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grepai-search-advanced skill

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This skill enables efficient GrepAI searches with JSON outputs, compact mode, and AI agent integration for scripting and token optimization.

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---
name: grepai-search-advanced
description: Advanced search options in GrepAI. Use this skill for JSON output, compact mode, and AI agent integration.
---

# GrepAI Advanced Search Options

This skill covers advanced search options including JSON output, compact mode, and integration with AI agents.

## When to Use This Skill

- Integrating GrepAI with scripts or tools
- Using GrepAI with AI agents (Claude, GPT)
- Processing search results programmatically
- Reducing token usage in AI contexts

## Command-Line Options

| Option | Description |
|--------|-------------|
| `--limit N` | Number of results (default: 10) |
| `--json` | JSON output format |
| `--compact` | Compact JSON (80% token reduction) |

## JSON Output

### Standard JSON

```bash
grepai search "authentication" --json
```

Output:
```json
{
  "query": "authentication",
  "results": [
    {
      "score": 0.89,
      "file": "src/auth/middleware.go",
      "start_line": 15,
      "end_line": 45,
      "content": "func AuthMiddleware() gin.HandlerFunc {\n    return func(c *gin.Context) {\n        token := c.GetHeader(\"Authorization\")\n        if token == \"\" {\n            c.AbortWithStatus(401)\n            return\n        }\n        claims, err := ValidateToken(token)\n        ...\n    }\n}"
    },
    {
      "score": 0.82,
      "file": "src/auth/jwt.go",
      "start_line": 23,
      "end_line": 55,
      "content": "func ValidateToken(tokenString string) (*Claims, error) {\n    ..."
    }
  ],
  "total": 2
}
```

### Compact JSON (AI Optimized)

```bash
grepai search "authentication" --json --compact
```

Output:
```json
{
  "q": "authentication",
  "r": [
    {
      "s": 0.89,
      "f": "src/auth/middleware.go",
      "l": "15-45"
    },
    {
      "s": 0.82,
      "f": "src/auth/jwt.go",
      "l": "23-55"
    }
  ],
  "t": 2
}
```

**Key differences:**
- Abbreviated keys (`s` vs `score`, `f` vs `file`)
- No content (just file locations)
- ~80% fewer tokens for AI agents

## Compact Format Reference

| Full Key | Compact Key | Description |
|----------|-------------|-------------|
| `query` | `q` | Search query |
| `results` | `r` | Results array |
| `score` | `s` | Similarity score |
| `file` | `f` | File path |
| `start_line`/`end_line` | `l` | Line range ("15-45") |
| `total` | `t` | Total results |

## Combining Options

```bash
# 5 results in compact JSON
grepai search "error handling" --limit 5 --json --compact

# 20 results in full JSON
grepai search "database" --limit 20 --json
```

## AI Agent Integration

### For Claude/GPT Prompts

Use compact mode to minimize tokens:

```bash
# Agent asks for context
grepai search "payment processing" --json --compact --limit 5
```

Then provide results to the AI with file read tool for details.

### Workflow Example

1. **Search for relevant code:**
```bash
grepai search "authentication middleware" --json --compact --limit 3
```

2. **Get response:**
```json
{
  "q": "authentication middleware",
  "r": [
    {"s": 0.92, "f": "src/auth/middleware.go", "l": "15-45"},
    {"s": 0.85, "f": "src/auth/jwt.go", "l": "23-55"},
    {"s": 0.78, "f": "src/handlers/auth.go", "l": "10-40"}
  ],
  "t": 3
}
```

3. **Read specific files:**
AI reads `src/auth/middleware.go:15-45` for full context.

## Scripting with JSON

### Bash + jq

```bash
# Get just file paths
grepai search "config" --json | jq -r '.results[].file'

# Filter by score
grepai search "config" --json | jq '.results[] | select(.score > 0.8)'

# Count results
grepai search "config" --json | jq '.total'
```

### Python

```python
import subprocess
import json

result = subprocess.run(
    ['grepai', 'search', 'authentication', '--json'],
    capture_output=True,
    text=True
)

data = json.loads(result.stdout)
for r in data['results']:
    print(f"{r['score']:.2f} | {r['file']}:{r['start_line']}")
```

### Node.js

```javascript
const { execSync } = require('child_process');

const output = execSync('grepai search "authentication" --json');
const data = JSON.parse(output);

data.results.forEach(r => {
    console.log(`${r.score.toFixed(2)} | ${r.file}:${r.start_line}`);
});
```

## MCP Integration

GrepAI provides MCP tools with automatic compact mode:

```bash
# Start MCP server
grepai mcp-serve
```

MCP tools use compact format by default:

| MCP Tool | Description |
|----------|-------------|
| `grepai_search` | Semantic search |
| `grepai_trace_callers` | Find function callers |
| `grepai_trace_callees` | Find function callees |
| `grepai_trace_graph` | Full call graph |
| `grepai_index_status` | Index health |

## Token Optimization

### Token Comparison

For a typical search with 5 results:

| Format | Approximate Tokens |
|--------|-------------------|
| Human-readable | ~2,000 |
| JSON full | ~1,500 |
| JSON compact | ~300 |

### When to Use Each Format

| Format | Use Case |
|--------|----------|
| Human-readable | Manual inspection |
| JSON full | Scripts needing content |
| JSON compact | AI agents, token-limited contexts |

## Piping Results

### To File

```bash
grepai search "authentication" --json > results.json
```

### To Another Tool

```bash
# Open results in VS Code
grepai search "config" --json | jq -r '.results[0].file' | xargs code

# Copy first result path to clipboard (macOS)
grepai search "config" --json | jq -r '.results[0].file' | pbcopy
```

## Batch Searches

Run multiple searches:

```bash
#!/bin/bash
queries=("authentication" "database" "logging" "error handling")

for q in "${queries[@]}"; do
    echo "=== $q ==="
    grepai search "$q" --json --compact --limit 3
    echo
done
```

## Error Handling

### JSON Error Response

When search fails:

```json
{
  "error": "Index not found. Run 'grepai watch' first.",
  "code": "INDEX_NOT_FOUND"
}
```

### Checking for Errors in Scripts

```bash
result=$(grepai search "query" --json)
if echo "$result" | jq -e '.error' > /dev/null 2>&1; then
    echo "Error: $(echo "$result" | jq -r '.error')"
    exit 1
fi
```

## Best Practices

1. **Use compact for AI agents:** 80% token savings
2. **Use full JSON for scripts:** When you need content
3. **Use human-readable for debugging:** Easier to read
4. **Limit results appropriately:** Don't fetch more than needed
5. **Check for errors:** Parse JSON response properly

## Output Format

Advanced search output (JSON compact):

```json
{
  "q": "authentication middleware",
  "r": [
    {"s": 0.92, "f": "src/auth/middleware.go", "l": "15-45"},
    {"s": 0.85, "f": "src/auth/jwt.go", "l": "23-55"},
    {"s": 0.78, "f": "src/handlers/auth.go", "l": "10-40"}
  ],
  "t": 3
}
```

**Token estimate:** ~80 tokens (vs ~800 for full content)

Overview

This skill provides advanced search options for GrepAI including JSON output, compact mode, and AI agent integration. It helps you get machine-friendly results, reduce token usage for LLMs, and script or pipeline search workflows. Use it to return either full content for programmatic processing or a compact summary optimized for agents.

How this skill works

The skill exposes command-line flags to control output: --json to return structured JSON and --compact to emit an abbreviated, token‑efficient JSON shape. Results can include full snippet content, file locations and line ranges, similarity scores, and total counts. Compact mode replaces verbose keys with single-letter keys and omits content to save about 80% of tokens for AI usage.

When to use it

  • Integrating GrepAI results into automation, CI, or other tooling
  • Feeding search context to LLM agents (Claude, GPT) where tokens are limited
  • Batch or scripted processing of search results (Bash, Python, Node)
  • Index health checks and call-graph tooling via MCP integrations
  • Reducing payload size when passing results between services

Best practices

  • Use --compact when sending results to an LLM to minimize token cost
  • Use full --json when you need snippet content for static analysis or diffs
  • Limit results with --limit to fetch only what you need
  • Pipe JSON through jq or parse in your language to check for .error before proceeding
  • Combine compact search with a file-read tool so the agent requests only necessary file ranges

Example use cases

  • Run grepai search "auth middleware" --json --compact --limit 3 and let an agent read only selected file ranges
  • Script nightly scans: loop queries and write compact JSON to a central index for downstream processing
  • Integrate with MCP tools that default to compact format to power call-graph and trace lookups
  • Use full JSON with --limit 20 when building a code-intelligence dashboard that shows snippets
  • Pipe search output into jq to filter by score and then open matching files in an editor

FAQ

What does compact mode change in the output?

Compact mode shortens keys (e.g., q, r, s, f, l, t), removes snippet content, and returns only metadata like file paths, line ranges, and scores to greatly reduce token size.

When should I use full JSON instead of compact JSON?

Use full JSON when you need code snippet contents for analysis, debugging, or display; use compact JSON when passing context to token-limited AI agents or for lightweight tooling.