# Lukasstrickler AI Dev Atelier Search

> Search

- Skill: `tomevault-io/lukasstrickler-ai-dev-atelier-search` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/lukasstrickler-ai-dev-atelier-search`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/lukasstrickler-ai-dev-atelier-search/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/lukasstrickler-ai-dev-atelier-search

---


# Search

Search web, library docs, and GitHub code using progressive escalation.

## Quick Start

**Decision Tree:**
- **Library/framework docs?** → Context7 `get-library-docs`
- **Code examples/patterns?** → GitHub Grep `grep_searchGitHub`
- **Web info/tutorials?** → Tavily `tavily_search` (fallback chain: Exa → Z.AI `webSearchPrime`)
- **Error screenshot/diagram?** → Z.AI Vision `diagnose_error_screenshot` / `understand_technical_diagram`
- **Multiple sources needed?** → Run tools in parallel

**Default Workflow:**
1. Start simple: `search_depth: "basic"`, `maxResults: 5`
2. If insufficient: Escalate to Level 2 (expand query, increase results)
3. If repeated problem: Escalate to Level 3 (parallel queries, extraction, crawling)

## Agent Roles

**If you are the main agent (orchestrator):**
- **External questions** → Fire 3-5 `librarian` agents in parallel with different angles
- **Local codebase patterns** → Fire `explore` in background
- **Quick web lookups** → Do Tavily yourself (faster than delegation overhead)
- **Build confidence** → Fire multiple librarians: 2 for docs, 2 for real-world examples, 2 to find edge cases/gotchas
- Collect results with `background_output`, synthesize, cross-validate

**If you are the librarian (subagent):**
- **You are the WORKHORSE** - do NOT be lazy or return minimal results
- **Fire 3-5 parallel tool calls** depending on request complexity (see TYPE A/B/C/D in your system prompt)
- **Vary your queries** - different angles, not the same pattern repeated
- **Always cite with permalinks** - every claim needs `[Source](url#L10-L20)` format
- **Rate your confidence** - end with: `CONFIDENCE: HIGH/MEDIUM/LOW` and why

### Subagent Calling Example

```typescript
// GOOD: Fire multiple librarians with different angles for comprehensive coverage
background_task({
  agent: "librarian",
  prompt: `Find OFFICIAL documentation for Next.js 15 App Router authentication.

FIRST: MUST load and read 'search' skill before starting
LEVEL: 3 (deep research - parallel queries, thorough extraction)
FOCUS: Official Next.js and next-auth docs only
TOOLS: Context7 for Next.js, next-auth docs
FORMAT: Use markdown tables for comparisons, code blocks for snippets
OUTPUT: Official recommended approach with doc permalinks
END WITH: CONFIDENCE rating (HIGH/MEDIUM/LOW) and reasoning`
})

background_task({
  agent: "librarian", 
  prompt: `Find REAL-WORLD implementations of Next.js 15 authentication.

FIRST: MUST load and read 'search' skill before starting
LEVEL: 3 (deep research - multiple pattern variations, cross-repo)
FOCUS: Production codebases on GitHub
TOOLS: grep_searchGitHub with queries: "getServerSession(", "auth(", language: TypeScript
FORMAT: For each example: repo name, permalink, architecture notes
OUTPUT: 3-5 code examples with GitHub permalinks, note patterns/variations
END WITH: CONFIDENCE rating (HIGH/MEDIUM/LOW) and reasoning`
})

background_task({
  agent: "librarian",
  prompt: `Find EDGE CASES and GOTCHAS for Next.js 15 authentication.

FIRST: MUST load and read 'search' skill before starting
LEVEL: 3 (deep research - cross-reference multiple sources)
FOCUS: Issues, discussions, Stack Overflow
TOOLS: zai-zread_search_doc for repo issues/discussions (thorough), tavily_search for blog posts/SO
FORMAT: Problem → Evidence → Solution table
OUTPUT: Common pitfalls, breaking changes, migration issues
END WITH: CONFIDENCE rating (HIGH/MEDIUM/LOW) and reasoning`
})

// Then collect and cross-validate:
// - Do real-world examples match official docs?
// - Are there gotchas the docs don't mention?
// - Synthesize into recommendation with overall confidence

// BAD: No skill loading, no structure
background_task({
  agent: "librarian", 
  prompt: "How does Next.js auth work?"  // Missing FIRST step, no level, no format = lazy results
})
```

## Tools Overview

### Tavily (Web Search)
| Tool | When to Use | Key Params |
|------|-------------|------------|
| `tavily_search` | General web search, tutorials, blog posts, news | `search_depth`: "basic"/"advanced", `maxResults`: 5-20, `time_range`: "day"/"week"/"month"/"year", `include_domains`: filter to specific sites |
| `tavily_extract` | Get full content from specific URLs (after search) | `extract_depth`: "basic"/"advanced", `query`: rerank chunks by relevance |
| `tavily_crawl` | Crawl multiple pages from a docs site | `max_depth`: 1-3, `limit`: max pages, `select_paths`: regex to include, `instructions`: natural language filter |
| `tavily_map` | Discover site structure before crawling | `max_depth`: 1-3, `limit`: max URLs to return |

### Web Fallback Providers

| Tool | When to Use | Key Params |
|------|-------------|------------|
| `websearch_web_search_exa` | **Secondary fallback** when Tavily quota/execution fails | `numResults` (default: 8), `type`: "auto"/"fast"/"deep"/"neural" |
| `webSearchPrime` (via `zai-web-search-prime` MCP) | **Tertiary fallback** when Exa also fails or returns empty/low-value results | `search_query` (required), `search_engine` (fixed: `"search-prime"`, set by MCP), `count`: 1-50, `search_recency_filter`, `search_domain_filter` |

### Context7 (Library Docs)
| Tool | When to Use | Key Params |
|------|-------------|------------|
| `resolve-library-id` | Get library ID (required first) | `libraryName`: package name |
| `get-library-docs` | Fetch official docs | `mode`: "code" for API/params, "info" for concepts; `topic`: specific area |

### GitHub Grep (Code Search)
| Tool | When to Use | Key Params |
|------|-------------|------------|
| `grep_searchGitHub` | Find real code patterns across GitHub | `query`: literal code pattern, `language`: ["TypeScript"], `repo`: "owner/repo", `path`: "/api/", `useRegexp`: true for regex |

**Critical:** GitHub Grep searches **literal code patterns**, not keywords!
- ✅ Good: `useState(`, `getServerSession`, `(?s)try {.*await`
- ❌ Bad: `react tutorial`, `how to authenticate`

### Z.AI Zread (Semantic GitHub Search)
| Tool | When to Use | Key Params |
|------|-------------|------------|
| `zai-zread_search_doc` | Semantic search for issues/PRs/docs when keyword search fails | `repo_name`: "owner/repo", `query`: natural language question, `language`: "en"/"zh" |

**Use when:** Code/keyword search misses context, need discussion threads, searching for "why" not "what". 

### Z.AI Vision (Visual Content)
| Tool | When to Use | Key Params |
|------|-------------|------------|
| `zai-vision_diagnose_error_screenshot` | Analyze error screenshots, stack traces | `image_source`: file path or URL, `prompt`: describe what help you need, `context`: when error occurred |
| `zai-vision_understand_technical_diagram` | Interpret architecture/flow/UML/ER diagrams | `image_source`: file path or URL, `prompt`: what to extract, `diagram_type`: "architecture"/"flowchart"/"uml"/"er-diagram" (optional) |
| `zai-vision_analyze_data_visualization` | Understand charts/graphs/dashboards | `image_source`: file path or URL, `prompt`: what insights needed, `analysis_focus`: "trends"/"anomalies"/"comparisons" |
| `zai-vision_ui_to_artifact` | Generate code from UI screenshots | `image_source`: file path or URL, `output_type`: "code"/"prompt"/"spec"/"description", `prompt`: specific requirements |

**Use when:** User provides screenshot, error image, architecture diagram, or UI mockup. 

### GitHub CLI (Repo Search)
```bash
# Repository structure
gh api "repos/{owner}/{repo}/git/trees/{branch}?recursive=1"

# Search issues
gh api -X GET search/issues -f q="repo:{owner}/{repo} is:issue {keywords}"

# Read file directly
webfetch("https://raw.githubusercontent.com/{owner}/{repo}/{branch}/{path}")
```

## Progressive Escalation Levels

### Level 1: Simple Search (Default)
**When:** Quick lookups, straightforward questions, first encounter

1. Tavily: `search_depth: "basic"`, `maxResults: 5`
2. Context7: `mode: "code"` for API, `mode: "info"` for concepts
3. GitHub Grep: literal code patterns with language filter
4. **Parallel execution** when appropriate

**Sufficient? → Done. Insufficient? → Level 2**

### Level 2: Enhanced Search
**When:** Initial results incomplete, need more examples, outdated results

1. **Expand query:** Add synonyms, context (keep <400 chars)
2. **Increase:** `maxResults: 10-15`, `search_depth: "advanced"`
3. **Filter domains:** `include_domains: ["stackoverflow.com", "github.com"]`
4. **Time filter:** `time_range: "year"` for recent info
5. **Two-step extraction:** Search → Filter by score (>0.5) → Extract top URLs
6. **Discussions/docs gap:** Use `search_doc` or `gh api search/issues` when keyword/code search misses context

**Sufficient? → Done. Insufficient? → Level 3**

### Level 3: Deep Research
**When:** Problem encountered 2+ times, complex topic, building knowledge base

1. **Parallel queries:** 3-5 query variations with synonyms
2. **Systematic extraction:** Top 5-10 URLs with `extract_depth: "advanced"`
3. **Website exploration:** `tavily_map` → `tavily_crawl`
4. **GitHub deep dive:** Multiple pattern variations, regex, cross-repo comparison
5. **Cross-reference:** Verify across multiple sources

## Key Tips (Reminders)

### Query Formulation
- **400 char limit** - Break complex queries into sub-queries
- **Natural language works better** - Full sentences > keywords
- **Be specific** - Include technology, use case, context
- For full guide: See `references/query-guide.md`

### Score-Based Filtering
- Tavily results include `score` (0-1)
- **>0.5 typically good** - Adjust based on distribution
- Filter before extracting to save credits

### Two-Step Extraction Pattern
```
1. Search with search_depth: "advanced"
2. Filter URLs by score (>0.5)
3. Extract top 2-5 URLs with extract_depth: "basic"
4. Upgrade to "advanced" only if needed
```

### GitHub Grep Patterns
```
# API usage
Query: getServerSession
Language: ['TypeScript'], Path: '/api/'

# Multiline with regex
Query: (?s)useEffect\(\(\) => {.*cleanup
useRegexp: true
```

### Cost Optimization
- `basic` = 1 credit, `advanced` = 2 credits
- Prefer two-step extraction over `include_raw_content: true`
- Use `tavily_map` before `tavily_crawl`

**Quota Management:**
- Default to Tavily for important/critical searches (better relevance when quota available)
- If Tavily fails due to quota/rate limit (429), fail over immediately to Exa (no retry)
- For other transient Tavily failures (timeout/5xx), do one jittered retry (~300-800ms)
- Fallback to Exa (`websearch_web_search_exa`) when Tavily still fails after that retry
- If Exa fails due to quota/rate limit, fail over immediately to Z.AI `webSearchPrime` (no retry)
- For other transient Exa failures (timeout/5xx), do one jittered retry (~300-800ms), then fail over to Z.AI
- If Exa is empty/low-quality, fallback to Z.AI `webSearchPrime`
- Don't loop retries across providers; fail over immediately to next provider

For advanced techniques: See `references/advanced-techniques.md`

## Common Patterns

| Pattern | Level 1 | Level 2 | Level 3 |
|---------|---------|---------|---------|
| **Error resolution** | Exact error + SO domain | Remove quotes, add context | Extract top answers, cross-ref docs |
| **Best practices** | "Tech best practices 2024" | Domain filter + extract | Parallel aspect searches |
| **API reference** | Context7 with topic | + Tavily + GitHub Grep | Crawl official docs |
| **Code patterns** | GitHub Grep literal | + language/path filters | Regex + cross-repo |

For workflow examples: See `references/examples/example-workflows.md`

## References

- **`references/reference-parameters.md`** - Complete parameter reference for all tools
- **`references/query-guide.md`** - Query structuring, 400 char limit, expansion strategies
- **`references/advanced-techniques.md`** - Two-step extraction, post-processing, cost optimization
- **`references/examples/example-workflows.md`** - Practical workflow examples

## Output

Search results are used directly in context. No files saved unless requested. For comprehensive research with evidence cards, use the `research` skill.

---
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<!-- tomevault:4.0:skill_md:2026-04-13 -->