Install
$ agentstack add skill-echoleesong-claude-skills-plugin-academic-pipeline ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Academic Pipeline v3.11.1 — 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= in a fresh session to continue from the recorded stage. See [references/passport_as_reset_boundary.md](references/passportasreset_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= [stage=] [mode=]
--> Loads the Material Passport (Schema 9), locates the kind: boundary entry matching `, and confirms it has no later kind: resume entry consuming it. If pendingdecision 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 pendingdecision), the next stage is determined by: (a) stage= 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=1must be set in the emitting session. Without the flag, nokind: boundaryentries are written and there is nothing to resume from. - Gate (resume): No flag required. Any session can invoke
resume_from_passport=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](references/passportasreset_boundary.md) — see §"resume_from_passportmode 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
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 (literaturestrategistagent) and the visualization_agent can operate in parallel after Phase 2 (structurearchitectagent) completes the outline. Specifically:
- Once the outline includes a visualization plan,
visualization_agentcan begin figure generation - Simultaneously,
argument_builder_agentcan build CER chains draft_writer_agentwaits 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 remind
…
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: echoleesong
- Source: echoleesong/claude-skills-plugin
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.