kmshihab7878 Paper Scanner — Research Department Intelligence Engine
Automated discovery and evaluation of research relevant to CoreMind/AION. UAOP Stage 1 for Research.
When to use
- Weekly research scan — "anything new in multi-agent systems?"
- Before architecture decisions — "what does the research say?"
- Technology evaluation — "is this approach validated?"
- Building a literature review for a specific topic
Pipeline
Step 1: Scan Sources
- arXiv (cs.AI, cs.MA, cs.SE) — last 7/30 days
- Conference proceedings (NeurIPS, ICML, KubeCon, PyCon)
- Tech blogs from relevant companies (Anthropic, OpenAI, Google DeepMind)
- Industry reports (Gartner, a16z, Sequoia)
Step 2: Filter and Score
For each paper/article:
- Relevance to CoreMind priorities (multi-agent, LLM, governance, financial ML)
- Evidence grade (A/B/C per research/rules.md)
- Applicability score (1-10): can we use this in the next 90 days?
- Implementation complexity (S/M/L)
Step 3: Produce Research Brief
Per qualifying paper:
- One-paragraph summary (what they did, what they found)
- Key finding applicable to CoreMind
- Implementation proposal (if applicable)
- Evidence grade + confidence level
Step 4: Self-Improvement Loop
- Track research-to-implementation conversion rate
- Reinforce sources with high conversion
- Adjust scanning keywords based on current priorities
Cadence
WEEKLY: arXiv scan + tech blog digest
MONTHLY: Full research brief with top 10 findings
QUARTERLY: Research agenda review based on implementation outcomes
Agents
| Agent | Role |
|---|---|
| deep-research (L2) | Owns research agenda, executes scans |
| data-analyst (L2) | Evaluates quantitative findings |
| root-cause-analyst (L5) | Validates methodology quality |
| learning-guide (L5) | Creates learning paths from findings |