Skip to content
Back to skills

Depth Search

ASecurity

Deep multi-source research combining academic MCPs (arxiv, semantic-scholar, paper-search, deepwiki), Exa semantic search, and local ~/.topos knowledge base. Use for comprehensive research requiring multiple sources. NEVER fall back to web_search - ask user for help instead.

  • 666 stars
  • 0 votes
  • 1 copy
  • 5 views
  • Added February 8, 2026
researchgogitdatabasedocumentation

Works with

  • mcp

Security analysis

A100/100

Scanned February 12, 2026

npx -y skills add majiayu000/claude-skill-registry --skill depth-search --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Depth Search?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Depth Search
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/majiayu000-depth-search/badge)](https://www.skillsdirectory.com/skills/majiayu000-depth-search)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: depth-search
description: Deep multi-source research combining academic MCPs (arxiv, semantic-scholar, paper-search, deepwiki), Exa semantic search, and local ~/.topos knowledge base. Use for comprehensive research requiring multiple sources. NEVER fall back to web_search - ask user for help instead.
version: 1.0.0
---


# Depth Search

Comprehensive multi-source research skill. Searches across academic databases, semantic web search, and local knowledge before asking the user for help.

## Search Order

Execute searches in this order, using parallel subagents where possible:

### 1. Local Knowledge Base (~/.topos)
Search `~/.topos` directory first for existing research, notes, and cached data:
- Use `glob` and `Grep` to find relevant files
- Check `.md`, `.org`, `.jl`, `.py`, `.json` files
- Look in subdirectories: `skills/`, `archived/`, `Gay.jl/`, etc.

### 2. Academic MCPs (parallel)
Launch parallel subagents to search all 4 academic sources:

| MCP | Tools | Best For |
|-----|-------|----------|
| **arxiv** | `search_papers`, `get_paper`, `download_paper` | Preprints, CS/physics/math papers |
| **semantic-scholar** | `paper_relevance_search`, `paper_details`, `paper_citations` | Citation analysis, author profiles |
| **paper-search** | `search_arxiv`, `search_pubmed`, `search_biorxiv`, etc. | Multi-source aggregation |
| **deepwiki** | `read_wiki_structure`, `read_wiki_contents`, `ask_question` | GitHub repo documentation |

### 3. Exa Semantic Search
Use Exa MCP for high-quality web search:
- `web_search_exa` - Semantic web search
- `crawling_exa` - Extract web content
- `company_research_exa` - Company research
- `deep_researcher_start` / `deep_researcher_check` - Deep research tasks

### 4. Ask User for Help
If all sources fail to find what's needed:
- **DO NOT fall back to `web_search`** - it's basic keyword matching only
- Instead, ask the user:
  - "I couldn't find [X] in academic databases, Exa, or local files. Can you provide a link, paper title, or more context?"
  - Suggest specific sources they might check manually
  - Offer to try different search terms

## Critical Rules

1. **NEVER use `web_search` as a fallback** - it's not equivalent to Exa
2. **NEVER use `web_search` in Task subagents** - use Exa tools instead
3. **Always search local ~/.topos first** - may have cached/annotated versions
4. **Use parallel subagents** for academic MCPs to maximize speed
5. **Ask user for help** rather than guessing or using inferior search

## Example Workflow

```
User: "Find papers on world models for LLMs"

1. Search ~/.topos for existing notes/papers
2. Launch 4 parallel Task subagents:
   - arxiv: search_papers("world models LLM")
   - semantic-scholar: paper_relevance_search("world models language models")
   - paper-search: search across all sources
   - deepwiki: check relevant GitHub repos
3. If needed, use Exa: web_search_exa("world models LLM research")
4. Synthesize results from all sources
5. If still not found: ask user for clarification
```

## Parallel Subagent Template

When searching academic sources, use this pattern:

```
Launch 4 parallel Task subagents:
- Task 1: Use arxiv MCP to search for [query]
- Task 2: Use semantic-scholar MCP to search for [query]  
- Task 3: Use paper-search MCP to search for [query]
- Task 4: Use deepwiki MCP to find related repos/docs
```

## What NOT To Do

❌ `web_search` as fallback when Exa fails  
❌ Single-source search when multiple are available  
❌ Skipping local ~/.topos search  
❌ Guessing answers without exhausting sources  
❌ Sequential searches when parallel is possible  

## What TO Do

✅ Search ~/.topos first for cached knowledge  
✅ Parallel subagents for academic MCPs  
✅ Exa for semantic web search  
✅ Ask user when sources are exhausted  
✅ Synthesize results from multiple sources  



## Scientific Skill Interleaving

This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:

### Graph Theory
- **networkx** [○] via bicomodule
  - Universal graph hub

### Bibliography References

- `algorithms`: 19 citations in bib.duckdb



## SDF Interleaving

This skill connects to **Software Design for Flexibility** (Hanson & Sussman, 2021):

### Primary Chapter: 10. Adventure Game Example

**Concepts**: autonomous agent, game, synthesis

### GF(3) Balanced Triad

```
depth-search (+) + SDF.Ch10 (+) + [balancer] (+) = 0
```

**Skill Trit**: 1 (PLUS - generation)

### Secondary Chapters

- Ch8: Degeneracy
- Ch4: Pattern Matching
- Ch2: Domain-Specific Languages

### Connection Pattern

Adventure games synthesize techniques. This skill integrates multiple patterns.
## Cat# Integration

This skill maps to **Cat# = Comod(P)** as a bicomodule in the equipment structure:

```
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826
```

### GF(3) Naturality

The skill participates in triads satisfying:
```
(-1) + (0) + (+1) ≡ 0 (mod 3)
```

This ensures compositional coherence in the Cat# equipment structure.

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.