Menu
Search conversation history for research context - papers discussed, citations analyzed, discoveries made, or questions explored.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Initialize a new user's research assistant. Use this on first interaction or when user asks to "get started", "set up", or "introduce yourself". Also use when you don't know the user's research interests or the human memory block still has placeholder text.
Walk the user through new Thoth features since their last onboarding or update. Use when the user asks "what's new", "what changed", or "what can you do now". Also use after check_whats_new returns updates to walk through them.
Create, manage, and iterate on research plan documents in the Obsidian vault. Use when the user asks for a research plan, literature review roadmap, or when you need to formalize your own working research strategy.
Conduct deep analysis of research papers, synthesize literature, and generate comprehensive reviews. Use when user needs thorough paper analysis, literature reviews, or cross-paper synthesis.
Manage external knowledge collections (textbooks, lecture notes, background material) and search them to support research. Use when user wants to upload reference material or query foundational knowledge.
Answer questions using your existing research collection and external knowledge. Use when user asks questions about papers they have, wants summaries, or seeks insights from their knowledge base.
| name | research-messages-search |
| description | Search conversation history for research context - papers discussed, citations analyzed, discoveries made, or questions explored. |
Find past research conversations, paper discussions, and analysis from your conversation history.
Most common use: Finding when you discussed a specific paper, topic, or research question.
User: "When did we discuss transformer architectures?"
Agent: "Let me search our conversation history for transformer discussions.
I'll use hybrid search (semantic + keyword) to find the most relevant messages."
Then execute the search:
npx tsx [SKILL_DIR]/scripts/search-messages.ts --query "transformer architectures" --limit 10
Present results:
Agent: "Found 8 conversations about transformers:
Most relevant:
- Dec 15, 2025: Analyzed 'Attention Is All You Need' paper
- Dec 18, 2025: Discussed transformer memory mechanisms
- Jan 3, 2026: Compared transformer vs Mamba architectures
Want me to expand around any of these to see the full context?"
Ask 2 questions to understand the search:
Question 1: What type?
Agent: "Are you looking for:
A) A specific paper we discussed?
B) Analysis of a research topic?
C) Discovery results from a query?
D) Citation network we built?
E) Something else?"
Question 2: Time range?
Agent: "Time frame:
A) Recent (last week)
B) This month
C) Specific date/period
D) Any time (full history)"
Route based on answers:
Type A (paper) + Recent → Paper title search, last 7 days
Type B (topic) + Any time → Semantic search, all history
Type C (discovery) + Month → Keyword "discovery", current month
Type D (citation) + Specific → Date-bounded search
Trigger: User asks about a specific paper
User: "What did we say about the BERT paper?"
Agent: "Let me search for BERT discussions."
[Run search with "BERT paper", focus on title/authors]
Agent: "Found 3 conversations:
- Nov 20: Initial BERT paper analysis
- Nov 22: Compared BERT vs RoBERTa
- Dec 1: Used BERT for sentiment analysis
The Nov 20 conversation has the main analysis. Want to see it?"
[If yes, use needle+expand strategy]
Trigger: User asks about research topic/concept
User: "When did we talk about citation networks?"
Agent: "Searching for citation network discussions..."
[Run semantic search, --mode vector for concept matching]
Agent: "Found 5 conversations about citation networks:
Most relevant:
- Jan 5: Built citation graph for ML papers
- Jan 8: Analyzed influential papers using PageRank
- Jan 10: Discussed loop closure in citations
These span multiple conversations. Want the full thread?"
[If yes, expand around first occurrence and follow chronologically]
Trigger: User asks about papers found from discovery
User: "What papers did we find about state space models?"
Agent: "Searching for state space model discoveries..."
[Search with "discovery state space models" + keyword mode]
Agent: "Found 2 discovery sessions:
- Dec 28: Discovered 15 SSM papers from ArXiv
- Jan 4: Found Mamba paper and variants
The Dec 28 session has the full paper list. Show that?"
Trigger: User wants full context around a specific finding
Agent: "Found the needle! Message from Dec 15 at 2:30 PM.
Getting context around that message..."
[Run get-messages with --before and --after]
Agent: "Here's the full conversation (10 messages before + 10 after):
[Show conversation thread]
That's the complete context. Need more?"
When to use each mode:
| Mode | Use When | Example |
|---|---|---|
hybrid (default) | General search | "transformer discussions" |
vector | Concept/semantic | "papers about memory" |
fts | Exact phrase | "Attention Is All You Need" |
Default to hybrid unless user needs exact matches or pure semantic.
Common time patterns:
# Last week
--start-date "2026-01-06" --end-date "2026-01-13"
# Specific month
--start-date "2025-12-01" --end-date "2025-12-31"
# After specific date
--start-date "2025-11-01"
# Before specific date
--end-date "2025-10-31"
Pro tip: Use ISO format YYYY-MM-DD for dates.
Effective search terms for research:
Examples:
"Attention Is All You Need" → Exact paper
transformer memory mechanisms → Topic discussion
Vaswani et al → Author search
citation network analysis → Analysis type
discovered mamba papers → Discovery results
Two-step strategy for full context:
Step 1: Find the needle
npx tsx [SKILL_DIR]/scripts/search-messages.ts \
--query "your search terms" \
--limit 5
Step 2: Expand around it
# Get context before
npx tsx [SKILL_DIR]/scripts/get-messages.ts \
--before "message-id-from-search" \
--limit 10
# Get context after
npx tsx [SKILL_DIR]/scripts/get-messages.ts \
--after "message-id-from-search" \
--order asc \
--limit 10
Symptom: Search returns 50+ messages, overwhelming
Fix: Narrow the search
Agent: "That search returned too many results. Let's narrow it:
Option A: Add time filter (when roughly was this?)
Option B: Add specific terms (any unique words?)
Option C: Use exact phrase (put in quotes)
Which helps?"
Symptom: Search returns 0 results
Fix: Broaden and diagnose
Agent: "No results for that search. Let's troubleshoot:
1. Try semantic search (concepts vs exact words):
--mode vector
2. Try broader terms:
'transformer' instead of 'transformer architecture'
3. Search all agents (if multi-agent setup):
--all-agents
Which should we try?"
Symptom: Found messages but not the right conversation
Fix: Expand correctly
Agent: "That's not the conversation you wanted. Let me:
1. Check the other search results (we have 4 more)
2. Expand more context (20 messages instead of 10)
3. Refine search terms (what's unique about that conversation?)
Which approach?"
Symptom: Topic discussed across multiple sessions
Fix: Search with sort, present chronologically
Agent: "This topic spans multiple conversations. Here's the timeline:
Session 1 (Dec 5): Initial discussion
Session 2 (Dec 8): Follow-up analysis
Session 3 (Dec 12): Final conclusions
Want to see all three in order, or just the most relevant?"
| Problem | Quick Fix |
|---|---|
| Search too slow | Reduce --limit to 5 |
| No results found | Use --mode vector for semantic search |
| Too many results | Add date range with --start-date |
| Wrong messages | Use exact phrase in quotes |
| Need more context | Use get-messages.ts with --before/--after |
| Want full thread | Expand before+after the needle |
| Multi-agent search | Add --all-agents flag |
| Need specific date | Use --start-date and --end-date (same day) |
| Results not relevant | Switch to --mode fts for exact keyword |
Use case: Finding which agent discussed a topic
Agent: "Searching across all agents for transformer discussions..."
[Run with --all-agents flag]
Agent: "Found discussions in 3 agents:
- Agent A (Lead Engineer): Technical analysis
- Agent B (Literature Review): Paper summaries
- Agent C (Research Assistant): Discovery results
Which agent's context do you want to explore?"
Results include agent_id - use with finding-agents skill to get agent details.
Core workflow:
Key principles:
Success: User finds the research conversation they were looking for and gets the full context they need.