Bip

Bip Reference Library

A CLI tool for managing academic references with local storage and external paper search.

Repository: Configured via nexus_path in ~/.config/bip/config.json

⚠️ CRITICAL: Local-First Search Policy

ALWAYS search locally before using external APIs. NEVER call ASTA without explicit user permission.

The nexus library has ~6000 papers. Most relevant papers are already there.

Required Search Order

1. Local search FIRST (always do this):

   bip search "author keyword"
   

2. If bip search fails (e.g., schema error), rebuild the database:

   bip rebuild --force
   

   Then retry the search.

3. Only if not found locally AND user confirms, use ASTA:

   "I couldn't find that paper in the local library. Would you like me to search Semantic Scholar (ASTA)?"
   

DO NOT call bip asta, mcp__asta__*, or any external API without asking first.

Argument Handling

When invoked with arguments like /bip find <query> or /bip <query>:

1. Always search local library first with bip search "<query>"
2. If local search fails with an error, rebuild the database and retry
3. Only after exhausting local options, ask user if they want to search externally
4. For title searches, use the full title; for topic searches, use key terms

Proactive Concept Discovery

When discussing papers, always look for opportunities to create concept nodes:

• Papers that introduce new methods, models, or techniques (e.g., "categorical Jacobian")
• Papers that apply existing concepts in novel ways
• Connections between papers through shared concepts

Suggest creating concepts when you notice:

• A named method or algorithm being introduced
• A technique being reused across multiple papers
• A bridge between the user's work and external literature

Quick Reference

Search Strategy

Field-Specific Search Flags

Use --author and --year flags for precise filtering:

# Search by author (exact last name matching to avoid false positives)
bip search --author "Yu" --author "Bloom"    # Last names only
bip search -a "Tim Yu" -a "Bloom"            # First + last name
bip search -a "Yu, Timothy"                  # Last, First format

# Filter by year
bip search --year 2024           # exact year
bip search --year 2020:2024      # range (inclusive)
bip search --year 2022:          # 2022 and later
bip search --year :2020          # 2020 and earlier

# Combine keyword + filters
bip search "deep mutational scanning" --author "Bloom" --year 2023:

Multiple authors use AND logic - all must appear in the paper.

Author matching rules:

• Single word (e.g., -a "Yu") → exact last name match (won't match "Yujia")
• Two+ words (e.g., -a "Tim Yu") → exact last name + first name prefix
• Comma format (e.g., -a "Yu, Tim") → same as above

Query Formulation Tips

Keep queries short and specific - Long conceptual queries perform poorly:

• Bad: "correlation between BME criterion and Felsenstein likelihood around correct tree"
• Good: "BME Felsenstein likelihood phylogeny" or "Bruno WEIGHBOR likelihood"

Use --author flag instead of embedding names in query - Precise last name matching:

• Good: bip search -a "Yu" -a "Bloom" --year 2022: (exact last name match)
• Good: bip search -a "Tim Yu" -a "Bloom" (first prefix + exact last name)
• Bad: bip search "Tim Yu Bloom" (keyword search is substring-based)

Use specific method/algorithm names:

• "WEIGHBOR", "FASTME", "neighbor joining" rather than general descriptions

Systematic Search Workflow

For finding a specific paper or result:

1. Local library first (fastest, already curated):

   # Use flags for author/year filtering (most reliable)
   bip search -a "AuthorName" --year 2020:
   bip search "topic" -a "Author"
   
   # Or plain keyword search
   bip search "author topic"
   bip semantic "conceptual description"  # for topic-heavy queries
   

2. External keyword search with author names:

   bip asta search "AuthorName keyword1 keyword2" --limit 20 --human
   

3. Broaden if needed - remove author, try synonyms:

   bip asta search "minimum evolution likelihood" --human
   bip asta search "distance method maximum likelihood phylogeny" --human
   

4. Citation tracing - if you find a related paper, check what cites it:

   bip asta citations DOI:10.xxxx/yyyy --limit 50 --human
   

5. MCP tools directly - for more control over fields and filters:

   mcp__asta__search_papers_by_relevance with specific date ranges
   mcp__asta__get_citations with publication_date_range filter
   

Snippet Search Caveats

The bip asta snippet command can be slow and unreliable (timeouts are common). Alternatives:

• Use keyword search first to find candidate papers
• Use MCP mcp__asta__snippet_search directly with smaller limits
• If snippet times out, fall back to bip asta search

S2 vs ASTA: When to Use Which

Both access Semantic Scholar's paper database but through different APIs:

Rule of thumb: Use bip asta for exploration, bip s2 when you want to modify your library.

See api-guide.md for detailed comparison.

Common Workflows

Find a Paper

1. Search local library first:

   bip search "Schmidler phylogenetics"
   # or for topic-heavy queries:
   bip semantic "importance sampling MCMC"
   

2. Get PDF path for a result:

   bip get <id>
   # pdf_path field + "/Users/matsen/Google Drive/My Drive/Paperpile"
   

3. If not in library, search externally:

   bip asta search "phylogenetic inference"
   

Update Library from Paperpile

1. Export from Paperpile (JSON format) to ~/Downloads
2. Find the export file:

   ls -t ~/Downloads/Paperpile*.json | head -1
   

3. Import:

   bip import --format paperpile "<path>"
   

4. Optionally delete the export file after confirming success

Explore Literature

1. Search by topic:

   bip asta search "variational inference phylogenetics" --limit 20
   

2. Find specific text passages:

   bip asta snippet "Bayesian phylogenetic inference"
   

3. Trace citations:

   bip asta citations DOI:10.1093/sysbio/syy032
   bip asta references DOI:10.1093/sysbio/syy032
   

4. Add interesting papers to your collection:

   bip s2 add DOI:10.1093/sysbio/syy032
   

See workflows.md for detailed workflow instructions.

Output Format

All commands output JSON by default. Add --human for readable format:

bip asta search "phylogenetics" --human
bip s2 lookup DOI:10.1234/example --human

Paper ID Formats

Both S2 and ASTA accept these identifier formats:

• DOI:10.1093/sysbio/syy032
• ARXIV:2106.15928
• PMID:19872477
• CorpusId:215416146
• Raw Semantic Scholar ID (40-char hex)

Concept Nodes (Knowledge Graph)

Build a knowledge graph by creating concepts and linking papers to them.

Create Concepts

# Add a concept with name, aliases, and description
bip concept add somatic-hypermutation \
  --name "Somatic Hypermutation" \
  --aliases "SHM,shm" \
  --description "Process by which B cells diversify antibody genes"

# List all concepts
bip concept list --human

# Get a specific concept
bip concept get somatic-hypermutation --human

Link Papers to Concepts

# Use flags: -s (source paper), -t (target concept with concept: prefix), -r (relationship type), -m (summary)
bip edge add -s Halpern1998-yc -t concept:mutation-selection-model -r introduces \
  -m "Foundational paper defining the mutation-selection model"

bip edge add -s Yaari2013-dg -t concept:somatic-hypermutation -r models \
  -m "Introduces S5F model for SHM targeting"

Note: Use concept: prefix for concept targets, project: for project targets.

Standard Relationship Types

Query the Knowledge Graph

# Find all papers linked to a concept
bip concept papers somatic-hypermutation --human

# Filter by relationship type
bip concept papers somatic-hypermutation --type introduces

# Find what concepts a paper relates to
bip paper concepts Halpern1998-yc --human

Manage Concepts

# Update a concept
bip concept update somatic-hypermutation --description "Updated description"

# Delete a concept (warns if papers linked)
bip concept delete unused-concept

# Force delete (removes linked edges too)
bip concept delete old-concept --force

# Merge duplicate concepts
bip concept merge shm somatic-hypermutation --human

Troubleshooting

Snippet Search Timeouts

bip asta snippet frequently times out with "context deadline exceeded". Workarounds:

1. Reduce limit: --limit 5 instead of default
2. Use MCP directly: mcp__asta__snippet_search with small limit
3. Fall back to keyword search: bip asta search is more reliable
4. Retry once - sometimes it's transient

No Results Found

If searches return nothing relevant:

1. Check spelling of author names and technical terms
2. Simplify query - fewer terms, more common synonyms
3. Try both local and external:

   bip search "topic"        # local
   bip semantic "topic"      # local semantic
   bip asta search "topic"   # external
   

4. Check date filters - paper may be too old/new for range

Paper Not Found by ID

If bip get <id> or bip asta paper <id> fails:

1. Verify ID format: DOI:10.xxxx/yyyy (include prefix)
2. Try alternate IDs: Same paper may have DOI, PMID, arXiv ID
3. Search by title instead: bip asta search "exact paper title"

SQL Schema Errors

If you see errors like no such column: pmid or similar schema mismatches:

bip rebuild --force

The SQLite database is ephemeral and rebuilt from the JSONL source of truth. Schema changes require deleting and rebuilding.

Slow Performance

• bip s2 commands are rate-limited to 1 req/sec
• Use bip asta for bulk exploration (10 req/sec)
• Run searches in parallel when independent