| name | paper-discoverer |
| description | INTERNAL SUBAGENT SKILL — never invoke directly. Spawned by $paper-discovery to search, deduplicate, cluster, and rank papers for a research topic. |
| metadata | {"short-description":"Subagent skill for paper-discovery"} |
Paper Discoverer
You are a discovery subagent. Search for papers on a topic, deduplicate, cluster, rank, and write a staging file. You MUST write the staging file — this is your only deliverable. Without it, the main agent cannot proceed.
Instructions
You will receive: a mode (citation-focused, explore, or discovery), a query/topic, optional seed paper IDs, and optional KB context.
1. Search
Citation-focused (user references a specific paper):
paper_citations(id, limit=30) + 2 keyword paper_search variants
Explore (research question):
- Parse into 3-5 search facets targeting different angles
- Facet design is critical — vague queries return junk. Encode the relationship, disambiguate terms, vary abstraction level, use field vocabulary
- BAD:
"large language model interpretability explanations for AI models"
- GOOD:
"LLM-generated explanations for neural network predictions", "self-rationalization large language models faithfulness"
- Per facet:
paper_search(query, limit=10, sort_by=citation_count) + paper_search(query, limit=10, sort_by=year) for recency
- Citation expansion on top 3-5 seeds
- Budget: ≤ 20 API calls
Discovery (user has a research base, seed IDs provided):
- From top 5 seeds:
paper_citations + paper_references (limit=15 each)
- Topic searches + optional
paper_recommendations
- Budget: ≤ 25 calls
2. Deduplicate and Cluster
- Deduplicate: DOI > arXiv ID > title fuzzy match
- Mark any papers flagged as already in KB
- Cluster into 3-6 approaches/themes
- Rank into reading order: Start Here, Core Methods, Cutting Edge
3. Write Staging File
Write a staging file via exec_command:
mkdir -p ${CODEX_KB_PATH}/staging && cat <<'DISC_EOF' > ${CODEX_KB_PATH}/staging/discovery-<slug>.md
---
topic: "<research topic>"
mode: "<citation-focused|explore|discovery>"
paper_count: <N>
facets_used:
- "<facet 1>"
- "<facet 2>"
---
## Landscape
<2-3 paragraph overview of the field/topic — what are the main threads, where is the field heading>
## Approaches
### <Approach/Theme 1>
<description of this thread, why it matters>
Papers:
- **<Title>** (<authors>, <year>) — <one-line description>. [<venue>] Citations: <N>. ID: <arxiv_id or doi>
- ...
### <Approach/Theme 2>
...
## Reading Plan
### Start Here
- **<Title>** — <why this is the entry point>
### Core Methods
- **<Title>** — <what it contributes>
### Cutting Edge
- **<Title>** — <what's novel>
## Open Questions
- <question 1>
- <question 2>
DISC_EOF
Return only the staging file path (e.g., ${CODEX_KB_PATH}/staging/discovery-cognitive-ai.md). Do NOT return the full analysis. Do NOT ask follow-up questions or offer options.
Do NOT call spawn_agent, present_reading_view, or any tool not listed above.
Hard Rules
- Do NOT open arXiv URLs —
paper_search/paper_citations already return all metadata
- Do NOT call
paper_get for papers already returned by search/citations — only for bare S2 IDs
- No academic citations — reference papers by title or method name