Academic Pipeline v3.5 — Full Academic Research Workflow Orchestrator

A lightweight orchestrator that manages the complete academic pipeline from research exploration to final manuscript. It does not perform substantive work — it only detects stages, recommends modes, dispatches skills, manages transitions, and tracks state.

v2.0 Core Improvements:

1. Mandatory user confirmation checkpoints — Each stage completion requires user confirmation before proceeding to the next step
2. Academic integrity verification — After paper completion and before review submission, 100% reference and data verification must pass
3. Two-stage review — First full review + post-revision focused verification review
4. Final integrity check — After revision completion, re-verify all citations and data are 100% correct
5. Reproducible — Standardized workflow producing consistent quality assurance each time
6. Process documentation — After pipeline completion, automatically generates a "Paper Creation Process Record" PDF documenting the human-AI collaboration history

Quick Start

Full workflow (from scratch):

I want to write a research paper on the impact of AI on higher education quality assurance

--> academic-pipeline launches, starting from Stage 2 (RESEARCH)

Mid-entry (existing paper):

I already have a paper, help me review it

--> academic-pipeline detects mid-entry, starting from Stage 4 (INTEGRITY)

Revision mode (received reviewer feedback):

I received reviewer comments, help me revise

--> academic-pipeline detects, starting from Stage 7 (REVISE)

Execution flow:

1. Detect the user's current stage and available materials
2. Recommend the optimal mode for each stage
3. Dispatch the corresponding skill for each stage
4. After each stage completion, proactively prompt and wait for user confirmation
5. Track progress throughout; Pipeline Status Dashboard available at any time

Trigger Conditions

Trigger Keywords

English: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow

Non-Trigger Scenarios

Trigger Exclusions

• If the user only needs a single function (just search materials, just check citations), no pipeline is needed — directly trigger the corresponding skill
• If the user is already using a specific mode of a skill, do not force them into the pipeline
• The pipeline is optional, not mandatory

Pipeline Stages (12 Stages)

Parallelization opportunity (v3.3): Within Stage 3, the academic-paper skill's Phase 1 (literature_strategist_agent) and the visualization_agent can operate in parallel after Phase 2 (structure_architect_agent) completes the outline. Specifically:

• Once the outline includes a visualization plan, visualization_agent can begin figure generation
• Simultaneously, argument_builder_agent can build CER chains
• draft_writer_agent waits for both to complete before beginning Phase 4

This mirrors PaperOrchestra's parallel execution of Plot Generation (Step 2) and Literature Review (Step 3) after Outline (Step 1), which reduces overall pipeline latency. The parallelization is optional — sequential execution remains the default for simplicity.

Pipeline State Machine

1. Stage 1 LITERATURE SEARCH -> user confirmation -> Stage 2
2. Stage 2 RESEARCH -> user confirmation -> Stage 3
3. Stage 3 WRITE -> user confirmation -> Stage 4
4. Stage 4 INTEGRITY -> PASS -> Stage 5 (FAIL -> fix and re-verify, max 3 rounds)
5. Stage 5 REVIEW -> Accept -> Stage 9 / Minor|Major -> Stage 7 / Reject -> Stage 3 or end
6. Stage 7 REVISE -> user confirmation -> Stage 6
7. Stage 6 RE-REVIEW -> Accept|Minor -> Stage 9 / Major -> Stage 8
8. Stage 8 RE-REVISE -> user confirmation -> Stage 9 (no return to review)
9. Stage 9 FINAL INTEGRITY -> PASS (zero issues) -> Stage 10 (FAIL -> fix and re-verify)
10. Stage 10 HUMANIZE -> user confirmation -> Stage 11
11. Stage 11 FINALIZE -> MD + DOCX -> ask about LaTeX -> confirm -> PDF -> Stage 12
12. Stage 12 PROCESS SUMMARY -> ask language version -> generate process record MD -> LaTeX -> PDF -> end

See references/pipeline_state_machine.md for complete state transition definitions.

Adaptive Checkpoint System

⚠️ IRON RULE — Core rule: After each stage completion, the system must proactively prompt the user and wait for confirmation. The checkpoint presentation adapts based on context and user engagement.

Checkpoint Types

Decision Dashboard (shown at FULL checkpoints)

━━━ Stage [X] [Name] Complete ━━━

Metrics:
- Word count: [N] (target: [T] +/-10%)    [OK/OVER/UNDER]
- References: [N] (min: [M])              [OK/LOW]
- Coverage: [N]/[T] sections drafted       [COMPLETE/PARTIAL]
- Quality indicators: [score if available]

Deliverables:
- [Material 1]
- [Material 2]

Flagged: [any issues detected, or "None"]

Ready to proceed to Stage [Y]? You can also:
1. View progress (say "status")
2. Adjust settings
3. Pause pipeline
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Adaptive Rules

1. First checkpoint: always FULL
2. After 2+ consecutive "continue" without review: prompt user awareness ("You've auto-continued [N] times. Want to review progress?")
3. Integrity boundaries (Stage 4, 9): always MANDATORY
4. Review decisions (Stage 5, 6'): always MANDATORY
5. Before finalization (Stage 11): always MANDATORY
6. All other stages: start FULL, downgrade to SLIM if user says "just continue"

Checkpoint Rules

1. ⚠️ IRON RULE: Cannot auto-skip MANDATORY checkpoints: Even if the previous stage result is perfect, explicit user input is required at MANDATORY checkpoints
2. User can adjust: At FULL and MANDATORY checkpoints, users can modify the mode or settings for the next step
3. Pause-friendly: Users can pause at any checkpoint and resume later
4. SLIM mode: If the user says "just continue" or "fully automatic," subsequent non-critical checkpoints switch to SLIM format (one-line status + auto-continue), but notifications are still sent
5. Awareness guard: After 4+ consecutive auto-continues, the system inserts a FULL checkpoint regardless of stage type to ensure user remains engaged

Self-Check Questions (at every FULL checkpoint)

Before presenting the checkpoint to the user, the orchestrator asks itself:

1. Citation integrity: Are there any unverified citations in the latest output?
2. Sycophantic concession: Did the latest stage uncritically accept all feedback without pushback?
3. Quality trajectory: Is the latest output ≥ the quality of the previous stage? If declining, PAUSE and flag.
4. Scope discipline: Did the latest stage add content not requested by the user or the revision roadmap?
5. Completeness: Are all required deliverables for this stage present?

If ANY answer raises concern, include it in the checkpoint presentation to the user.

Agent Team (3 Agents)

Orchestrator Workflow

Step 1: INTAKE & DETECTION

pipeline_orchestrator_agent analyzes the user's input:

1. What materials does the user have?
   - No materials           --> Stage 2 (RESEARCH)
   - Has research data      --> Stage 3 (WRITE)
   - Has paper draft        --> Stage 4 (INTEGRITY)
   - Has verified paper     --> Stage 5 (REVIEW)
   - Has review comments    --> Stage 7 (REVISE)
   - Has revised draft      --> Stage 6 (RE-REVIEW)
   - Has final draft for formatting --> Stage 11 (FINALIZE)

2. What is the user's goal?
   - Full workflow (research to publication)
   - Partial workflow (only certain stages needed)

3. Determine entry point, confirm with user

Step 2: MODE RECOMMENDATION

Based on entry point and user preferences, recommend modes for each stage:

User type determination:
- Novice / wants guidance --> socratic (Stage 2) + plan (Stage 3) + guided (Stage 5)
- Experienced / wants direct output --> full (Stage 2) + full (Stage 3) + full (Stage 5)
- Time-limited --> quick (Stage 2) + full (Stage 3) + quick (Stage 5)

Explain the differences between modes when recommending, letting the user choose

Step 3: STAGE EXECUTION

Call the corresponding skill (does not do work itself, purely dispatching):

1. Inform the user which Stage is about to begin
2. Load the corresponding skill's SKILL.md
3. Launch the skill with the recommended mode
4. Monitor stage completion status

After completion:
1. Compile deliverables list
2. Update pipeline state (call state_tracker_agent)
3. [MANDATORY] Proactively prompt checkpoint, wait for user confirmation

Step 4: TRANSITION

After user confirmation:

1. Pass the previous stage's deliverables as input to the next stage
2. Trigger handoff protocol (defined in each skill's SKILL.md):
   - Stage 2  --> 2: deep-research handoff (RQ Brief + Bibliography + Synthesis)
   - Stage 3  --> 4: Pass complete paper to integrity_verification_agent
   - Stage 4 --> 3: Pass verified paper to reviewer
   - Stage 5  --> 4: Pass Revision Roadmap to academic-paper revision mode
   - Stage 7  --> 6: Pass revised draft and Response to Reviewers to reviewer
   - Stage 6 --> 8: Pass new Revision Roadmap + R&R Traceability Matrix (Schema 11) to academic-paper revision mode
   - Stage 7/8 --> 9: Pass revision-completed paper to integrity_verification_agent (final verification)
   - Stage 9 --> 5: Pass verified final draft to format-convert mode
3. Begin next stage

Mid-Conversation Reinforcement Protocol

At every stage transition, the orchestrator MUST inject a brief core principles reminder. This prevents context rot in long conversations.

Template (adapt to the upcoming stage):

--- STAGE TRANSITION: [Current] → [Next] ---

🔄 Core Principles Reinforcement:
1. [Most relevant IRON RULE for the next stage]
2. [Most relevant Anti-Pattern to avoid in the next stage]
3. Quality check: Is the output of [Current Stage] at least as good as [Previous Stage]? If not, PAUSE.

Checkpoint: [MANDATORY/ADVISORY] — [What user needs to confirm]
---

Stage-specific reinforcement content: See references/reinforcement_content.md for the full transition → reinforcement focus table.

Integrity Review Protocol

Stage 4 (pre-review) and Stage 9 (post-revision) verification. 5-phase protocol: references → citation context → statistical data → originality → claims.

⚠️ IRON RULE: Stage 9 must PASS with zero issues to proceed to Stage 11. Stage 9 verifies from scratch independently.

⚠️ IRON RULE (v3.2): Both Stage 4 and Stage 9 must also run the AI Research Failure Mode Checklist — a 7-mode taxonomy extending the citation hallucination checks into implementation bugs, hallucinated results, shortcut reliance, bug-as-insight, methodology fabrication, and pipeline-level frame-lock. If any of the 7 modes is SUSPECTED, or if Modes 1/3/5/6 are INSUFFICIENT EVIDENCE, the pipeline blocks and the user must acknowledge (confirm / override with reasoning / revise) before the pipeline proceeds. There is no --no-block escape hatch. Stage 12 PROCESS SUMMARY then reports the full failure-mode audit log as part of the AI Self-Reflection Report.

See references/integrity_review_protocol.md for the 5-phase citation/claim verification procedures. See references/ai_research_failure_modes.md for the 7-mode AI research failure checklist and block/override logic.

Two-Stage Review Protocol

Stage 5 (full review, 5 reviewers) → Revision Coaching → Stage 7 → Stage 6 (re-review) → optional Residual Coaching → Stage 8.

See references/two_stage_review_protocol.md for detailed stage flows and coaching dialogue limits.

Mid-Entry Protocol

Users can enter from any stage. The orchestrator will:

1. Detect materials: Analyze the content provided by the user to determine what is available
2. Identify gaps: Check what prerequisite materials are needed for the target stage
3. Suggest backfilling: If critical materials are missing, suggest whether to return to earlier stages
4. Direct entry: If materials are sufficient, directly start the specified stage

Important: mid-entry cannot skip Stage 4

• If the user brings a paper and enters directly, go through Stage 4 (INTEGRITY) first before Stage 5 (REVIEW)
• Only exception: User can provide a previous integrity verification report and content has not been modified

External Review Protocol

Handles external (human) reviewer feedback integration. 4-step workflow: Intake & Structuring → Strategic Revision Coaching → Revision & Response → Self-Verification.

See references/external_review_protocol.md for the complete 4-step workflow, coaching dialogue patterns, and capability boundaries.

Progress Dashboard

ASCII dashboard shown at FULL checkpoints to display pipeline progress.

See references/progress_dashboard_template.md for the dashboard template.

Revision Loop Management

• Stage 5 (first review) -> Stage 7 (revision) -> Stage 6 (verification review) -> Stage 8 (re-revision, if needed) -> Stage 9 (final verification)
• Maximum 1 round of RE-REVISE (Stage 8): If Stage 6 gives Major, enter Stage 8 for revision then proceed directly to Stage 9 (no return to review)
• Pipeline overrides academic-paper's max 2 revision rule: In the pipeline, revisions are limited to Stage 7 + Stage 8 (one round each), replacing academic-paper's max 2 rounds rule
• Mark unresolved issues as Acknowledged Limitations
• Provide cumulative revision history (each round's decision, items addressed, unresolved items)

Early-Stopping Criterion (v3.2)

At the end of each revision round, if delta \x3C 3 points on the 0-100 rubric AND no P0 issues remain, suggest stopping the revision loop ("converged"). User can override. Hard cap: 2 full revision loops (Stage 7 + Stage 8).

Budget Transparency (v3.2)

At pipeline start, estimate token cost based on paper length, mode, and cross-model toggle. Present estimate and ask for user confirmation before Stage 2 begins.

Reproducibility

Every pipeline artifact is versioned, hashed, and auditable.

See references/reproducibility_audit.md for standardized workflow guarantees, audit trail format, and artifact tracking.

Stage 12: Process Summary Protocol

Produces the final process record: paper creation journey, collaboration quality evaluation (6 dimensions, 1-100), and AI self-reflection report.

See references/process_summary_protocol.md for full workflow, required content structure, scoring dimensions, and output specifications.

Anti-Patterns

Explicit prohibitions to prevent common failure modes:

Quality Standards

Error Recovery

Agent File References

Reference Files

Templates

Examples

Output Language

Follows user language. Academic terminology retained in English.

Integration with Other Skills

academic-pipeline dispatches the following skills (does not do work itself):

Stage 2: deep-research
  - socratic mode: Guided research exploration
  - full mode: Complete research report
  - quick mode: Quick research summary

Stage 3: academic-paper
  - plan mode: Socratic chapter-by-chapter guidance
  - full mode: Complete paper writing

Stage 4: integrity_verification_agent (Mode 1: pre-review)
Stage 9: integrity_verification_agent (Mode 2: final-check)

Stage 5: academic-paper-reviewer
  - full mode: Complete 5-person review (EIC + R1/R2/R3 + Devil's Advocate)

Stage 6: academic-paper-reviewer
  - re-review mode: Verification review (focused on revision responses)

Stage 7/8: academic-paper (revision mode)
Stage 11: academic-paper (format-convert mode)
  - Step 1: Ask user which academic formatting style (APA 7.0 / Chicago / IEEE, etc.)
  - Step 2: Auto-produce MD + DOCX
  - Step 3: Produce LaTeX (using corresponding document class, e.g., apa7 class for APA 7.0)
  - Step 4: After user confirms content is correct, tectonic compiles PDF (final version)
  - Fonts: Times New Roman (English) + Source Han Serif TC VF (Chinese) + Courier New (monospace)
  - ⚠️ IRON RULE: PDF must be compiled from LaTeX (HTML-to-PDF is prohibited)

Related Skills

Version Info

Changelog

See references/changelog.md for full version history.