Paper Reference Assistant (CLI)

VerifiedSafe

CLI interface for paperpipe (papi) to list, search, and view academic papers. Use before MCP RAG tools for optimized paper discovery and retrieval.

Sby Skills Guide Bot
Data & AIIntermediate
306/2/2026
Claude Code
#paperpipe#cli-tool#paper-management#academic-research#reference-assistant

Recommended for

Our review

A CLI tool (papi) for managing and searching a local paper database, designed to be used before resorting to RAG-based MCP tools for paper queries.

Strengths

  • Fast exact-text and regex search without LLM overhead
  • Clear escalation path to RAG when CLI search fails
  • Integrated with per-paper files like summaries and equations
  • Supports adding papers via arXiv, URLs, PDFs, and bulk import

Limitations

  • Requires local paper database setup and indexing for ranked search
  • Not a substitute for semantic synthesis or cross-paper comparisons
  • Search quality depends on preprocessing (e.g., equation parsing)
When to use it

Use when you know the paper name or need exact term lookups, citations, or quick summaries before deeper RAG analysis.

When not to use it

Avoid when you need cross-paper synthesis, open-ended questions, or when the paper is not yet in your local database.

Security analysis

Safe
Quality score92/100

The skill instructs use of a dedicated CLI tool for paper management, with no dangerous commands, data exfiltration, or obfuscated payloads. It relies on Bash for command execution, but only for legitimate purposes.

No concerns found

Examples

List all papers
List all papers in my paperpipe database using papi list.
Show paper summary
Show me the summary of paper 2303.13476 using papi show.
Search for a term
Search for the term 'attention mechanism' using exact text search with papi search --rg.

name: papi description: CLI reference for paperpipe (papi). Use BEFORE MCP RAG tools. For listing, searching, showing, adding papers. allowed-tools: Read, Bash, Glob, Grep

Paper Reference Assistant (CLI)

Entry point skill. Use papi CLI first; MCP RAG tools only when CLI is insufficient.

For specialized workflows, invoke dedicated skills:

  • /papi-ask — RAG queries requiring synthesis
  • /papi-verify — verify code against paper
  • /papi-compare — compare papers for decision
  • /papi-ground — ground responses with citations
  • /papi-curate — create project notes

Setup

papi path   # DB location (default ~/.paperpipe/; override via PAPER_DB_PATH)
papi list   # available papers
papi list | grep -i "keyword"  # check if paper exists before searching

When NOT to Use MCP RAG

  • Paper name known → papi show <paper> -l summary
  • Exact term search → papi search --rg "term"
  • Checking equations → papi show <paper> -l eq
  • Only use RAG when above methods fail or semantic matching required

Decision Tree

| Question | Tool | |----------|------| | "What does paper X say about Y?" | papi show X -l summary, then papi search --rg "Y" | | "Does my code match the paper?" | /papi-verify skill | | "Which paper mentions X?" | papi search --rg "X" first, then leann_search() if no hits | | "Compare approaches across papers" | /papi-compare skill or papi ask | | "Need citable quote with page number" | retrieve_chunks() (PQA MCP) | | "Cross-paper synthesis" | papi ask "..." |

Search Commands

papi search --rg "query"              # exact text (fast, no LLM)
papi search --rg --regex "pattern"    # regex (OR, wildcards)
papi search "query"                   # ranked BM25
papi search --hybrid "query"          # ranked + exact boost
papi ask "question"                   # PaperQA2 RAG
papi ask "question" --backend leann   # LEANN RAG
papi notes {name}                     # open/print implementation notes

Search Escalation (cheapest first)

  1. papi search --rg "X" — exact text, fast, no LLM
  2. papi search "X" — ranked BM25 (requires papi index --backend search first)
  3. papi search --hybrid "X" — ranked + exact boost
  4. leann_search() — semantic search, returns file paths for follow-up
  5. retrieve_chunks() — formal citations (DOI, page numbers)
  6. papi ask "..." — full RAG synthesis

MCP Tool Selection (when papi CLI insufficient)

| Tool | Speed | Output | Best For | |------|-------|--------|----------| | leann_search(index, query, top_k) | Fast | Snippets + file paths | Exploration, finding which paper to dig into | | retrieve_chunks(query, index, k) | Slower | Chunks + formal citations | Verification, citing specific claims | | papi ask "..." | Slowest | Synthesized answer | Cross-paper questions, "what does literature say" |

  • Check indexes: leann_list() or list_pqa_indexes()
  • Embedding priority: Voyage AI → Google/Gemini → OpenAI → Ollama

Adding Papers

papi add 2303.13476                   # arXiv ID
papi add https://arxiv.org/abs/...    # URL
papi add --pdf /path/to.pdf           # local PDF
papi add --pdf "https://..."          # PDF from URL
papi add --from-file papers.bib       # bulk import

Per-Paper Files

Located at {db}/papers/{name}/:

| File | Best For | |------|----------| | equations.md | Code verification | | summary.md | Understanding approach | | source.tex | Exact definitions | | notes.md | Implementation gotchas | | figures/ | Architecture diagrams, plots |

If agent can't read ~/.paperpipe/, export to repo: papi export <papers...> --level equations --to ./paper-context/ Use --figures to include extracted figures in export.

See commands.md for full reference.

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