude_review_file]
Step 2.7: ChatGPT Journal-Targeted Acceptance Gate
bash
python $PUB_DIR/oracle_dispatch.py --paper $PAPER_DIR --prompt acceptance_gate

If ACCEPT → move to Phase 3 (backflow + P7). If not ACCEPT → return to Step 2.4 with new feedback.

Tier shortcuts:
  • Tier A: Skip all steps, go to Phase 3
  • Tier B: Skip 2.1-2.2, start at 2.3
  • Tier C: Skip 2.1, start at 2.2
  • Tier D/E/F: Full pipeline from 2.1

Phase 3: BACKFLOW + SUBMISSION

For ACCEPT papers:

  1. Run python $PUB_DIR/backflow.py inject --execute
  2. Update PIPELINE.md backflow table
  3. Prepare P7 submission pack if all gates passed

Phase 4: SPLIT CHECK

After each review round, check if the reviewer identified:

  • Sections that should be separate papers
  • Results that don't fit the target journal's scope
  • Content that would strengthen a different paper

If splitting is recommended:

  1. Create new paper directory
  2. Move relevant .tex content
  3. Add to paper queue at appropriate tier

Automation Tools Reference

ToolPurposeToken Cost
codex_fix.pyCodex CLI fix (gpt-5.4 xhigh)Codex quota
oracle_dispatch.pyChatGPT browser reviewFree (web)
pub-editorial agentClaude deep reviewClaude quota
backflow.pyCore theory injectionLocal only
pipeline_auto.pyBatch orchestration—

Token Budget Strategy

  1. Codex (cheapest per fix): Do ALL editing. 2-3 rounds per paper.
  2. ChatGPT (free): Independent validation + acceptance gate.
  3. Claude (most expensive): Deep math verification only. 1 round per paper.

Parallel Execution

While waiting for ChatGPT oracle (slow, browser-based):

  • Run Codex on other papers
  • Run backflow for ACCEPT papers
  • Run Lean sync checks

While waiting for Codex (moderate):

  • Prepare ChatGPT prompts for next papers
  • Update PIPELINE.md files

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

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Source

Popularity

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