academic-pipeline

What it does

The skill acts as an orchestrator that manages the complete academic pipeline from research exploration to final manuscript. It does not perform substantive work itself; it detects stages, recommends modes, dispatches skills, manages transitions, and tracks state across a 9-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. It enforces user confirmations at stage boundaries and includes a paper creation process record at completion.

How it works

• It detects the user’s current stage based on provided materials and goals, then selects an entry point (Stage 1 through 6) and suggests modes for each stage.
• For each stage, it loads the corresponding skill and launches it with the recommended mode, then monitors completion.
• After a stage completes, it compiles a deliverables list, updates the pipeline state via a state-tracking mechanism, and prompts the user for confirmation at mandatory checkpoints.
• It passes outputs between stages according to a defined handoff protocol, e.g., Stage 1 to Stage 2 uses a deep-research handoff; Stage 2.5 to Stage 3 passes the verified paper; Stage 4.5 to Stage 5 passes the verified final draft, etc.
• It includes integrity verification steps at Stage 2.5 (pre-review) and Stage 4.5 (final integrity), each with explicit verification scopes and pass/fail handling.
• It supports mid-entry entry, where entry can be from any stage but Stage 2.5 cannot be skipped.

When to use it

• Trigger keywords include: "academic pipeline", "research to paper", "full paper workflow", "paper pipeline", "end-to-end paper", "research-to-publication", "complete paper workflow".
• Use when you want an end-to-end orchestration of the full academic pipeline from exploration to final publication, with mandatory integrity checks and two-stage review.

What it can touch

• It dispatches the skills named in the workflow and coordinates state updates across stages. The handoff protocol references specific stages and skills, including: deep-research, academic-paper, academic-paper-reviewer, integrity_verification_agent, and the orchestrator itself.

Caveats

• The workflow enforces mandatory checkpoints at integrity and review stages; explicit user input is required to proceed at those checkpoints.
• It aims for reproducible quality via a standardized workflow and produces a Paper Creation Process Record PDF documenting human-AI collaboration after pipeline completion.
• It relies on the underlying skills to perform substantive work; this skill only manages orchestration, state, and transitions.