Semtools - Semantic Search & Document Parsing

Overview

Semtools is a high-performance CLI toolkit providing semantic search capabilities using AI embeddings and document parsing for unsupported formats. Unlike traditional text search (grep), semtools understands semantic meaning, enabling discovery of conceptually related content even when exact keywords don't match.

When to Use This Skill

Use semtools PROACTIVELY when:

Documentation & Configuration Exploration

• Searching across docs/ for relevant guides, architecture docs, or reference materials
• Finding examples in YAML manifests (ArgoCD applications, Helm values, Crossplane XRDs)
• Locating configuration patterns in config/, terraform/, or application directories
• Exploring unfamiliar parts of the codebase to understand patterns and conventions

Semantic Understanding Requirements

• When keyword search (grep) returns too many irrelevant results or misses important content
• When searching for concepts that might be described using different terminology
• When exploring how a feature or pattern is implemented across the codebase
• When the exact wording is unknown but the concept is clear

Document Analysis

• Parsing and searching PDF documentation, vendor guides, or research papers
• Analyzing large collections of heterogeneous documents
• Extracting information from Office documents (DOCX, PPTX)

Examples of When to Use

• "Find all examples of Vault authentication configuration" (may be described as "Vault auth", "authentication to Vault", "Vault login", etc.)
• "Search for documentation about Crossplane composition patterns" (semantic understanding of "composition" vs "XRD" vs "managed resources")
• "Locate YAML manifests using external secrets" (finds various ways of referencing external secrets)
• "Find similar error handling patterns" (understands conceptual similarity, not just keyword matches)

Installation & Setup

Semtools requires Rust and a LlamaCloud API key for parsing operations.

# Install semtools
cargo install semtools

# Set API key (required for parse command)
export LLAMA_CLOUD_API_KEY=your_api_key

# Add to shell profile for persistence
echo 'export LLAMA_CLOUD_API_KEY=your_api_key' >> ~/.zshrc

Core Workflow: Search Documentation

The primary workflow when searching documentation or configuration files:

Step 1: Decide on Workspace Usage

Create a workspace for repeated searches or large file collections:

# Create/activate workspace (recommended for multiple searches)
workspace use cluster-ops-docs
export SEMTOOLS_WORKSPACE=cluster-ops-docs

Skip workspace for one-off quick searches.

Step 2: Execute Semantic Search

Use recommended flags for consistent, high-quality results:

search "vault OIDC authentication" docs/ \
  --ignore-case \
  --n-lines 30 \
  --max-distance 0.3

Flag explanation:

• --ignore-case (or -i): Case-insensitive matching (ALWAYS use this)
• --n-lines 30 (or -n 30): Context lines (default 3 is too small, use 30-50)
• --max-distance 0.3 (or -m 0.3): Similarity threshold (0.3 is good default)

Step 3: Refine if Needed

Adjust search parameters based on results:

# Too many results? Tighten similarity threshold
search "query" docs/ -i -n 30 -m 0.2

# Too few results? Loosen similarity threshold
search "query" docs/ -i -n 30 -m 0.4

# Need more context? Increase lines
search "query" docs/ -i -n 50 -m 0.3

Common Search Patterns

Pattern 1: Quick Documentation Search

For one-off searches without workspace overhead:

search "crossplane composition patterns" docs/ -i -n 30 -m 0.3

Pattern 2: Research Mode with Workspace

For exploring a topic with multiple related searches:

# Setup workspace once
workspace use architecture-research
export SEMTOOLS_WORKSPACE=architecture-research

# Multiple searches (fast after first one)
search "service mesh networking" docs/ -i -n 30 -m 0.3
search "cilium cluster mesh" docs/ -i -n 30 -m 0.3
search "BGP configuration" docs/ -i -n 30 -m 0.3

Pattern 3: Multi-Directory Configuration Search

Search across multiple directories for configuration patterns:

search "external secrets configuration" apps/ argocd/ crossplane/ \
  -i -n 40 -m 0.3

Pattern 4: YAML Manifest Search

Find specific patterns in Kubernetes/Helm manifests:

# Find ingress configurations with authentication
search "ingress with oauth2 proxy" apps/ -i -n 30 -m 0.3

# Find Crossplane resource examples
search "vault kubernetes role composition" crossplane/ -i -n 30 -m 0.3

# Find ArgoCD sync configurations
search "sync waves and hooks" argocd/ -i -n 25 -m 0.3

Pattern 5: Pre-filter with grep

Combine exact-match filtering with semantic search:

# Find files mentioning "vault", then semantic search within
grep -l "vault" apps/*/values.yaml | \
  xargs search "authentication configuration" -i -n 30 -m 0.3

# Pre-filter by section, then semantic search
cat docs/reference/*.md | grep -A 50 "## Authentication" | \
  search "OIDC provider setup" -i -n 20 -m 0.3

Document Parsing Workflow

Parse unsupported file formats (PDF, DOCX, PPTX) into searchable markdown.

Step 1: Create Workspace for PDFs

workspace use vendor-docs
export SEMTOOLS_WORKSPACE=vendor-docs

Step 2: Parse Documents

# Parse PDFs (results cached to ~/.parse/)
parse docs/vendor/*.pdf

# Parse multiple formats
parse whitepaper.pdf guide.docx presentation.pptx

Step 3: Search Parsed Content

# Search cached parsed files
search "API authentication" ~/.parse/*.pdf.md -i -n 30 -m 0.3

# Or parse and search in pipeline
parse document.pdf | xargs cat | search "security model" -i -n 40 -m 0.3

Step 4: Repeated Searches

Subsequent searches use cached embeddings (very fast):

search "rate limiting" ~/.parse/ -i -n 30 -m 0.3
search "error handling" ~/.parse/ -i -n 30 -m 0.3

Advanced Workflows

Workflow: Complex Research Pipeline

Chain Unix tools for powerful document processing:

# Find YAML files, pre-filter with grep, then semantic search
find apps/ argocd/ -name "*.yaml" | \
  xargs cat | \
  grep -i "ingress" | \
  search "TLS certificate management" -i -n 30 -m 0.3

Workflow: PDF Document Analysis

Analyze large PDF collections efficiently:

# Setup dedicated workspace
workspace use research-papers
export SEMTOOLS_WORKSPACE=research-papers

# Parse all PDFs once (cached)
parse papers/*.pdf

# Run multiple semantic queries (fast)
search "kubernetes security" ~/.parse/ -i -n 50 -m 0.2
search "container isolation" ~/.parse/ -i -n 50 -m 0.3
search "network policies" ~/.parse/ -i -n 50 -m 0.3

# Clean up when done
workspace prune

Workflow: Codebase Pattern Discovery

Discover how patterns are implemented across the codebase:

# Find authentication implementations
search "authentication middleware" src/ -i -n 40 -m 0.3

# Find error handling patterns
search "error propagation patterns" src/ lib/ -i -n 30 -m 0.3

# Find similar API endpoint structures
search "REST endpoint with validation" src/api/ -i -n 35 -m 0.3

Understanding Distance Thresholds

The --max-distance parameter controls semantic similarity (cosine distance):

Threshold	Precision	Recall	Use When
0.2	Very High	Low	Need only highly relevant, precise matches
0.3	High	Medium	Recommended default, good balance
0.4	Medium	High	Exploratory search, broader results
0.5+	Low	Very High	Very broad search, discovery mode

General guidance:

• Start with 0.3 (good default)
• If too many irrelevant results → decrease to 0.2
• If missing relevant results → increase to 0.4
• For discovery/exploration → use 0.4-0.5

Best Practices

1. Always Use These Three Flags

For consistent, high-quality results, always use:

search "query" path/ -i -n 30 -m 0.3

Why:

• -i: Don't know how terms are capitalized in files
• -n 30: Default 3 is rarely sufficient context (use 30-50)
• -m 0.3: Good precision/recall balance

2. Use Workspaces for Large Operations

Create workspace before searching large file collections or running multiple related searches:

workspace use project-name
export SEMTOOLS_WORKSPACE=project-name
# First search generates embeddings (slower)
# Subsequent searches use cache (much faster)

Benefits:

• Dramatically faster repeated searches
• Cost-effective (avoids re-embedding)
• Automatic cache invalidation when files change

3. Pre-parse PDFs Once

Parse PDFs as a one-time operation, then search cached markdown:

# Parse once
parse documents/*.pdf

# Search many times (fast)
search "topic 1" ~/.parse/ -i -n 30 -m 0.3
search "topic 2" ~/.parse/ -i -n 30 -m 0.3

4. Chain with grep for Exact Pre-filtering

Combine exact-match filtering with semantic understanding:

# Find files with exact keyword, then semantic search
grep -l "kubernetes" docs/*.md | \
  xargs search "authentication patterns" -i -n 30 -m 0.3

5. Adjust Context Lines Based on Content Type

Different content types need different context amounts:

# Code/configs: 30-40 lines
search "query" src/ -i -n 35 -m 0.3

# Documentation: 40-50 lines
search "query" docs/ -i -n 45 -m 0.3

# Dense technical docs: 50+ lines
search "query" papers/ -i -n 60 -m 0.3

When NOT to Use Semtools

Don't use semtools when:

1. Simple Exact-Match Search

Use grep or Grep tool for literal string matching:

# Use grep, not semtools
grep -r "function_name" src/
grep "exact error message" logs/*.txt

2. Code Structure Search

Use ast-grep for AST-based code pattern matching:

# Use ast-grep, not semtools
ast-grep --pattern 'async function $NAME($$$)'

3. File Name Search

Use find or Glob tool for file path patterns:

# Use find/glob, not semtools
find . -name "*.yaml"
glob "apps/**/*.values.yaml"

4. Real-time Operations

Semtools requires embedding time; use grep for instant results:

# For instant results, use grep
grep "ERROR" logs/current.log

5. Very Small or Single-File Searches

Use native tools for focused, single-file operations:

# Use grep for single files
grep "keyword" single_file.txt

Tool Selection Guide

Need	Tool	Reason
Exact string match	grep	Fast, instant, literal matching
Code structure/AST	ast-grep	Understands syntax, structural patterns
File name patterns	find/Glob	Fast directory traversal
Semantic/concept search	semtools	Understands meaning, finds related content
Exploring unfamiliar code	semtools	Discovers patterns via semantic similarity
Multi-format docs	semtools	Parses PDFs, DOCX, searches semantically

Troubleshooting

Search Returns No Results

1. Increase distance threshold:

   search "query" files/ -i -n 30 -m 0.4  # or 0.5
   

2. Rephrase query using different terminology

3. Check file paths exist and are readable:

   ls docs/  # verify path
   

4. Verify workspace status:

   workspace status
   

Search is Slow

1. Use workspace for repeated searches:

   workspace use project
   export SEMTOOLS_WORKSPACE=project
   

2. Pre-parse PDFs to avoid parsing repeatedly

3. Reduce scope - search specific directories, not entire repo

Parse Fails

1. Check API key:

   echo $LLAMA_CLOUD_API_KEY  # should output your key
   

2. Verify network connection (LlamaParse requires internet)

3. Check file format (PDF, DOCX, PPTX supported)

Embeddings Seem Stale

# Remove stale cache entries
workspace prune

# Or create fresh workspace
workspace use new-workspace
export SEMTOOLS_WORKSPACE=new-workspace

Too Many Irrelevant Results

1. Tighten distance threshold:

   search "query" files/ -i -n 30 -m 0.2
   

2. Use more specific query terms

3. Pre-filter with grep:

   grep -l "exact_term" *.yaml | xargs search "broader query" -i -n 30 -m 0.3
   

Cost Considerations

Semtools uses LlamaCloud API for:

• Document parsing (PDF, DOCX, etc.)
• Embedding generation for semantic search

Cost optimization strategies:

• Use workspaces to cache embeddings (avoids re-embedding)
• Pre-parse documents once, search multiple times
• Parse → cache → search workflow minimizes API calls

Example costs:

• 910 ACL research papers analyzed for ~$0.68 (from docs)

Workspace Management

Create and Activate Workspace

workspace use my-project
export SEMTOOLS_WORKSPACE=my-project

Add to shell profile for persistence:

echo 'export SEMTOOLS_WORKSPACE=my-project' >> ~/.zshrc

Check Workspace Status

workspace status
# Shows: active workspace, cached files, size, last modified

Clean Up Workspace

# Remove stale/missing files from cache
workspace prune

Workspace Directory

Workspaces stored at: ~/.semtools/workspaces/<workspace-name>/

Examples for This Codebase

Search Architecture Documentation

search "service mesh design" docs/architecture/ -i -n 40 -m 0.3

Find Crossplane XRD Patterns

search "composition with managed resources" crossplane/ -i -n 30 -m 0.3

Locate Vault Configuration Examples

search "vault kubernetes authentication role" apps/ crossplane/ terraform/ \
  -i -n 30 -m 0.3

Search Terraform Modules

search "authentik group provisioning" terraform/modules/ -i -n 30 -m 0.3

Find ArgoCD Application Patterns

search "argocd sync waves and hooks" argocd/ -i -n 30 -m 0.3

Explore Helm Values

search "ingress configuration with TLS" apps/*/values.yaml -i -n 35 -m 0.3

Search Across Documentation Types

# Search guides, reference docs, and architecture docs
search "secret management patterns" docs/ -i -n 40 -m 0.3

Quick Reference Card

Essential Pattern

# Standard search command
search "<query>" <path> -i -n 30 -m 0.3

Create Workspace

workspace use <name>
export SEMTOOLS_WORKSPACE=<name>

Parse Documents

parse *.pdf
search "query" ~/.parse/ -i -n 30 -m 0.3

Adjust Precision/Recall

-m 0.2  # High precision (strict)
-m 0.3  # Balanced (default)
-m 0.4  # High recall (broad)

Resources

For detailed CLI documentation, see references/cli_reference.md.

External resources:

• GitHub: https://github.com/run-llama/semtools
• Documentation: https://github.com/run-llama/semtools/blob/main/README.md
• Examples: https://github.com/run-llama/semtools/tree/main/examples