
Understand Domain
- 1.1k installs
- 77.5k repo stars
- Updated July 30, 2026
- lum1104/understand-anything
understand-domain is an agent skill that runs extract-domain-context.py to scan a project directory and emit structured domain-context.json—sampling up to 5000 files—for developers onboarding LLM agents to unfamiliar cod
About
understand-domain is a skill from lum1104/understand-anything that scans any codebase and produces clean, structured domain context for LLM agents. The bundled extract-domain-context.py script walks a project root with limits of depth 6, 50 files per directory, 5000 files total, 40 sampled files, and capped lines per file, writing output to .understand-anything/intermediate/domain-context.json. A domain-analyzer agent then identifies business domains, flows, and steps. Developers reach for understand-domain when agents need accurate implementation or analysis in unfamiliar repositories without manual architecture tours.
- Scans project directories while respecting MAX_FILES_TOTAL=5000 and MAX_SAMPLED_FILES=40 limits
- Extracts structured JSON context focused on business domains, flows, and steps
- Supports 20+ languages via SOURCE_EXTENSIONS including TypeScript, Python, Go, Rust, Java, and more
- Outputs to .understand-anything/intermediate/domain-context.json for downstream domain-analyzer agents
- Enforces MAX_OUTPUT_BYTES=512KB to stay within agent context windows
Understand Domain by the numbers
- 1,125 all-time installs (skills.sh)
- +24 installs in the week ending Aug 5, 2026 (Skillselion tracking)
- Ranked #965 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/lum1104/understand-anything --skill understand-domainAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 1.1k |
|---|---|
| repo stars | ★ 77.5k |
| Security audit | 3 / 3 scanners passed |
| Last updated | July 30, 2026 |
| Repository | lum1104/understand-anything ↗ |
How do you extract domain context from a codebase?
Scan any codebase and generate clean, structured domain context that an LLM agent can immediately use for accurate analysis and implementation.
Who is it for?
Developers onboarding AI agents to large or unfamiliar repositories who need structured domain context before implementation tasks.
Skip if: Tiny single-file scripts or teams that already maintain complete architecture docs requiring no automated extraction.
When should I use this skill?
User asks to understand codebase domain, extract business context, or generate domain-context.json for agent analysis.
What you get
domain-context.json under .understand-anything/intermediate/ with scanned file tree, sampled sources, and domain flow metadata.
- domain-context.json
- Domain flow and step identification input
By the numbers
- Scans up to 5000 files with max tree depth 6 and 50 files per directory
- Samples up to 40 files into domain-context.json output
Files
/understand-domain
Extracts business domain knowledge — domains, business flows, and process steps — from a codebase and produces an interactive horizontal flow graph in the dashboard.
How It Works
- If a knowledge graph already exists (
.understand-anything/knowledge-graph.json), derives domain knowledge from it (cheap, no file scanning) - If no knowledge graph exists, performs a lightweight scan: file tree + entry point detection + sampled files
- Use
--fullflag to force a fresh scan even if a knowledge graph exists
Instructions
Phase 0: Resolve PROJECT_ROOT
Set PROJECT_ROOT to the current working directory.
Worktree redirect. If PROJECT_ROOT is inside a git worktree (not the main checkout), redirect output to the main repository root. Worktrees managed by Claude Code are ephemeral — .understand-anything/ written there is destroyed when the session ends, taking the domain graph with it (issue #133). Detect a worktree by comparing git rev-parse --git-dir against git rev-parse --git-common-dir; in a normal checkout or submodule they resolve to the same path, in a worktree they differ and the parent of --git-common-dir is the main repo root.
COMMON_DIR=$(git -C "$PROJECT_ROOT" rev-parse --git-common-dir 2>/dev/null)
GIT_DIR=$(git -C "$PROJECT_ROOT" rev-parse --git-dir 2>/dev/null)
if [ -n "$COMMON_DIR" ] && [ -n "$GIT_DIR" ]; then
COMMON_ABS=$(cd "$PROJECT_ROOT" && cd "$COMMON_DIR" 2>/dev/null && pwd -P)
GIT_ABS=$(cd "$PROJECT_ROOT" && cd "$GIT_DIR" 2>/dev/null && pwd -P)
if [ -n "$COMMON_ABS" ] && [ "$COMMON_ABS" != "$GIT_ABS" ]; then
MAIN_ROOT=$(dirname "$COMMON_ABS")
if [ -d "$MAIN_ROOT" ] && [ "${UNDERSTAND_NO_WORKTREE_REDIRECT:-0}" != "1" ]; then
echo "[understand-domain] Detected git worktree at $PROJECT_ROOT"
echo "[understand-domain] Redirecting output to main repo root: $MAIN_ROOT"
echo "[understand-domain] (Set UNDERSTAND_NO_WORKTREE_REDIRECT=1 to keep PROJECT_ROOT as the worktree.)"
PROJECT_ROOT="$MAIN_ROOT"
fi
fi
fiUse $PROJECT_ROOT (not the bare CWD) for every reference to "the current project" / <project-root> in subsequent phases.
Important: do not assume the plugin root is simply two directories above the skill path string. In many installations ~/.agents/skills/understand-domain is a symlink into the real plugin checkout. Prefer runtime-provided plugin roots first (for Claude), then fall back to universal symlinks, skill symlink resolution, and common clone-based install paths.
Resolve the plugin root like this:
SKILL_REAL=$(realpath ~/.agents/skills/understand-domain 2>/dev/null || readlink -f ~/.agents/skills/understand-domain 2>/dev/null || echo "")
SELF_RELATIVE=$([ -n "$SKILL_REAL" ] && cd "$SKILL_REAL/../.." 2>/dev/null && pwd || echo "")
COPILOT_SKILL_REAL=$(realpath ~/.copilot/skills/understand-domain 2>/dev/null || readlink -f ~/.copilot/skills/understand-domain 2>/dev/null || echo "")
COPILOT_SELF_RELATIVE=$([ -n "$COPILOT_SKILL_REAL" ] && cd "$COPILOT_SKILL_REAL/../.." 2>/dev/null && pwd || echo "")
PLUGIN_ROOT=""
for candidate in \
"${CLAUDE_PLUGIN_ROOT}" \
"$HOME/.understand-anything-plugin" \
"$SELF_RELATIVE" \
"$COPILOT_SELF_RELATIVE" \
"$HOME/.codex/understand-anything/understand-anything-plugin" \
"$HOME/.opencode/understand-anything/understand-anything-plugin" \
"$HOME/.pi/understand-anything/understand-anything-plugin" \
"$HOME/understand-anything/understand-anything-plugin"; do
if [ -n "$candidate" ] && [ -f "$candidate/package.json" ] && [ -f "$candidate/pnpm-workspace.yaml" ]; then
PLUGIN_ROOT="$candidate"
break
fi
done
if [ -z "$PLUGIN_ROOT" ]; then
echo "Error: Cannot find the understand-anything plugin root."
echo "Checked:"
echo " - ${CLAUDE_PLUGIN_ROOT:-<unset CLAUDE_PLUGIN_ROOT>}"
echo " - $HOME/.understand-anything-plugin"
echo " - ${SELF_RELATIVE:-<unresolved path derived from ~/.agents/skills/understand-domain>}"
echo " - ${COPILOT_SELF_RELATIVE:-<unresolved path derived from ~/.copilot/skills/understand-domain>}"
echo " - $HOME/.codex/understand-anything/understand-anything-plugin"
echo " - $HOME/.opencode/understand-anything/understand-anything-plugin"
echo " - $HOME/.pi/understand-anything/understand-anything-plugin"
echo " - $HOME/understand-anything/understand-anything-plugin"
echo "Make sure the plugin is installed correctly."
exit 1
fiUse $PLUGIN_ROOT for every reference to agent definitions in subsequent phases.
Phase 1: Detect Existing Graph
1. Check if $PROJECT_ROOT/.understand-anything/knowledge-graph.json exists 2. If it exists AND --full was NOT passed → proceed to Phase 3 (derive from graph) 3. Otherwise → proceed to Phase 2 (lightweight scan)
Phase 2: Lightweight Scan (Path 1)
The preprocessing script does NOT produce a domain graph — it produces raw material (file tree, entry points, exports/imports) so the domain-analyzer agent can focus on the actual domain analysis instead of spending dozens of tool calls exploring the codebase. Think of it as a cheat sheet: cheap Python preprocessing → expensive LLM gets a clean, small input → better results for less cost.
1. Run the preprocessing script bundled with this skill, passing $PROJECT_ROOT from Phase 0:
python ./extract-domain-context.py "$PROJECT_ROOT"This outputs $PROJECT_ROOT/.understand-anything/intermediate/domain-context.json containing:
- File tree (respecting
.gitignore) - Detected entry points (HTTP routes, CLI commands, event handlers, cron jobs, exported handlers)
- File signatures (exports, imports per file)
- Code snippets for each entry point (signature + first few lines)
- Project metadata (package.json, README, etc.)
2. Read the generated domain-context.json as context for Phase 4 3. Proceed to Phase 4
Phase 3: Derive from Existing Graph (Path 2)
1. Read $PROJECT_ROOT/.understand-anything/knowledge-graph.json 2. Format the graph data as structured context:
- All nodes with their types, names, summaries, and tags
- All edges with their types (especially
calls,imports,contains) - All layers with their descriptions
- Tour steps if available
3. This is the context for the domain analyzer — no file reading needed 4. Proceed to Phase 4
Phase 4: Domain Analysis
1. Read the domain-analyzer agent prompt from $PLUGIN_ROOT/agents/domain-analyzer.md 2. Dispatch a subagent with the domain-analyzer prompt + the context from Phase 2 or 3 3. The agent writes its output to $PROJECT_ROOT/.understand-anything/intermediate/domain-analysis.json
Phase 5: Validate and Save
1. Read the domain analysis output 2. Validate using the standard graph validation pipeline (the schema now supports domain/flow/step types) 3. If validation fails, log warnings but save what's valid (error tolerance) 4. Save to $PROJECT_ROOT/.understand-anything/domain-graph.json 5. Clean up $PROJECT_ROOT/.understand-anything/intermediate/domain-analysis.json and $PROJECT_ROOT/.understand-anything/intermediate/domain-context.json
Phase 6: Launch Dashboard
1. Auto-trigger /understand-dashboard to visualize the domain graph 2. The dashboard will detect domain-graph.json and show the domain view by default
#!/usr/bin/env python3
"""
extract-domain-context.py — Lightweight codebase scanner for domain knowledge extraction.
Scans a project directory and produces a structured JSON context file that the
domain-analyzer agent uses to identify business domains, flows, and steps.
Usage:
python extract-domain-context.py <project-root>
Output:
<project-root>/.understand-anything/intermediate/domain-context.json
"""
import json
import os
import re
import sys
from pathlib import Path
from typing import Any
# ── Configuration ──────────────────────────────────────────────────────────
MAX_FILE_TREE_DEPTH = 6
MAX_FILES_PER_DIR = 50
MAX_FILES_TOTAL = 5000
MAX_SAMPLED_FILES = 40
MAX_LINES_PER_FILE = 80
MAX_ENTRY_POINTS = 200
MAX_OUTPUT_BYTES = 512 * 1024 # 512 KB — keeps output within agent context limits
# File extensions we care about for domain analysis
SOURCE_EXTENSIONS = {
".ts", ".tsx", ".js", ".jsx", ".mjs", ".cjs",
".py", ".pyi",
".go",
".rs",
".java", ".kt", ".scala",
".rb",
".cs",
".php",
".swift",
".c", ".cpp", ".h", ".hpp",
".ex", ".exs",
".hs",
".lua",
".r", ".R",
}
# Directories to always skip
SKIP_DIRS = {
"node_modules", ".git", ".svn", ".hg", "__pycache__", ".tox",
"venv", ".venv", "env", ".env", "dist", "build", "out", ".next",
".nuxt", "target", "vendor", ".idea", ".vscode", "coverage",
".understand-anything", ".pytest_cache", ".mypy_cache",
"Pods", "DerivedData", ".gradle", "bin", "obj",
}
# Files that reveal project metadata
METADATA_FILES = [
"package.json", "Cargo.toml", "go.mod", "pyproject.toml",
"setup.py", "setup.cfg", "pom.xml", "build.gradle",
"Gemfile", "composer.json", "mix.exs", "Makefile",
"docker-compose.yml", "docker-compose.yaml",
"README.md", "README.rst", "README.txt", "README",
]
# ── Entry point detection patterns ─────────────────────────────────────────
ENTRY_POINT_PATTERNS: list[tuple[str, str, re.Pattern[str]]] = [
# HTTP routes
("http", "Express/Koa route", re.compile(
r"""(?:app|router|server)\s*\.\s*(?:get|post|put|patch|delete|all|use)\s*\(\s*['"](/[^'"]*?)['"]""",
re.IGNORECASE,
)),
("http", "Decorator route (Flask/FastAPI/NestJS)", re.compile(
r"""@(?:app\.)?(?:route|get|post|put|patch|delete|api_view|RequestMapping|GetMapping|PostMapping)\s*\(\s*['"](/[^'"]*?)['"]""",
re.IGNORECASE,
)),
("http", "Next.js/Remix route handler", re.compile(
r"""export\s+(?:async\s+)?function\s+(GET|POST|PUT|PATCH|DELETE|HEAD|OPTIONS)\b""",
)),
# CLI
("cli", "CLI command", re.compile(
r"""\.command\s*\(\s*['"]([\w\-:]+)['"]""",
)),
("cli", "argparse subparser", re.compile(
r"""add_parser\s*\(\s*['"]([\w\-]+)['"]""",
)),
# Event handlers
("event", "Event listener", re.compile(
r"""\.on\s*\(\s*['"]([\w\-:.]+)['"]""",
)),
("event", "Event subscriber decorator", re.compile(
r"""@(?:EventHandler|Subscribe|Listener|on_event)\s*\(\s*['"]([\w\-:.]+)['"]""",
)),
# Cron / scheduled
("cron", "Cron schedule", re.compile(
r"""@?(?:Cron|Schedule|Scheduled|crontab)\s*\(\s*['"]([^'"]+)['"]""",
re.IGNORECASE,
)),
# GraphQL
("http", "GraphQL resolver", re.compile(
r"""@(?:Query|Mutation|Subscription|Resolver)\s*\(""",
)),
# gRPC (only in .proto files — handled by file extension check below)
("http", "gRPC service", re.compile(
r"""^service\s+(\w+)\s*\{""", re.MULTILINE,
)),
# Exported handlers (generic)
("manual", "Exported handler", re.compile(
r"""export\s+(?:async\s+)?function\s+(handle\w+|process\w+|on\w+)\b""",
)),
]
# ── Gitignore support ──────────────────────────────────────────────────────
def parse_gitignore(project_root: Path) -> list[re.Pattern[str]]:
"""Parse .gitignore into a list of compiled regex patterns."""
gitignore = project_root / ".gitignore"
patterns: list[re.Pattern[str]] = []
if not gitignore.exists():
return patterns
for line in gitignore.read_text(errors="replace").splitlines():
line = line.strip()
if not line or line.startswith("#"):
continue
# Convert glob to regex (simplified)
regex = line.replace(".", r"\.").replace("**/", "(.*/)?").replace("*", "[^/]*").replace("?", "[^/]")
if line.endswith("/"):
regex = regex.rstrip("/") + "(/|$)"
try:
patterns.append(re.compile(regex))
except re.error as e:
print(f"Warning: skipping invalid gitignore pattern '{line}': {e}", file=sys.stderr)
return patterns
def is_ignored(rel_path: str, gitignore_patterns: list[re.Pattern[str]]) -> bool:
"""Check if a relative path matches any gitignore pattern."""
for pattern in gitignore_patterns:
if pattern.search(rel_path):
return True
return False
# ── File tree scanner ──────────────────────────────────────────────────────
def scan_file_tree(
root: Path,
gitignore_patterns: list[re.Pattern[str]],
max_depth: int = MAX_FILE_TREE_DEPTH,
) -> list[str]:
"""Return a flat list of relative file paths (source files only)."""
result: list[str] = []
def _walk(dir_path: Path, depth: int) -> None:
if depth > max_depth or len(result) >= MAX_FILES_TOTAL:
return
try:
entries = sorted(dir_path.iterdir(), key=lambda e: (not e.is_dir(), e.name.lower()))
except PermissionError:
return
file_count = 0
for entry in entries:
if len(result) >= MAX_FILES_TOTAL:
break
# Skip symlinks to avoid infinite loops
if entry.is_symlink():
continue
rel = str(entry.relative_to(root))
if entry.is_dir():
if entry.name in SKIP_DIRS:
continue
if is_ignored(rel + "/", gitignore_patterns):
continue
_walk(entry, depth + 1)
elif entry.is_file():
if file_count >= MAX_FILES_PER_DIR:
break
if entry.suffix not in SOURCE_EXTENSIONS:
continue
if is_ignored(rel, gitignore_patterns):
continue
result.append(rel)
file_count += 1
_walk(root, 0)
return result
# ── Entry point detection ──────────────────────────────────────────────────
def detect_entry_points(root: Path, file_paths: list[str]) -> list[dict[str, Any]]:
"""Scan source files for entry point patterns."""
entry_points: list[dict[str, Any]] = []
# Skip test files and the extraction script itself
test_patterns = re.compile(r"(?:\.test\.|\.spec\.|__tests__|_test\.py|test_\w+\.py|extract-domain-context\.py)")
for rel_path in file_paths:
if len(entry_points) >= MAX_ENTRY_POINTS:
break
if test_patterns.search(rel_path):
continue
full_path = root / rel_path
try:
content = full_path.read_text(errors="replace")
except (OSError, UnicodeDecodeError):
continue
lines = content.splitlines()
for entry_type, description, pattern in ENTRY_POINT_PATTERNS:
for match in pattern.finditer(content):
# Find line number
line_no = content[:match.start()].count("\n") + 1
# Extract a snippet (signature + a few lines)
start = max(0, line_no - 1)
end = min(len(lines), start + 5)
snippet = "\n".join(lines[start:end])
entry_points.append({
"file": rel_path,
"line": line_no,
"type": entry_type,
"description": description,
"match": match.group(0)[:120],
"snippet": snippet[:300],
})
if len(entry_points) >= MAX_ENTRY_POINTS:
break
if len(entry_points) >= MAX_ENTRY_POINTS:
break
return entry_points
# ── File signatures ────────────────────────────────────────────────────────
def extract_file_signatures(root: Path, file_paths: list[str]) -> list[dict[str, Any]]:
"""Extract exports and imports from each file (lightweight)."""
signatures: list[dict[str, Any]] = []
# Prioritize files likely to contain business logic
priority_keywords = [
"controller", "service", "handler", "router", "route", "api",
"model", "entity", "repository", "usecase", "use_case",
"command", "query", "event", "subscriber", "listener",
"middleware", "guard", "interceptor", "resolver",
"workflow", "flow", "process", "pipeline", "job", "task",
]
def priority_score(path: str) -> int:
lower = path.lower()
score = 0
for kw in priority_keywords:
if kw in lower:
score += 1
return score
sorted_paths = sorted(file_paths, key=priority_score, reverse=True)
for rel_path in sorted_paths[:MAX_SAMPLED_FILES]:
full_path = root / rel_path
try:
content = full_path.read_text(errors="replace")
except (OSError, UnicodeDecodeError):
continue
lines = content.splitlines()[:MAX_LINES_PER_FILE]
truncated = "\n".join(lines)
# Extract exports (JS/TS)
exports = re.findall(
r"export\s+(?:default\s+)?(?:async\s+)?(?:function|class|const|let|var|interface|type|enum)\s+(\w+)",
truncated,
)
# Extract exports (Python)
if not exports:
exports = re.findall(r"^(?:def|class)\s+(\w+)", truncated, re.MULTILINE)
# Extract imports (first 20)
imports = re.findall(
r"""(?:import\s+.*?from\s+['"]([^'"]+)['"]|from\s+([\w.]+)\s+import)""",
truncated,
)
import_list = [m[0] or m[1] for m in imports][:20]
signatures.append({
"file": rel_path,
"exports": exports[:20],
"imports": import_list,
"lines": len(content.splitlines()),
"preview": truncated[:500],
})
return signatures
# ── Metadata extraction ────────────────────────────────────────────────────
def extract_metadata(root: Path) -> dict[str, Any]:
"""Read project metadata files."""
metadata: dict[str, Any] = {}
for filename in METADATA_FILES:
filepath = root / filename
if not filepath.exists():
continue
try:
content = filepath.read_text(errors="replace")
except (OSError, UnicodeDecodeError):
continue
if filename == "package.json":
try:
pkg = json.loads(content)
metadata["package.json"] = {
"name": pkg.get("name"),
"description": pkg.get("description"),
"scripts": list((pkg.get("scripts") or {}).keys()),
"dependencies": list((pkg.get("dependencies") or {}).keys()),
"devDependencies": list((pkg.get("devDependencies") or {}).keys()),
}
except json.JSONDecodeError:
metadata["package.json"] = content[:500]
elif filename.endswith((".md", ".rst", ".txt")) or filename == "README":
metadata[filename] = content[:2000]
elif filename.endswith((".toml", ".cfg", ".mod")):
metadata[filename] = content[:1000]
elif filename.endswith((".json", ".yml", ".yaml", ".xml", ".gradle")):
metadata[filename] = content[:1000]
return metadata
# ── Main ───────────────────────────────────────────────────────────────────
def _truncate_to_fit(context: dict[str, Any]) -> dict[str, Any]:
"""Progressively trim context sections to stay under MAX_OUTPUT_BYTES."""
output = json.dumps(context, indent=2)
if len(output.encode()) <= MAX_OUTPUT_BYTES:
return context
# 1. Trim file tree to just a count
context["fileTree"] = context["fileTree"][:200]
output = json.dumps(context, indent=2)
if len(output.encode()) <= MAX_OUTPUT_BYTES:
return context
# 2. Trim previews in signatures
for sig in context.get("fileSignatures", []):
sig["preview"] = sig["preview"][:200]
output = json.dumps(context, indent=2)
if len(output.encode()) <= MAX_OUTPUT_BYTES:
return context
# 3. Trim snippets in entry points
for ep in context.get("entryPoints", []):
ep["snippet"] = ep["snippet"][:100]
output = json.dumps(context, indent=2)
if len(output.encode()) <= MAX_OUTPUT_BYTES:
return context
# 4. Reduce number of signatures and entry points
context["fileSignatures"] = context["fileSignatures"][:20]
context["entryPoints"] = context["entryPoints"][:100]
return context
def main() -> None:
if len(sys.argv) < 2:
print("Usage: python extract-domain-context.py <project-root>", file=sys.stderr)
sys.exit(1)
project_root = Path(sys.argv[1]).resolve()
if not project_root.is_dir():
print(f"Error: {project_root} is not a directory", file=sys.stderr)
sys.exit(1)
try:
# Ensure output directory exists
output_dir = project_root / ".understand-anything" / "intermediate"
output_dir.mkdir(parents=True, exist_ok=True)
output_path = output_dir / "domain-context.json"
print(f"Scanning {project_root} ...", file=sys.stderr)
gitignore_patterns = parse_gitignore(project_root)
file_tree = scan_file_tree(project_root, gitignore_patterns)
print(f" Found {len(file_tree)} source files", file=sys.stderr)
entry_points = detect_entry_points(project_root, file_tree)
print(f" Detected {len(entry_points)} entry points", file=sys.stderr)
signatures = extract_file_signatures(project_root, file_tree)
print(f" Extracted {len(signatures)} file signatures", file=sys.stderr)
metadata = extract_metadata(project_root)
print(f" Read {len(metadata)} metadata files", file=sys.stderr)
context = {
"projectRoot": str(project_root),
"fileCount": len(file_tree),
"fileTree": file_tree,
"entryPoints": entry_points,
"fileSignatures": signatures,
"metadata": metadata,
}
context = _truncate_to_fit(context)
output = json.dumps(context, indent=2)
output_path.write_text(output)
size_kb = len(output.encode()) / 1024
print(f" Wrote {output_path} ({size_kb:.0f} KB)", file=sys.stderr)
except Exception as e:
print(f"Error: {e}", file=sys.stderr)
sys.exit(1)
if __name__ == "__main__":
main()
Related skills
How it compares
Use understand-domain for automated domain JSON extraction; use architecture-doc skills when writing human-facing C4 or ADR documents.
FAQ
What file does understand-domain generate?
understand-domain runs extract-domain-context.py to write .understand-anything/intermediate/domain-context.json—a structured JSON context file the domain-analyzer agent uses for business domains, flows, and steps.
What scan limits does extract-domain-context.py enforce?
extract-domain-context.py caps file tree depth at 6, 50 files per directory, 5000 files total, and 40 sampled files—with per-file line limits—to keep domain extraction lightweight.
Is Understand Domain safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.