Log Essence — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Log Essence (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Extract the essence of your logs for LLM analysis.
Analyzes log files using template extraction (Drain3) and semantic clustering (FastEmbed) to produce token-efficient summaries for LLM consumption. Includes automatic secret/PII redaction for safe external analysis.
https://github.com/user-attachments/assets/97d66d89-1745-4d0f-ac10-38744f98b636
<p align="center"> <em>Raw logs → Token-efficient summary with automatic secret redaction</em> </p>
# Using uv (recommended)
uvx log-essence
# Using pip
pip install log-essence# Analyze a log file
log-essence /var/log/app.log
# Analyze with glob pattern
log-essence "/var/log/*.log"
# Read from stdin — pipe any command's output
docker logs my-app 2>&1 | log-essence -
journalctl --since "1h ago" --no-pager | log-essence -
# Filter by severity
log-essence /var/log/app.log --severity ERROR WARNING
# Filter by time
log-essence /var/log/app.log --since 1h
# Strict redaction mode
log-essence /var/log/app.log --redact strict
# Disable redaction (for internal logs only)
log-essence /var/log/app.log --no-redact
# JSON output for programmatic use
log-essence /var/log/app.log -o json
# Watch mode for live log monitoring
log-essence /var/log/app.log --watch --interval 5
# Run as MCP server
log-essence --serve| Option | Description |
|---|---|
--token-budget N | Maximum tokens in output (default: 8000) |
--clusters N | Number of semantic clusters (default: 10) |
--severity LEVEL... | Filter by severity (ERROR, WARNING, INFO, DEBUG) |
--since TIME | Only logs since TIME (1h, 30m, 2d, 2025-01-01) |
--redact MODE | Redaction: strict, moderate (default), minimal, disabled |
--no-redact | Disable redaction |
-o, --output FORMAT | Output format: markdown (default) or json |
-w, --watch | Watch log file for changes (live updates) |
--interval SECONDS | Update interval for watch mode (default: 3.0) |
--config FILE | Path to config file |
--profile NAME | Use named configuration profile |
--serve | Run as MCP server |
--version | Show version number |
A browser-based interface for quick log analysis without command-line setup.
# Using uvx (recommended - no installation needed)
uvx --with log-essence[ui] log-essence ui
# Or specify a custom port
uvx --with log-essence[ui] log-essence ui --port 8080
# Using pip (if you prefer to install)
pip install log-essence[ui]
log-essence ui| Option | Description |
|---|---|
--port N | Port to run on (default: 8501) |
--no-browser | Don't auto-open browser |
log-essence can run as an MCP (Model Context Protocol) server, allowing Claude Desktop, Claude Code, Cursor, and other MCP-compatible clients to directly analyze logs from your system. This enables natural language interactions like:
"Check the logs from the last hour for any database errors" "What's causing the slow response times in my API?" "Analyze the docker logs and find the root cause of the crash"
Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"log-essence": {
"command": "uvx",
"args": ["log-essence", "--serve"]
}
}
}Restart Claude Desktop. You'll see log-essence listed in the MCP servers (🔌 icon).
The logs never leave your machine unredacted - log-essence strips sensitive data before Claude sees it, and the analysis runs locally using Drain3 and FastEmbed.
#### discover_log_sources
Find log sources for a code project — project-scoped, so it returns the project's own log files (vendored/VCS/build dirs pruned), the containers and Compose file belonging to that project's Docker Compose stack, and — since most code projects log to stdout rather than files — the run commands (from package.json scripts) you can pipe in, plus any standard agent-instruction files (CLAUDE.md, AGENTS.md, GEMINI.md, …) that document how to run and where logs go. It does not surface machine-wide system logs or other projects' containers. Each result is annotated with the tool or command to use. Call this first when you don't know what's available.
discover_log_sources() # scan the current directory
discover_log_sources(path="/repo") # scan a specific project#### get_logs
Analyze and consolidate log files.
get_logs(
path="/var/log/app.log",
token_budget=8000,
num_clusters=10,
severity_filter=["ERROR", "WARNING"],
since="1h",
redact=True # or "strict", "minimal", False
)#### get_container_logs
Analyze Docker container logs.
get_container_logs(
container="my-app",
since="1h",
token_budget=8000
)#### get_docker_logs
Analyze logs from Docker Compose services.
get_docker_logs(
path="/path/to/project",
services=["api", "worker"],
since="30m"
)#### get_error_chain
Trace error root causes through related log entries.
get_error_chain(
path="/var/log/app.log",
error_pattern="database",
time_window=60
)#### search_logs
Semantic search through log entries.
search_logs(
path="/var/log/app.log",
query="connection timeout",
top_k=10
)#### get_journald_logs
Analyze systemd journal logs.
get_journald_logs(
unit="nginx.service",
since="1h",
priority="err"
)#### list_containers
List running Docker containers.
list_containers()#### list_docker_services
List Docker Compose services in a project.
list_docker_services(path="/path/to/project")Every analysis tool (get_logs, get_docker_logs, get_container_logs, get_journald_logs) ends its summary with an analysis_id. Pass it back to get_raw_logs to pull the full, redacted lines on demand:
get_raw_logs(analysis_id) — all lines (paginate with start_line/max_lines).get_raw_logs(analysis_id, cluster_id=N) — only the lines behind "Cluster N"from the summary, so an agent can expand exactly the cluster under investigation without pulling the whole log back.
Retrieved lines carry the same redaction as the summary (redacted unless that analysis was run with redact=False).
Logs are automatically redacted before analysis to prevent leaking sensitive data to external LLMs.
| Mode | Description |
|---|---|
moderate | Default. Emails, IPs, credit cards, SSNs, phones, API keys |
strict | All moderate patterns + high-entropy strings in key=value |
minimal | Only obvious secrets (bearer tokens, API keys) |
disabled | No redaction (use only for internal logs) |
Redacted values use the format [TYPE:length?:hash4]:
# Input
[email protected] logged in from 192.168.1.50
Error processing payment for [email protected] card 4111111111111111
# Output (same entity → same hash for correlation)
[EMAIL:a7f2] logged in from [IPV4:3bc1]
Error processing payment for [EMAIL:a7f2] card [CC:16:d4e8]PII:
Secrets:
# Log Analysis Summary
**Format detected:** docker
**Total lines:** 15,432
**Unique patterns:** 47
**Semantic clusters:** 10
---
## Log Patterns by Severity
### Cluster 1: Database Operations
**Occurrences:** 5,234 | **Patterns:** 8
- `Query executed in <*>ms` (2,341x)
- `Connection pool size: <*>` (1,892x)
- `Transaction committed` (1,001x)
**Example:**2025-01-01T10:00:00Z INFO Query executed in 45ms
### Cluster 2: HTTP Requests
**Occurrences:** 4,123 | **Patterns:** 5
- `[IPV4:3bc1] - GET /api/<*> <*>` (3,456x)
- `Response time: <*>ms` (667x)# Clone and install
git clone https://github.com/petebytes/log-essence
cd log-essence
uv sync --all-groups
# Run tests
uv run pytest
# Lint
uv run ruff check src/ tests/
# Format
uv run ruff format src/ tests/MIT
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.