Sucht und analysiert akademische Literatur. Findet relevante Papers, erstellt strukturierte Zusammenfassungen. Zitiert NIEMALS — schlaegt nur vor.
This skill discovers and analyzes academic literature relevant to the Master Thesis on multi-agent orchestration. It searches across academic databases, creates structured summaries, and proposes papers for human review. It is the thesis agent's eyes into the research landscape.
CRITICAL: This skill NEVER adds citations to the thesis. It NEVER modifies references.bib. It NEVER writes \cite{} commands in any .tex file. It only discovers and proposes. The citation-gatekeeper skill handles all approval and citation management.
The research scout searches across the following academic databases and repositories:
| Source | Best For | URL Pattern |
|---|---|---|
| Google Scholar | Broad academic search, citation counts | scholar.google.com |
| Semantic Scholar |
| AI/ML papers, citation graphs, API access |
| semanticscholar.org |
| arXiv | Preprints, cutting-edge AI/LLM research | arxiv.org |
| ACM Digital Library | Software engineering, HCI, systems | dl.acm.org |
| IEEE Xplore | Systems, distributed computing | ieeexplore.ieee.org |
| DBLP | Computer science bibliography, author search | dblp.org |
Search for papers matching a thesis-relevant topic:
Follow prolific authors in relevant fields:
Given a known relevant paper, find:
Combine keywords for precision:
Every discovered paper is summarized in a structured format and saved to thesis/latex/bibliography/pending-papers.json.
{
"id": "sem-scholar-abc123",
"title": "Communicative Agents for Software Development",
"authors": ["Chen Qian", "Xin Cong", "Wei Liu"],
"year": 2024,
"venue": "ACL 2024",
"url": "https://arxiv.org/abs/2307.07924",
"doi": "10.18653/v1/2024.acl-long.1",
"summary": "Proposes ChatDev, a multi-agent framework where LLM-powered agents collaborate through natural language communication to develop software. Agents take roles (CEO, CTO, programmer, tester) and coordinate through structured chat chains.",
"key_findings": [
"Role-based agent specialization improves task completion",
"Chat-chain communication reduces hallucination in code generation",
"Multi-agent debate improves code quality over single-agent approaches"
],
"methodology": "Experimental evaluation on software development benchmarks, comparing single-agent vs. multi-agent approaches",
"relevance_score": 4,
"relevance_justification": "Directly relevant as a multi-agent software framework. Different approach (role-playing chat) than juliaz_agents (tool-calling orchestration). Good contrast for verwandte-arbeiten.",
"suggested_chapter": "03-verwandte-arbeiten",
"suggested_section": "Bestehende Multi-Agenten-Frameworks",
"discovered_date": "2026-02-22",
"search_query": "multi-agent LLM software development",
"status": "pending"
}
| Status | Meaning |
|---|---|
pending | Discovered, awaiting human review via citation-gatekeeper |
approved | Human approved; moved to approved-papers.json by citation-gatekeeper |
rejected | Human rejected; stays in pending with rejection_reason field |
duplicate | Already exists in pending or approved list |
Each paper receives a relevance score from 1 to 5:
| Score | Meaning | Action |
|---|---|---|
| 5 | Directly addresses a thesis research question | Recommend immediate review |
| 4 | Highly relevant to a specific chapter | Recommend for review |
| 3 | Relevant background or related approach | Include in batch review |
| 2 | Tangentially related, might be useful | Include only if topic area is thin |
| 1 | Loosely connected, likely not needed | Skip unless specifically requested |
Only papers scoring 3 or higher are added to pending-papers.json by default. Papers scoring 1-2 are mentioned in the search report but not persisted unless the human requests it.
Before adding a paper to pending-papers.json:
pending-papers.json by title similarity (fuzzy match, >90%)approved-papers.json by title or DOIreferences.bib by BibTeX key or DOIduplicate and note the existing entry IDThe following topic areas are the primary search targets, mapped to thesis chapters:
After a search session, produce a summary:
## Search Report: [Topic]
**Date**: 2026-02-22
**Query**: "multi-agent orchestration LLM"
**Sources checked**: Google Scholar, Semantic Scholar, arXiv
### Papers Found: 7
- **Score 5**: 1 paper (immediate review recommended)
- **Score 4**: 2 papers
- **Score 3**: 3 papers
- **Score 1-2**: 1 paper (not added to pending)
### Added to pending-papers.json:
1. [Title 1] (Score 5) -- 03-verwandte-arbeiten
2. [Title 2] (Score 4) -- 02-grundlagen
...
### Duplicates skipped: 1
### Next suggested search: "tool calling evaluation benchmark"
Assess how well each chapter is covered by discovered literature:
## Literature Coverage
- 02-grundlagen: 12 papers (good coverage)
- 03-verwandte-arbeiten: 8 papers (needs more on MCP ecosystem)
- 04-konzept: 3 papers (thin -- search for architecture pattern papers)
- 05-implementierung: 2 papers (acceptable for implementation chapter)
- 06-evaluation: 1 paper (critical gap -- need evaluation methodology papers)