Hire an AI research paper discovery reviewer

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A standing summary of what is known, built the first time and kept up to date with your yes
• Each month, the new papers ranked by relevance with an evidence grade for the ones that matter
• Lines of your summary that a strong new paper goes against, with a proposed rewrite
• Up to three papers worth reading in full, each with a plain summary, and the search so it can be repeated

How it does the job well

• Pin down the exact question, scope and the standard of evidence needed before searching.
• Prefer primary sources, and say how strong each source is.
• Separate what is established, debated and unknown, with confidence levels.
• Cite specifically: author, work, date or page where possible.

Mistakes it avoids

• Rewriting the standing summary on one new paper.
• Treating a preprint as settled. Mark preprints as not yet reviewed.
• Reading only the abstract of a paper that changes a line.
• Letting the seen list grow unsorted. Mark each paper read, skimmed or not read.
• Presenting one source or a popular claim as settled.
• Inventing citations, quotes or page numbers.

What a good result looks like

An example, not your task: You follow one research topic for work, study or a decision, and want to stay current with little effort.

• This month. How many papers were found, how many were new and relevant, and the dates searched.
• Lines at risk. Lines of your summary that a strong new paper goes against, with the paper, its grade and a proposed rewrite.
• Support. Strong new papers that back a line of your summary, with their grade.
• Weak or conflicting. Papers logged but not acted on, with the reason and what explains any conflict.
• Read these. Up to three papers worth reading in full, each with a plain summary and why it matters.
• The search. The terms and databases used, so you can repeat the search.

How the work is checked

• Every paper is either new, or removed because it is in seen.md.
• Every claim about a paper comes from its text or abstract, and says which.
• No line was marked "at risk" on a weak paper.
• The standing summary was not changed without a clear yes.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

A second opinion

Before it hands back, your AI reviews the draft the way Rand Fishkin would. This is a way of reviewing the work. It does not mean they wrote or endorse it.

Capabilities

• Build the base. On the first run, it finds the key papers sorted by theme and drafts a standing summary of five lines or fewer for you to approve.
• Search for what is new. Each month it searches open scholarly databases for papers dated since last time and removes those already seen.
• Choose the path. If nothing relevant is new, it says so and stops. If there is something, it ranks the papers and keeps the ten most relevant.
• Pull out and check the claims. For papers that touch your summary, it pulls out claims with their numbers and limits and grades how strong the study is.
• Decide what it means. A strong paper that goes against a line marks it at risk and proposes a rewrite. A weak paper is logged and changes nothing.
• Pick what to read. Chooses up to three papers worth reading in full and gives each a plain summary.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id research-topic-watcher only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/research-topic-watcher/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• The topic, in one or two sentences, and what makes a paper relevant
• Notes, a review you wrote or papers you already trust (optional, but they make the first standing summary more accurate)
• Key terms, authors or journals (optional)
• How far back to look on the first run (optional)

Helpful context (optional)

• A short review or notes you wrote on the topic
• Three to five papers you trust most

Tools and access

• Claude Code: It can keep the watch folder, the seen list and the standing summary, and run each month.
• Zotero: Keep the papers you read here so the seen list and your library match.

Functions and deliverables

• Research paper discovery reviewer: Find new papers on a focused question. Remove repeats, review evidence strength and suggest what is worth reading.
  • A standing summary of what is known, built the first time and kept up to date with your yes
  • Each month, the new papers ranked by relevance with an evidence grade for the ones that matter
  • Lines of your summary that a strong new paper goes against, with a proposed rewrite
  • Up to three papers worth reading in full, each with a plain summary, and the search so it can be repeated
• Research literature finder: Share a topic and research question. It asks framing questions, searches open sources and groups found papers by theme with limits noted.
  • A search plan with framework
  • Papers found, deduplicated
  • Papers grouped by theme
  • Counts of searches and papers
  • A note on any search failures
  Source: Alireza Rezvani.
• Scholarly database searcher: Search PubMed, arXiv, OpenAlex and 15 more free sources for papers, citations and open full text. Every query is shown so you can repeat it.
  • A list of matching papers and preprints
  • Open access links where they exist
  • Citation data
  • The queries used, so you can repeat them
  Source: K-Dense.
• Paper claim evidence finder: With BGPT connected, search a topic or DOI. Get extracted paper claims, source notes and evidence gaps to verify.
  • An evidence table with these columns: claim, result, sample size, limits, DOI and source section.
  • One sample row reads: the claim in one line, the main number, how many took part, the author's stated limit, the DOI, and the table or figure.
  • A flag on any record that has no claim-level evidence.
  • Details of the experiment behind each claim.
  Source: K-Dense.
• Study and claim evidence reviewer: Share a study or claim. Get a review of its design, bias, statistics and limits.
  • A list of biases and confounders
  • Notes on weak or misused statistics
  • An evidence-strength grade
  • A plain-language verdict
  • Questions to ask the authors
  Source: K-Dense.
• Research paper summarizer: Give it a paper, article or report. Get the key findings, plain summaries and a comparison across sources.
  • The key findings of each source, with where each one appears
  • A plain summary of the method and its limits
  • A rough quality rating for each source, judged only from the text you gave it
  • A side-by-side comparison of two or more sources
  • Citations in the style you ask for, APA 7 if you do not say
  Source: Alireza Rezvani.
• Research paper and code note writer: Share a paper, repo or messy notes. Get claims, methods and evidence sorted into a clear research folder.
  • A research folder with claims, methods and results
  • Every claim linked to its supporting table or log
  • Results tables copied with exact numbers
  • A record of dead ends and decisions
  • A short report on what was filled in and what was missing
  Source: Orchestra Research.
• Rand Fishkin: Plan audience research and pick marketing channels with Rand Fishkin's recorded approach. Find where your buyers pay attention and tie it to a goal.
  • Your problem worked on the way Rand Fishkin would: their questions, their method, their push-back
  • The answer or the work, in Rand Fishkin's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step

Tasks you can use it for

• You follow one research topic for work, study or a decision, and want to stay current with little effort.
• You want to know if new papers change what you believe, not just a list of titles.
• You want one weak study to stop moving your view.

Limits to check before starting

• You need a one-time overview of a topic: ask your AI for a literature review and read the main papers yourself.
• Your topic has few papers each year: check by hand every three months, since most months will say nothing new.
• Your sources sit behind paywalls: use your library's own search, because this agent searches open databases and will miss those papers.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Start a chat with the agent. In Claude Code (a paid tool, needed to keep the folder and run each month), add it as a skill or save it in .claude/agents, then name your topic. Zotero is optional: it is free to use, with paid plans for extra storage.
• On the first run, read the draft standing summary. Fix it and say yes before it is saved.
• Each month, ask it to run. It reads the same folder and searches only what is new.
• Read the papers at risk and the three to read. Say yes or no to each proposed change.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/research-topic-watcher for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.