AgentStack
Browse Sign in
Browse Why AgentStack Sell Docs
Sign in
SKILL verified MIT Self-run

Academic Pipeline

skill-hamzabellouch-agent-skills-academic-academic-pipeline · by hamzabellouch

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 pip…

No reviews yet
0 installs
34 views
0.0% view→install

Install

$ agentstack add skill-hamzabellouch-agent-skills-academic-academic-pipeline

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No 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.

View the full security report →

Verified badge

Passed review? Show it. Paste this badge into your README, it links to the public security report.

AgentStack Verified badge Links to your public security report.
[![AgentStack Verified](https://agentstack.voostack.com/badges/verified.svg)](https://agentstack.voostack.com/security/report/skill-hamzabellouch-agent-skills-academic-academic-pipeline)

Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
2mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
Are you the author of Academic Pipeline? Claim this listing to set pricing, connect Stripe payouts, and keep 70% of every sale.
Sign up to claim

About

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= 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:

  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= [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=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= 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_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

| 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_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

| Type | When Used | Content | |------|-----------|---------| | FULL | First checkpoint; after integrity boundaries; Stage 5 completion (final-deliverable acceptance) | 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 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)

| # | 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 during Stage 6 record compilation (whole-pipeline pass, before the Process Record is delivered). 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 confirm

…

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [hamzabellouch](https://github.com/hamzabellouch)
- **Source:** [hamzabellouch/agent-skills](https://github.com/hamzabellouch/agent-skills)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

Reviews

No reviews yet, be the first.

Versions

  • v0.1.0 Imported from the upstream source.