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Agents52k · #1824

academic-pipeline

Orchestrates the entire academic research process, from research to final review. It coordinates multiple steps to ensure quality and integrity.

What it does

This agent organizes the entire academic research process, from gathering information to the final paper version. It doesn't do the heavy lifting, just manages the stages and coordinates other tools.

When to use it

  • ✓When you have a complete research project and want to organize it.
  • ✓When starting a new academic paper and needing a step-by-step guide.
  • ✓If you already have parts of your paper and want to ensure a smooth process.

Example of what to ask your AI

“Organize my academic research workflow, from initial research to final paper review.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/Imbad0202/academic-research-skills/blob/main/academic-pipeline/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/Imbad0202/academic-research-skills/blob/main/academic-pipeline/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

It acts like a conductor, guiding you through each necessary step. It knows which tools to use and when to use them to ensure nothing is missed.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add Imbad0202/academic-research-skills --skill academic-pipeline

Or download just the file:

curl -L https://raw.githubusercontent.com/Imbad0202/academic-research-skills/main/academic-pipeline/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Academic Pipeline v3.23.1 — 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): plugin and skills-copy installs do not load this repository's .claude/CLAUDE.md, so its routing core is repeated below, identical to shared/references/routing_core.md (#892). If routing has not settled when this skill loads, apply the core before dispatching any agent.

<!-- routing-core:begin -->

Step 0 — Escape hatch check (before any classification): If the user's first message begins with [direct-mode] (case-insensitive byte-0 token, optionally preceded by whitespace/newlines that are stripped on parse), record this fact, strip the prefix and surrounding whitespace from the message, and skip directly to Step 1 explicit-intent handling on the stripped content. The literal [direct-mode] is NOT passed through to the dispatched agent. If the stripped message itself has no clear skill named, Step 1 falls through to Step 3 clarification (the escape hatch bypasses cross-phase clarification (Step 2), not all routing). When the token is honored and the named agent or skill needs inputs the message does not supply, read that agent's or skill's file and ask for what it requires, in its terms. A [direct-mode] token after any other non-whitespace character is not the escape hatch, even when the message asks to skip questions: classify the message through Steps 1-3 as if the token were absent, and do not forward the token. Without the byte-0 token, naming an agent is not explicit intent: such a message goes through Steps 1-3 like any other, so cross-phase materials still get Step 2 clarification.

Otherwise, classify the user's input:

  1. Explicit clear intent — user invokes a specific skill via /ars-* slash command, or uses an unambiguous trigger keyword that maps to a single skill (e.g., "lit-review this", "review my paper", "draft an abstract"): → Route directly; no clarification, no orchestrator detour. → The request stays explicit when the mode's usual input is absent or a word in it has other everyday senses. A revision request with no reviewer comments is revision mode's "feel certain sections need improvement" case, and "revisar artículo" is the reviewer's trigger. Route to that mode and let the mode handle what is missing; do not reopen the choice of workflow.

  2. Cross-phase materials detected — user provides artifacts spanning ≥ 2 pipeline phases without naming a specific skill (e.g., pre-written abstract + pre-collected literature; full draft + reviewer comments + bibliography): → Clarify. Do NOT auto-route to a single-phase agent. List candidate workflows as a-d options in markdown body (NOT via AskUserQuestion tool). See shared/references/intent_clarification_protocol.md for the message template. → Reason: clarification is the safest action when materials don't unambiguously identify intent. (v3.10 active conductor (#134) will handle this via structured intake; v3.9.2 asks.)

  3. Ambiguous intent, no materials — user provides no artifacts and no clear request: → Clarify per shared/references/intent_clarification_protocol.md.

Screening boundary (sr-screener): a request to screen records the user already has (database exports, pasted abstracts, full-text PDFs) against a review's eligibility criteria, or to build a screening protocol, pilot the screening, adjudicate screening conflicts, audit exclusions, or report the selection counts, routes to sr-screener. A request to write a literature review, or to run a systematic review, meta-analysis, or PRISMA report, does not route to sr-screener. Screening starts only when the user asks for it: deep-research systematic-review mode may mention sr-screener, but never hands over to it automatically.

Anti-pattern (caused #133): Receiving ambiguous cross-phase materials and silently auto-routing to a single-phase agent based on which phase the materials "look closest to." This bypasses orchestrator-level reconciliation and lets the subagent inherit the full ambiguity without independent oversight.

<!-- routing-core:end -->

…

FAQ

What does 'orchestrator' mean?

An orchestrator is like a conductor of an orchestra. They don't play any instruments but ensure all musicians (in this case, other AI tools) play together at the right time and in the right way to create a harmonious piece (your academic paper).

What are 'integrity checks'?

These are checks to ensure everything is correct and meets academic standards at different points in the process. It's like proofreading the work to make sure there are no errors or inconsistencies.

Can I skip steps?

The system is designed to follow a complete flow, but there are mechanisms to start at specific stages if needed, indicated by the '[direct-mode]' prefix.

Details

Original description by the author

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, coverage-bounded integrity checks, two-stage peer review, and auditable quality-assurance artifacts. Tri

repo: Imbad0202/academic-research-skills

Popularity

GitHub stars
52k
Ranking position
#1824
License
NOASSERTION
Updated
10/13/2026

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