| name | academic-pipeline |
| description | Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow, 연구부터 논문까지, 연구 주제 설정부터 논문 완성까지, 논문 전체 워크플로. |
| metadata | {"version":"3.16.0","last_updated":"2026-07-12","depends_on":"deep-research, academic-paper, academic-paper-reviewer","status":"active","data_access_level":"verified_only","task_type":"open-ended","related_skills":["deep-research","academic-paper","academic-paper-reviewer"]} |
Academic Pipeline v3.15.0 — 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.
Routing discipline (v3.9.2): see .claude/CLAUDE.md "Routing Discipline (v3.9.2)" + shared/references/intent_clarification_protocol.md for cross-skill routing rules. This skill assumes routing has already settled — ambiguous cross-phase materials should have been clarified upstream.
v3.6.3 (opt-in): Set ARS_PASSPORT_RESET=1 to promote FULL checkpoints to context-reset boundaries. Use resume_from_passport=<hash> in a fresh session to continue from the recorded stage. See references/passport_as_reset_boundary.md.
v3.8 (opt-in): Set ARS_CLAIM_AUDIT=1 to enable the L3 claim-faithfulness audit gate at the Stage 4 → Stage 5 transition. When the flag is set, the orchestrator dispatches claim_ref_alignment_audit_agent after the v3.7.1 Cite-Time Provenance Finalizer and before formatter_agent's hard gate. The audit emits claim_audit_results[] + uncited_assertions[] + claim_drifts[] + constraint_violations[] + audit_sampling_summaries[] aggregates per the 8-row matrix; HIGH-WARN classes gate-refuse output via the formatter REFUSE rules 6-10. Default OFF for v3.8.0 — ramp-on plan deferred to post-calibration evidence (spec §5 mode flag rationale). See agents/claim_ref_alignment_audit_agent.md and the orchestrator §3.6 prose.
v2.0 Core Improvements:
- Mandatory user confirmation checkpoints — Each stage completion requires user confirmation before proceeding to the next step
- Academic integrity verification — After paper completion and before review submission, 100% reference and data verification must pass
- Two-stage review — First full review + post-revision focused verification review
- Final integrity check — After revision completion, re-verify all citations and data are 100% correct
- Reproducible — Standardized workflow producing consistent quality assurance each time
- 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 1 (RESEARCH)
Mid-entry (existing paper):
I already have a paper, help me review it
--> academic-pipeline detects mid-entry, starting from Stage 2.5 (INTEGRITY)
Revision mode (received reviewer feedback):
I received reviewer comments, help me revise
--> academic-pipeline detects, starting from Stage 4 (REVISE)
Resume from passport (cross-session context reset, opt-in):
resume_from_passport=<hash> [stage=<n>] [mode=<m>]
--> Loads the Material Passport (Schema 9), locates the kind: boundary entry matching <hash>, and confirms it has no later kind: resume entry consuming it. If pending_decision is set, the decision prompt fires first to capture the user's branch choice for the audit ledger; the prompt is never skipped, even when the user supplies stage=. After the prompt (or immediately if no pending_decision), the next stage is determined by: (a) stage=<n> CLI override if provided, else (b) the matched option's next_stage, else (c) the next field recorded in the boundary entry. CLI stage=/mode= overrides win over option routing.
- Gate (emit):
ARS_PASSPORT_RESET=1 must be set in the emitting session. Without the flag, no kind: boundary entries are written and there is nothing to resume from.
- Gate (resume): No flag required. Any session can invoke
resume_from_passport=<hash> against a passport that carries a valid boundary entry matching the hash.
- Intent: Invoke in a fresh Claude Code session. Resuming within the same session that emitted the boundary provides no token savings and may drop still-live in-session context.
- Stage: Any. Resumes at whatever stage the routing rules above determine.
- Reference:
references/passport_as_reset_boundary.md — see §"resume_from_passport mode contract".
Execution flow:
- Detect the user's current stage and available materials
- Recommend the optimal mode for each stage
- Dispatch the corresponding skill for each stage
- After each stage completion, proactively prompt and wait for user confirmation
- 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
한국어: 학술 파이프라인, 연구부터 논문까지, 논문 전체 워크플로, 연구 주제 설정부터 논문 완성까지, 연구-논문 전 과정
Non-Trigger Scenarios
| Scenario | Skill to Use |
|---|
| Only need to search materials or do a literature review | deep-research |
| Only need to write a paper (no research phase needed) | academic-paper |
| Only need to review a paper | academic-paper-reviewer |
| Only need to check citation format | academic-paper (citation-check mode) |
| Only need to convert paper format | academic-paper (format-convert mode) |
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, respect that entry point; the pipeline is opt-in
- The pipeline is optional, not mandatory
Pipeline Stages (10 Stages)
| Stage | Name | Skill / Agent Called | Available Modes | Deliverables |
|---|
| 1 | RESEARCH | deep-research | socratic, full, quick | RQ Brief, Methodology, Bibliography, Synthesis |
| 2 | WRITE | academic-paper | plan, full | Paper Draft |
| 2.5 | INTEGRITY | integrity_verification_agent | pre-review | Integrity verification report + corrected paper |
| 3 | REVIEW | academic-paper-reviewer | full (incl. Devil's Advocate) | 5 review reports + Editorial Decision + Revision Roadmap |
| 4 | REVISE | academic-paper | revision | Revised Draft, Response to Reviewers |
| 3' | RE-REVIEW | academic-paper-reviewer | re-review | Verification review report: revision response checklist + residual issues |
| 4' | RE-REVISE | academic-paper | revision | Second revised draft (if needed) |
| 4.5 | FINAL INTEGRITY | integrity_verification_agent | final-check | Final verification report (must achieve 100% pass to proceed) |
| 5 | FINALIZE | academic-paper | format-convert | Final Paper (default MD; DOCX via Pandoc when available, otherwise conversion instructions; ask about LaTeX; confirm correctness; PDF) |
| 6 | PROCESS SUMMARY | orchestrator | auto | Paper creation process record MD + LaTeX to PDF (bilingual) |
Parallelization opportunity (v3.3): Within Stage 2, 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
- Stage 1 RESEARCH -> user confirmation -> Stage 2
- Stage 2 WRITE -> user confirmation -> Stage 2.5
- Stage 2.5 INTEGRITY -> PASS -> Stage 3 (FAIL -> fix and re-verify, max 3 rounds)
- Stage 3 REVIEW -> Accept -> Stage 4.5 / Minor|Major -> Stage 4 / Reject -> Stage 2 or end
- Stage 4 REVISE -> user confirmation -> Stage 3'
- Stage 3' RE-REVIEW -> Accept|Minor -> Stage 4.5 / Major -> Stage 4'
- Stage 4' RE-REVISE -> user confirmation -> Stage 4.5 (no return to review)
- Stage 4.5 FINAL INTEGRITY -> PASS (zero issues) -> Stage 5 (FAIL -> fix and re-verify)
- Stage 5 FINALIZE -> MD -> DOCX via Pandoc when available (otherwise instructions) -> ask about LaTeX -> confirm -> PDF -> Stage 6
- Stage 6 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
| Type | When Used | Content |
|---|
| FULL | First checkpoint; after integrity boundaries; before finalization | Full deliverables list + decision dashboard + all options |
| SLIM | After 2+ consecutive "continue" responses on non-critical stages | One-line status + explicit continue/pause prompt |
| MANDATORY | Integrity FAIL; Review decision; Stage 5 | Cannot be skipped; requires explicit user input |
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
- First checkpoint: always FULL
- After 2+ consecutive "continue" without review: prompt user awareness ("You've continued [N] times in a row. Want to review progress?")
- Integrity boundaries (Stage 2.5, 4.5): always MANDATORY
- Review decisions (Stage 3, 3'): always MANDATORY
- Before finalization (Stage 5): always MANDATORY
- All other stages: start FULL, downgrade to SLIM if user says "just continue"
Checkpoint Rules
- ⚠️ IRON RULE: Cannot auto-skip MANDATORY checkpoints: Even if the previous stage result is perfect, explicit user input is required at MANDATORY checkpoints
- User can adjust: At FULL and MANDATORY checkpoints, users can modify the mode or settings for the next step
- Pause-friendly: Users can pause at any checkpoint and resume later
- SLIM mode: If the user says "just continue" or "fully automatic," subsequent non-critical checkpoints switch to SLIM format (one-line status + explicit continue/pause prompt)
- Awareness guard: After 4+ consecutive continue responses, 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:
- Citation integrity: Are there any unverified citations in the latest output?
- Sycophantic concession: Did the latest stage uncritically accept all feedback without pushback?
- Quality trajectory: Is the latest output ≥ the quality of the previous stage? If declining, PAUSE and flag.
- Scope discipline: Did the latest stage add content not requested by the user or the revision roadmap?
- 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 (5 Agents)
| # | Agent | Role | File |
|---|
| 1 | pipeline_orchestrator_agent | Main orchestrator: detects stage, recommends mode, triggers skill, manages transitions | agents/pipeline_orchestrator_agent.md |
| 2 | state_tracker_agent | State tracker: records completed stages, produced materials, revision loop count | agents/state_tracker_agent.md |
| 3 | integrity_verification_agent | Integrity verifier: 100% reference/citation/data verification (blocking) | agents/integrity_verification_agent.md |
| 4 | collaboration_depth_agent | Observer (advisory only — never blocks). Reads dialogue log and scores user-AI collaboration pattern against shared/collaboration_depth_rubric.md. Invoked at FULL/SLIM checkpoints and at pipeline completion. Based on Wang & Zhang (2026). | agents/collaboration_depth_agent.md |
| 5 | claim_ref_alignment_audit_agent | Opt-in claim faithfulness auditor (v3.8 #103). Audits sampled citations for claim ↔ reference alignment + negative-constraint compliance; emits per-claim claim_audit_results[], claim_drift[], uncited_assertions[], constraint_violations[]. Dispatched via orchestrator §3.6 when claim_audit mode is requested. | agents/claim_ref_alignment_audit_agent.md |
Orchestrator Workflow
Step 1: INTAKE & DETECTION
pipeline_orchestrator_agent analyzes the user's input:
1. What materials does the user have?
- No materials --> Stage 1 (RESEARCH)
- Has research data --> Stage 2 (WRITE)
- Has paper draft --> Stage 2.5 (INTEGRITY)
- Has verified paper --> Stage 3 (REVIEW)
- Has review comments --> Stage 4 (REVISE)
- Has revised draft --> Stage 3' (RE-REVIEW)
- Has final draft for formatting --> Stage 5 (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 1) + plan (Stage 2) + guided (Stage 3)
- Experienced / wants direct output --> full (Stage 1) + full (Stage 2) + full (Stage 3)
- Time-limited --> quick (Stage 1) + full (Stage 2) + quick (Stage 3)
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 1 --> 2: deep-research handoff (RQ Brief + Bibliography + Synthesis)
- Stage 2 --> 2.5: Pass complete paper to integrity_verification_agent
- Stage 2.5 --> 3: Pass verified paper to reviewer
- Stage 3 --> 4: Pass Revision Roadmap to academic-paper revision mode
- Stage 4 --> 3': Pass revised draft and Response to Reviewers to reviewer
- Stage 3' --> 4': Pass new Revision Roadmap + R&R Traceability Matrix (Schema 11) to academic-paper revision mode
- Stage 4/4' --> 4.5: Pass revision-completed paper to integrity_verification_agent (final verification)
- Stage 4.5 --> 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.
Phase-by-phase Invocation Contract (v3.9.2)
academic-pipeline is the orchestrator skill that coordinates the full ARS pipeline across 10 stages (delegating to deep-research, academic-paper, academic-paper-reviewer). Two invocation modes:
Mode A — orchestrator-driven (default): pipeline_orchestrator_agent runs all stages end-to-end with state tracking via Material Passport. state_tracker_agent, integrity_verification_agent, collaboration_depth_agent, and claim_ref_alignment_audit_agent are dispatched by the orchestrator at the appropriate checkpoints.
Mode B — phase-by-phase (cross-session resume): User invokes one phase agent at a time across sessions, typically via ARS_PASSPORT_RESET=1 + resume_from_passport=<hash> (see references/passport_as_reset_boundary.md).
In Mode B, single-phase agents (Bucket A per docs/design/2026-05-18-ars-v3.9.2-agent-phase-classification.md) in the downstream skills (deep-research, academic-paper, academic-paper-reviewer) stay strictly within their assigned phase for writes. The 5 agents in academic-pipeline itself are all cross-phase / meta by design (Bucket C/D) — they have no fence by design:
pipeline_orchestrator_agent (D — orchestrator, full pipeline visibility)state_tracker_agent (D — meta state, all phases)integrity_verification_agent (C — Stage 2.5 / 4.5 cross-skill gate)collaboration_depth_agent (C — FULL/SLIM checkpoints + pipeline completion, advisory-only)claim_ref_alignment_audit_agent (C — opt-in claim audit, phase-orthogonal)
Routing into Mode B requires explicit user signal — /ars-<mode> slash command or [direct-mode] prefix. Ambiguous cross-phase input defaults to clarification per .claude/CLAUDE.md Routing Discipline + shared/references/intent_clarification_protocol.md. Critically: if pipeline_orchestrator_agent is dispatched on ambiguous cross-phase materials, the orchestrator itself currently cannot reconcile (this is the v3.10 conductor #134 work) — v3.9.2 routes such cases to clarification BEFORE the orchestrator runs.
Enforcement (v3.9.2): Phase Boundary blocks on downstream Bucket A agents + advisory verifier (scripts/check_pipeline_integrity.py) + a deterministic PreToolUse write-scope guard in hook-enabled runtimes (#134 rescope, PR #294). Multi-phase envelope + orchestrator structured intake remain forward-scope (#134 Slices 3-5).
Integrity Review Protocol
Stage 2.5 (pre-review) and Stage 4.5 (post-revision) verification. 5-phase protocol: references → citation context → statistical data → originality → claims.
⚠️ IRON RULE: Stage 4.5 must PASS with zero issues to proceed to Stage 5. Stage 4.5 verifies from scratch independently.
⚠️ IRON RULE (v3.2): Both Stage 2.5 and Stage 4.5 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 6 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.
- [v3.4.0]
compliance_agent runs mode-aware PRISMA-trAIce + RAISE compliance check; tier-based block semantics. See shared/compliance_checkpoint_protocol.md.
Two-Stage Review Protocol
Stage 3 (full review, 5 reviewers) → Revision Coaching → Stage 4 → Stage 3' (re-review) → optional Residual Coaching → Stage 4'.
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:
- Detect materials: Analyze the content provided by the user to determine what is available
- Identify gaps: Check what prerequisite materials are needed for the target stage
- Suggest backfilling: If critical materials are missing, suggest whether to return to earlier stages
- Direct entry: If materials are sufficient, directly start the specified stage
Important: mid-entry cannot skip Stage 2.5
- If the user brings a paper and enters directly, go through Stage 2.5 (INTEGRITY) first before Stage 3 (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 3 (first review) -> Stage 4 (revision) -> Stage 3' (verification review) -> Stage 4' (re-revision, if needed) -> Stage 4.5 (final verification)
- Maximum 1 round of RE-REVISE (Stage 4'): If Stage 3' gives Major, enter Stage 4' for revision then proceed directly to Stage 4.5 (no return to review)
- Pipeline overrides academic-paper's max 2 revision rule: In the pipeline, revisions are limited to Stage 4 + Stage 4' (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 < 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 4 + Stage 4').
Budget Transparency (v3.2; interaction-count extension #89/#388)
At pipeline start, estimate token cost based on paper length, mode, and cross-model toggle. Present estimate and ask for user confirmation before Stage 1 begins.
Alongside the token estimate, present the interaction-count budget: long-horizon document corruption compounds with the number of document round-trips, not with token volume (DELEGATE-52, arXiv:2604.15597). Enumerate the round-trip caps the pipeline already enforces — 2 full revision loops (Early-Stopping above), 8 + 5 Socratic coaching rounds (Stage 3→4 / 3'→4'), and the integrity-gate fix→re-verify loop at Stages 2.5/4.5 — and state the worst-case round-trip total those caps imply for the chosen mode. At each stage checkpoint, report the accumulated round-trip count next to the stage status. Advisory only: the count never blocks; the per-loop caps remain the enforcement layer. A run that exceeds its stated worst case signals a loop the caps do not cover — surface that explicitly rather than silently continuing.
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 6: 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.
Collaboration Depth Observer (v3.5.0, advisory only — never blocks)
The collaboration_depth_agent observes the user's collaboration pattern with the pipeline. It is advisory only and never blocks progression at any checkpoint. It is non-blocking by design and carries blocking: false in its frontmatter as a structural guarantee.
When invoked: every FULL checkpoint, every SLIM checkpoint, and after Stage 6 (pipeline completion). MANDATORY checkpoints (Stages 2.5 / 4.5 integrity gates) do not invoke the observer — those are integrity concerns and must not be diluted.
What it does: reads the dialogue range for the just-completed stage (at checkpoints) or the whole pipeline (at completion), scores the pattern against the canonical rubric at shared/collaboration_depth_rubric.md, and emits an advisory block/chapter. Dimensions: Delegation Intensity, Cognitive Vigilance, Cognitive Reallocation, Zone Classification (Zone 1 / Zone 2 / Zone 3). Rubric is based on Wang & Zhang (2026) IJETHE 23:11 (DOI 10.1186/s41239-026-00585-x).
Distinction from existing mechanisms:
| Mechanism | What it evaluates | Blocking? |
|---|
integrity_verification_agent (Stages 2.5 / 4.5) | Paper content — references, citations, data | Yes (blocking gate) |
| Stage 6 Collaboration Quality Evaluation (6 dims, 1–100) | AI's self-reflection on its own behaviour | No, but produced once only |
collaboration_depth_agent (this observer) | The user's collaboration pattern (delegation intensity, vigilance, reallocation) | No — never blocks. Advisory only. |
Non-blocking guarantees:
- Observer output never appears on the "Flagged" line of any checkpoint.
- The
Ready to proceed? prompt is unchanged by observer output.
blocked_by: collaboration_depth_agent is never a legal state in state_tracker.- If observer frontmatter ever asserts
blocking: true, the orchestrator must refuse to dispatch it.
Cross-model: when ARS_CROSS_MODEL is set, the observer runs on both models and flags any dimension divergence > 2 points. Scores are never silently averaged across models.
See agents/collaboration_depth_agent.md for full scoring procedure and anti-sycophancy discipline; shared/collaboration_depth_rubric.md for the canonical 4-dimension rubric.
Anti-Patterns
Explicit prohibitions to prevent common failure modes:
| # | Anti-Pattern | Why It Fails | Correct Behavior |
|---|
| 1 | Skipping integrity checks | "The paper looks fine, skip Stage 2.5/4.5" | Integrity checks are MANDATORY; they cannot be auto-skipped regardless of perceived quality |
| 2 | Orchestrator doing substantive work | Pipeline orchestrator writes content or reviews the paper | Orchestrator only dispatches and coordinates; substantive work belongs to the sub-skills |
| 3 | Auto-advancing past MANDATORY checkpoints | Moving to next stage without user confirmation at FULL checkpoints | MANDATORY checkpoints require explicit user input before proceeding |
| 4 | Quality degradation across stages | Stage 4 revision is worse than Stage 2 draft because context window is exhausted | If Stage N output quality < Stage N-1, PAUSE and reload core principles before continuing |
| 5 | Silently dropping reviewer concerns | Revision addresses 8 of 10 concerns and hopes nobody notices | The R&R tracking table must account for every concern with explicit status |
| 6 | Re-verifying only known issues at Stage 4.5 | Final integrity check only re-checks Stage 2.5 findings | Stage 4.5 must verify from scratch independently; revision may introduce new issues |
| 7 | Inflating Collaboration Quality scores | Giving 90/100 to avoid awkward self-criticism | Honesty first: no inflation, no pleasantries; cite specific evidence for every score |
| 8 | Bypassing the Failure Mode Checklist block (v3.2) | "The 7-mode checklist is new, let's skip it this run" | Stage 2.5/4.5 Failure Mode Checklist is MANDATORY and BLOCKING; no --no-block flag exists; overrides require user reasoning recorded for Stage 6 |
Quality Standards
| Dimension | Requirement |
|---|
| Stage detection | Correctly identify user's current stage and available materials |
| Mode recommendation | Recommend appropriate mode based on user preferences and material status |
| Material handoff | Stage-to-stage handoff materials are complete and correctly formatted |
| State tracking | Pipeline state updated in real time; Progress Dashboard accurate |
| Mandatory checkpoint | User confirmation required after each stage completion |
| Mandatory integrity check | Stage 2.5 and 4.5 cannot be skipped, must PASS |
| Mandatory failure mode checklist (v3.2) | Stage 2.5 and 4.5 must run the 7-mode AI research failure checklist; suspected failures block; overrides require user reasoning |
| No overstepping | ⚠️ IRON RULE: Orchestrator does not perform substantive research/writing/reviewing, only dispatching |
| No forcing | ⚠️ IRON RULE: User can pause or exit pipeline at any time (but cannot skip integrity checks) |
| Reproducible | Same input follows the same workflow across different sessions |
| Convergence-aware stopping (v3.2) | If delta < 3 points AND no P0 issues, suggest stopping revision loop; user can override |
| Budget transparency (v3.2; #388) | Token cost estimate + interaction-count budget (round-trip caps + accumulated count at checkpoints, advisory) + user confirmation at pipeline start |
Error Recovery
| Stage | Error | Handling |
|---|
| Intake | Cannot determine entry point | Ask user what materials they have and their goal |
| Stage 1 | deep-research not converging | Suggest mode switch (socratic -> full) or narrow scope |
| Stage 2 | Missing research foundation | Suggest returning to Stage 1 to supplement research |
| Stage 2.5 | Still FAIL after 3 correction rounds | List unverifiable items; user decides whether to continue |
| Stage 3 | Review result is Reject | Provide options: major restructuring (Stage 2) or abandon |
| Stage 4 | Revision incomplete on all items | List unaddressed items; ask whether to continue |
| Stage 3' | Verification still has major issues | Enter Stage 4' for final revision |
| Stage 4' | Issues remain after revision | Mark as Acknowledged Limitations; proceed to Stage 4.5 |
| Stage 4.5 | Final verification FAIL | Fix and re-verify (max 3 rounds) |
| Any | User leaves midway | Save pipeline state; can resume from breakpoint next time |
| Any | Skill execution failure | Report error; suggest retry, pause, or mode switch. Do not skip mandatory integrity or failure-mode gates |
Agent File References
| Agent | Definition File |
|---|
| pipeline_orchestrator_agent | agents/pipeline_orchestrator_agent.md |
| state_tracker_agent | agents/state_tracker_agent.md |
| integrity_verification_agent | agents/integrity_verification_agent.md |
| collaboration_depth_agent | agents/collaboration_depth_agent.md |
| claim_ref_alignment_audit_agent | agents/claim_ref_alignment_audit_agent.md |
Reference Files
| Reference | Purpose |
|---|
references/pipeline_state_machine.md | Complete state machine definition: all legal transitions, preconditions, actions |
references/plagiarism_detection_protocol.md | Phase D originality verification protocol + self-plagiarism + AI text characteristics |
references/mode_advisor.md | Unified cross-skill decision tree: maps user intent to optimal skill + mode |
references/claim_verification_protocol.md | Phase E claim verification protocol: claim extraction, source tracing, cross-referencing, verdict taxonomy |
references/claim_audit_calibration_protocol.md | v3.8 #103 claim_ref_alignment audit calibration: gold-set shape (T-C3), threshold gates FNR<0.15 / FPR<0.10 (T-C1), per-class FNR/FPR reporting (T-C2). Re-run via PYTHONPATH=. python3 -m unittest scripts.test_claim_audit_calibration -v. |
references/ai_research_failure_modes.md | 7-mode AI research failure checklist (Lu 2026), run at Stage 2.5 + 4.5 with blocking behaviour, reported at Stage 6 |
references/team_collaboration_protocol.md | Multi-person team coordination: role definitions, handoff protocol, version control, conflict resolution |
references/integrity_review_protocol.md | Stage 2.5 + 4.5 integrity verification: 5-phase protocol details |
references/two_stage_review_protocol.md | Two-stage review: Stage 3 full review + Stage 3' verification review |
references/external_review_protocol.md | External (human) reviewer feedback: 4-step intake/coaching/revision/verification |
references/process_summary_protocol.md | Stage 6: collaboration quality evaluation + AI self-reflection report |
references/reproducibility_audit.md | Standardized workflow guarantees + audit trail format |
references/progress_dashboard_template.md | ASCII progress dashboard template |
references/reinforcement_content.md | Stage-specific reinforcement focus table for transitions |
references/changelog.md | Full version history |
shared/handoff_schemas.md | Cross-skill data contracts: 9 schemas for all inter-stage handoff artifacts |
shared/collaboration_depth_rubric.md | Collaboration Depth Observer rubric (v1.0): 4 dimensions based on Wang & Zhang (2026) IJETHE 23:11 |
Templates
| Template | Purpose |
|---|
templates/pipeline_status_template.md | Progress Dashboard output template |
Examples
| Example | Demonstrates |
|---|
examples/full_pipeline_example.md | Complete pipeline conversation log (Stage 1-5, with integrity + 2-stage review) |
examples/mid_entry_example.md | Mid-entry example starting from Stage 2.5 (existing paper -> integrity check -> review -> revision -> finalization) |
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 1: deep-research
- socratic mode: Guided research exploration
- full mode: Complete research report
- quick mode: Quick research summary
Stage 2: academic-paper
- plan mode: Socratic chapter-by-chapter guidance
- full mode: Complete paper writing
Stage 2.5: integrity_verification_agent (Mode 1: pre-review)
Stage 4.5: integrity_verification_agent (Mode 2: final-check)
Stage 3: academic-paper-reviewer
- full mode: Complete 5-person review (EIC + R1/R2/R3 + Devil's Advocate)
Stage 3': academic-paper-reviewer
- re-review mode: Verification review (focused on revision responses)
Stage 4/4': academic-paper (revision mode)
Stage 5: academic-paper (format-convert mode)
- Step 1: Ask user which academic formatting style (APA 7.0 / Chicago / IEEE, etc.)
- Step 2: Produce MD, then generate DOCX via Pandoc when available (otherwise provide conversion instructions)
- 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
| Skill | Relationship |
|---|
deep-research | Dispatched (Stage 1 research phase) |
academic-paper | Dispatched (Stage 2 writing, Stage 4/4' revision, Stage 5 formatting) |
academic-paper-reviewer | Dispatched (Stage 3 first review, Stage 3' verification review) |
Model Tiering (#517, optional)
When ARS_MODEL_TIERING is set, the dispatching session routes this skill's agents per shared/model_tiering.md (canonical: the full 39-agent judgment/execution table + rules). Compact rule:
- Unset (default): every agent inherits the session model — byte-equivalent pre-#517 behavior.
economy (frontier-tier session): execution-type agents dispatch ONE tier below the session model — floor Opus-class, never lower; judgment-type agents stay on the session model. No-op at or below the floor (announce once).quality-boost (below-frontier session): judgment-type agents at the checkpoint surfaces (Stage 2.5/4.5 gates; the opt-in Stage 4→5 claim–ref audit; final review) jump UP to the frontier tier (however many tiers away — not a single increment); nothing is ever downgraded. No-op at the frontier (announce once).- Unknown values → warn once, behave as unset. Tiers are relative positions, never hard-pinned model ids. When a direction is active, route repeated same-stage calls to the SAME worker so its prompt cache accumulates; unset means dispatch shapes stay byte-equivalent too.
Version Info
| Item | Content |
|---|
| Skill Version | 3.16.0 |
| Last Updated | 2026-07-12 |
| Maintainer | Cheng-I Wu |
| Dependent Skills | deep-research v2.0+, academic-paper v2.0+, academic-paper-reviewer v1.1+ |
| Role | Full academic research workflow orchestrator |
Changelog
See references/changelog.md for full version history.
