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Imbad0202/academic-research-skills/academic-pipeline/SKILL.md

academic-pipeline

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-publicat

Source repository stars
40,841
Declared platforms
0
Static risk flags
0
Last source update
2026-08-04
Source checked
2026-08-04

Decision brief

What it does—and where it fits

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.

Best for

    Not for

    • Explicit prohibitions to prevent common failure modes:

    Compatibility matrix

    Platform support, with evidence labels

    PlatformStatusEvidenceWhat to check
    CodexNot declaredNo explicit evidencePortability before use
    Claude CodeNot declaredNo explicit evidencePortability before use
    CursorNot declaredNo explicit evidencePortability before use
    Gemini CLINot declaredNo explicit evidencePortability before use
    Open the compatibility checker

    Installation

    Inspect first. Install second.

    The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

    Source-detected install commandSource
    npx skills add https://github.com/Imbad0202/academic-research-skills --skill "academic-pipeline"
    Safe inspection promptEditorial

    Inspect the Agent Skill "academic-pipeline" from https://github.com/Imbad0202/academic-research-skills/blob/112a869f5205943728791d84602fe43fd3e1438b/academic-pipeline/SKILL.md at commit 112a869f5205943728791d84602fe43fd3e1438b. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

    Workflow

    What the source asks the agent to do

    1. 01

      Quick Start

      Full workflow (from scratch):

      Gate (emit): ARSPASSPORTRESET=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 resumefrompassport= 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.
    2. 02

      Orchestrator Workflow

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

      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-specific reinforcement content: See references/reinforcementcontent.md for the full transition → reinforcement focus table.
    3. 03

      Step 1: INTAKE & DETECTION

      Review the “Step 1: INTAKE & DETECTION” section in the pinned source before continuing.

      Review and apply the “Step 1: INTAKE & DETECTION” source section.
    4. 04

      Step 2: MODE RECOMMENDATION

      Review the “Step 2: MODE RECOMMENDATION” section in the pinned source before continuing.

      Review and apply the “Step 2: MODE RECOMMENDATION” source section.
    5. 05

      Step 3: STAGE EXECUTION

      Review the “Step 3: STAGE EXECUTION” section in the pinned source before continuing.

      Review and apply the “Step 3: STAGE EXECUTION” source section.

    Permission review

    Static risk signals and limitations

    No configured static risk pattern was detected

    This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score90/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars40,841SourceRepository attention, not individual Skill quality
    Compatibility0 platformsSourceDeclared in the catalog source record
    Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

    Pinned source

    Provenance and original SKILL.md

    Repository
    Imbad0202/academic-research-skills
    Skill path
    academic-pipeline/SKILL.md
    Commit
    112a869f5205943728791d84602fe43fd3e1438b
    License
    NOASSERTION
    Collected
    2026-08-04
    Default branch
    main
    View the original SKILL.md

    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:

    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 — Stage 6 generates a "Paper Creation Process Record" PDF documenting the human-AI collaboration history (delivered before the terminal acknowledgement that completes the pipeline)

    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:

    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

    한국어: 학술 파이프라인, 연구부터 논문까지, 논문 전체 워크플로, 연구 주제 설정부터 논문 완성까지, 연구-논문 전 과정

    Non-Trigger Scenarios

    ScenarioSkill to Use
    Only need to search materials or do a literature reviewdeep-research
    Only need to write a paper (no research phase needed)academic-paper
    Only need to review a paperacademic-paper-reviewer
    Only need to check citation formatacademic-paper (citation-check mode)
    Only need to convert paper formatacademic-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)

    StageNameSkill / Agent CalledAvailable ModesDeliverables
    1RESEARCHdeep-researchsocratic, full, quickRQ Brief, Methodology, Bibliography, Synthesis
    2WRITEacademic-paperplan, fullPaper Draft
    2.5INTEGRITYintegrity_verification_agentpre-reviewIntegrity verification report + corrected paper
    3REVIEWacademic-paper-reviewerfull (incl. Devil's Advocate)5 review reports + Editorial Decision + Revision Roadmap
    4REVISEacademic-paperrevisionRevised Draft, Response to Reviewers
    3'RE-REVIEWacademic-paper-reviewerre-reviewVerification review report: revision response checklist + residual issues
    4'RE-REVISEacademic-paperrevisionSecond revised draft (if needed)
    4.5FINAL INTEGRITYintegrity_verification_agentfinal-checkFinal verification report (must achieve 100% pass to proceed)
    5FINALIZEacademic-paperformat-convertFinal Paper (default MD; DOCX via Pandoc when available, otherwise conversion instructions; ask about LaTeX; confirm correctness; PDF)
    6PROCESS SUMMARYorchestratorautoPaper 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

    1. Stage 1 RESEARCH -> user confirmation -> Stage 2
    2. Stage 2 WRITE -> user confirmation -> Stage 2.5
    3. Stage 2.5 INTEGRITY -> PASS -> Stage 3 (FAIL -> fix and re-verify, max 3 rounds)
    4. Stage 3 REVIEW -> Accept -> Stage 4.5 / Minor|Major -> Stage 4 / Reject -> Stage 2 or end
    5. Stage 4 REVISE -> user confirmation -> Stage 3'
    6. Stage 3' RE-REVIEW -> Accept|Minor -> Stage 4.5 / Major -> Stage 4'
    7. Stage 4' RE-REVISE -> user confirmation -> Stage 4.5 (no return to review)
    8. Stage 4.5 FINAL INTEGRITY -> PASS (zero issues) -> Stage 5 (FAIL -> fix and re-verify)
    9. Stage 5 FINALIZE -> MD -> DOCX via Pandoc when available (otherwise instructions) -> ask about LaTeX -> confirm -> PDF -> completion checkpoint (FULL) -> Stage 6 (user may decline Stage 6: marked skipped, pipeline goes directly to completed)
    10. Stage 6 PROCESS SUMMARY -> ask language version -> generate process record MD -> LaTeX -> PDF -> terminal acknowledgement (finish / end / done / confirm, or an unambiguous natural-language equivalent) -> pipeline global state completed

    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

    TypeWhen UsedContent
    FULLFirst checkpoint; after integrity boundaries; Stage 5 completion (final-deliverable acceptance)Full deliverables list + decision dashboard + all options
    SLIMAfter 2+ consecutive "continue" responses on non-critical stagesOne-line status + explicit continue/pause prompt
    MANDATORYIntegrity FAIL; Review decision; Stage 5 entry gate (before finalization)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

    1. First checkpoint: always FULL
    2. After 2+ consecutive "continue" without review: prompt user awareness ("You've continued [N] times in a row. Want to review progress?")
    3. Integrity boundaries (Stage 2.5, 4.5): always MANDATORY
    4. Review decisions (Stage 3, 3'): always MANDATORY
    5. Before finalization (Stage 5 entry gate): always MANDATORY — this is the checkpoint between Stage 4.5 PASS and the Stage 5 dispatch, where the user explicitly confirms proceeding and makes the finalization-format decision (citation style); the in-stage LaTeX question and content confirmation stay inside Stage 5 execution. The Stage 5 completion checkpoint (Final Paper delivered, before Stage 6) is FULL — never SLIM. See references/pipeline_state_machine.md § Stage 5 boundary semantics
    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 + explicit continue/pause prompt)
    5. 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:

    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 (5 Agents)

    #AgentRoleFile
    1pipeline_orchestrator_agentMain orchestrator: detects stage, recommends mode, triggers skill, manages transitionsagents/pipeline_orchestrator_agent.md
    2state_tracker_agentState tracker: records completed stages, produced materials, revision loop countagents/state_tracker_agent.md
    3integrity_verification_agentIntegrity verifier: 100% reference/citation/data verification (blocking)agents/integrity_verification_agent.md
    4collaboration_depth_agentObserver (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 during Stage 6 record compilation (whole-pipeline pass, before the Process Record is delivered). Based on Wang & Zhang (2026).agents/collaboration_depth_agent.md
    5claim_ref_alignment_audit_agentOpt-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 + Methodology Blueprint + 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, the original (pre-revision) draft (#576 §3.1 Phase 2A comparison base — without it every new issue degrades to `indeterminate`), Response to Reviewers, the Editorial Decision Letter (its Review Panel Provenance block feeds the #539 Judge Record), the Round-1 review findings (Schema 6 reports — #576 §4 level-3 criterion layer), the Round-1 Revision Roadmap being verified, the round's apply report(s) with their paired revision patch/diff files (#390/#576 §11 — the two travel together), and the Round-1 Reviewer Configuration Cards (yardstick continuity — field_analyst is NOT re-run at Stage 3'; `re_review_mode_protocol.md` § Yardstick Continuity) to reviewer. This is the re-review-mode transfer, the default Stage 3' — dispatched under the #576 three-gate contract (`pipeline_orchestrator_agent.md` § Stage 3' Re-Review Contract Dispatch; legacy single-pass only behind `ARS_RE_REVIEW_LEGACY=1`); a user-requested fresh full review at 3' instead (mid-entry quick→full path: no Roadmap or Round-1 cards exist) transfers the revised draft + available context only and runs full mode, field_analyst included
       - Stage 3' --> 4': Pass new Revision Roadmap + R&R Traceability Matrix (Schema 11) to academic-paper revision mode; the traceability sidecar (frozen `previously_missed`/`indeterminate` records, #576 §8) rides through 4' toward Stage 4.5
       - Stage 3' --> 4.5 (Accept/Minor direct path): Pass verified revised draft + the traceability sidecar's frozen records to integrity_verification_agent as gate input
       - Stage 4/4' --> 4.5: Pass revision-completed paper to integrity_verification_agent (final verification); on the Major-via-4' path the Stage 3' traceability sidecar travels along as gate input
       - Stage 4.5 --> 5: Pass verified final draft to format-convert mode
       - Stage 5  --> 6: Pass final deliverables list + pipeline state history to Process Summary (user may decline Stage 6 at the Stage 5 completion checkpoint)
    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 + Stage 6 record compilation, 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'.

    Stage 3' runs under the #576 three-gate evidence-before-persuasion contract by default: the orchestrator emits a hash-bound input manifest, dispatches Phase 1 (criteria commitment, revision-blind) → Phase 2A (evidence verdict, persuasion-blind) → Phase 2B (claim matching, letter revealed), and invokes scripts/check_re_review_synthesis.py as a MANDATORY step before any decision surfaces — outcomes are Accept / Minor / Major, a user_review_required deferral, or a fail-closed abort (never Reject). The sidecar's frozen previously_missed/indeterminate new-issue records forward to Stage 4.5 on both routes. Legacy single-pass re-review requires the explicit ARS_RE_REVIEW_LEGACY=1 flag and is marked [LEGACY-NO-CONTRACT]. Authority: pipeline_orchestrator_agent.md § Stage 3' Re-Review Contract Dispatch + academic-paper-reviewer/references/re_review_mode_protocol.md.

    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 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.

    Terminal semantics (#528): Stage 6 is non-mandatory — the user may decline it at the Stage 5 completion checkpoint (Stage 6 marked skipped; the pipeline still terminates completed). When it runs, after the process record is delivered the orchestrator prompts for a terminal acknowledgement — finish / end / done / confirm, or an unambiguous natural-language equivalent that accepts the deliverables. On acknowledgement, Stage 6 is marked completed and the pipeline global state is set to completed; change requests (the other language version, content corrections) keep Stage 6 in_progress and are not acknowledgements. See references/pipeline_state_machine.md § Stage 6 terminal semantics.

    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 during Stage 6 record compilation (the whole-pipeline pass runs before the Process Record is generated and delivered, so its output can be a chapter of the record the user acknowledges). 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 (during Stage 6 record compilation), 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:

    MechanismWhat it evaluatesBlocking?
    integrity_verification_agent (Stages 2.5 / 4.5)Paper content — references, citations, dataYes (blocking gate)
    Stage 6 Collaboration Quality Evaluation (6 dims, 1–100)AI's self-reflection on its own behaviourNo, 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-PatternWhy It FailsCorrect Behavior
    1Skipping 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
    2Orchestrator doing substantive workPipeline orchestrator writes content or reviews the paperOrchestrator only dispatches and coordinates; substantive work belongs to the sub-skills
    3Auto-advancing past MANDATORY checkpointsMoving to next stage without user confirmation at FULL checkpointsMANDATORY checkpoints require explicit user input before proceeding
    4Quality degradation across stagesStage 4 revision is worse than Stage 2 draft because context window is exhaustedIf Stage N output quality < Stage N-1, PAUSE and reload core principles before continuing
    5Silently dropping reviewer concernsRevision addresses 8 of 10 concerns and hopes nobody noticesThe R&R tracking table must account for every concern with explicit status
    6Re-verifying only known issues at Stage 4.5Final integrity check only re-checks Stage 2.5 findingsStage 4.5 must verify from scratch independently; revision may introduce new issues
    7Inflating Collaboration Quality scoresGiving 90/100 to avoid awkward self-criticismHonesty first: no inflation, no pleasantries; cite specific evidence for every score
    8Bypassing 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

    DimensionRequirement
    Stage detectionCorrectly identify user's current stage and available materials
    Mode recommendationRecommend appropriate mode based on user preferences and material status
    Material handoffStage-to-stage handoff materials are complete and correctly formatted
    State trackingPipeline state updated in real time; Progress Dashboard accurate
    Mandatory checkpointUser confirmation required after each stage completion
    Mandatory integrity checkStage 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)
    ReproducibleSame 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

    StageErrorHandling
    IntakeCannot determine entry pointAsk user what materials they have and their goal
    Stage 1deep-research not convergingSuggest mode switch (socratic -> full) or narrow scope
    Stage 2Missing research foundationSuggest returning to Stage 1 to supplement research
    Stage 2.5Still FAIL after 3 correction roundsList unverifiable items; user decides whether to continue
    Stage 3Review result is RejectProvide options: major restructuring (Stage 2) or abandon
    Stage 4Revision incomplete on all itemsList unaddressed items; ask whether to continue
    Stage 3'Verification still has major issuesEnter Stage 4' for final revision
    Stage 4'Issues remain after revisionMark as Acknowledged Limitations; proceed to Stage 4.5
    Stage 4.5Final verification FAILFix and re-verify (max 3 rounds)
    AnyUser leaves midwaySave pipeline state; can resume from breakpoint next time
    AnySkill execution failureReport error; suggest retry, pause, or mode switch. Do not skip mandatory integrity or failure-mode gates

    Agent File References

    AgentDefinition File
    pipeline_orchestrator_agentagents/pipeline_orchestrator_agent.md
    state_tracker_agentagents/state_tracker_agent.md
    integrity_verification_agentagents/integrity_verification_agent.md
    collaboration_depth_agentagents/collaboration_depth_agent.md
    claim_ref_alignment_audit_agentagents/claim_ref_alignment_audit_agent.md

    Reference Files

    ReferencePurpose
    references/pipeline_state_machine.mdComplete state machine definition: all legal transitions, preconditions, actions
    references/plagiarism_detection_protocol.mdPhase D originality verification protocol + self-plagiarism + AI text characteristics
    references/mode_advisor.mdUnified cross-skill decision tree: maps user intent to optimal skill + mode
    references/claim_verification_protocol.mdPhase E claim verification protocol: claim extraction, source tracing, cross-referencing, verdict taxonomy
    references/claim_audit_calibration_protocol.mdv3.8 #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.md7-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.mdMulti-person team coordination: role definitions, handoff protocol, version control, conflict resolution
    references/integrity_review_protocol.mdStage 2.5 + 4.5 integrity verification: 5-phase protocol details
    references/two_stage_review_protocol.mdTwo-stage review: Stage 3 full review + Stage 3' verification review
    references/external_review_protocol.mdExternal (human) reviewer feedback: 4-step intake/coaching/revision/verification
    references/process_summary_protocol.mdStage 6: collaboration quality evaluation + AI self-reflection report
    references/reproducibility_audit.mdStandardized workflow guarantees + audit trail format
    references/progress_dashboard_template.mdASCII progress dashboard template
    references/reinforcement_content.mdStage-specific reinforcement focus table for transitions
    references/changelog.mdFull version history
    shared/handoff_schemas.mdCross-skill data contracts: 9 schemas for all inter-stage handoff artifacts
    shared/collaboration_depth_rubric.mdCollaboration Depth Observer rubric (v1.0): 4 dimensions based on Wang & Zhang (2026) IJETHE 23:11

    Templates

    TemplatePurpose
    templates/pipeline_status_template.mdProgress Dashboard output template

    Examples

    ExampleDemonstrates
    examples/full_pipeline_example.mdComplete pipeline conversation log (Stage 1-5, with integrity + 2-stage review)
    examples/mid_entry_example.mdMid-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 (Journal-Fit Reviewer + 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: Consume the citation-style decision recorded at the Stage 5 entry gate; ask which academic formatting style (APA 7.0 / Chicago / IEEE, etc.) only when no gate decision exists (direct format-convert / mid-entry invocation)
      - 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

    SkillRelationship
    deep-researchDispatched (Stage 1 research phase)
    academic-paperDispatched (Stage 2 writing, Stage 4/4' revision, Stage 5 formatting)
    academic-paper-reviewerDispatched (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

    ItemContent
    Skill Version3.19.0
    Last Updated2026-07-22
    MaintainerCheng-I Wu
    Dependent Skillsdeep-research v2.0+, academic-paper v2.0+, academic-paper-reviewer v1.1+
    RoleFull academic research workflow orchestrator

    Changelog

    See references/changelog.md for full version history.

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