server-log-analyzer

Analyzes server log files to detect problems, extract performance metrics, and provide troubleshooting insights. Triggers: "analyze logs", "log analysis", "c...

Security Scan

The skill's code and instructions match its stated purpose (parsing and analyzing log files); nothing in the provided files indicates unexpected network access, extra credentials, or system-wide changes, but the source is unknown and the provided script was partially truncated in the review so full certainty is limited.

Purpose & Capability

Name/description (server log analysis, exception tracking, performance metrics) align with the included code (scripts/log_analyzer.py) and the documentation. No unrelated binaries, env vars, or config paths are requested.

Instruction Scope

SKILL.md instructs only to run the provided Python script against a log file. The script reads and parses the supplied log file, extracts tracebacks and paths, and builds a report. It does not (in the inspected portions) access other system files, environment variables, or external endpoints. Note: the ExceptionTracker records file paths found in tracebacks (it filters paths that contain '/home/javanep/' or '/home/' and filters out library paths like 'paddle' and 'phi'), which is project-specific behavior but not in itself malicious.

Install Mechanism

No install spec — instruction-only plus a contained Python script that uses only the standard library. No downloads, package managers, or archive extraction were requested.

Credentials

The skill requires no credentials, no environment variables, and no config paths. The requested resources are proportional to the stated functionality.

Persistence & Privilege

always is false and the skill does not attempt to modify other skills or system-wide settings in the provided materials. No persistence or elevated privileges are requested.

Assessment

This skill appears coherent for local log analysis: it only needs the log file you point it at and uses the Python standard library. Before installing or running it: 1) Review the complete scripts/log_analyzer.py (the provided excerpt was truncated) to confirm there are truly no network calls, subprocess.exec usage, or file writes beyond the output/report. 2) Do not feed sensitive logs (containing PII, secrets, tokens) unless you trust the skill or run it in an isolated environment, since parsed output could contain sensitive data (tracebacks may include file paths and error messages). 3) If you plan to run this in production, run it first on a sample non-sensitive log and/or in a sandbox. If you want, provide the full untruncated script and I'll re-check for any hidden network, exec, or file-exfiltration behaviors to increase confidence.

Analyzes server log files to identify problems, extract performance metrics, and provide actionable insights for troubleshooting.

Supported Log Formats

[YYYY/MM/DD HH:MM:SS] module.path LEVEL line_number: message

Example:

[2026/04/15 12:08:03] sanhai.flow.linear_data_flow INFO 127: flow_id:2044266474671067136 - Worker completed

Usage

Basic Analysis

python scripts/log_analyzer.py /path/to/your/logfile.log

JSON Output (for automation)

python scripts/log_analyzer.py /path/to/your/logfile.log --json

Features

1. Log Statistics

• Counts INFO, WARNING, ERROR, CRITICAL entries
• Shows time range and duration
• Module-level statistics

2. Problem Detection

Automatically detects common issues:

Severity	Issue Type	Detection Pattern
High	Database failures	[DB] update/insert failed
High	Missing components	has no corrector
Medium	Notification failures	email notification failed
Medium	Classification errors	paper type error
Low	ID recognition failures	invalid student number

3. Python Exception Tracking

Extracts Python traceback information:

• Exception type and message
• Source file locations (filters out framework code)
• Key code location in your project

4. Performance Metrics

• TPS (Tasks Per Second)
• Batch processing time
• Worker-level timing

Output Sections

Section	Content
Summary	Log level counts, time range
Exceptions	Python exceptions (highest priority)
Performance	TPS, processing time
Issues	Problems by severity
Modules	Module call frequency

Performance Thresholds

Metric	Normal	Warning	Critical
TPS	50-300	<20	<10
Batch Time	<2s	>5s	>10s

Notes

• Large log files (>10MB) may take longer to process
• Exception tracking filters out framework/library code
• Results are sorted by severity (exceptions first)