Results for “log-analysis”

Add the /bl switch to MSBuild-based commands to generate binary logs for build diagnostics and performance analysis.

Hunt for threats in Windows Event Logs using Chainsaw, a fast Rust-based forensic tool that runs Sigma rules, keyword searches, and artifact analysis offline.

Error handling review — silent failure detection, catch block analysis, error logging.

Extract, parse, and analyze Windows Event Logs (EVTX) using Chainsaw, Hayabusa, and EvtxECmd to detect lateral movement, persistence, and privilege escalation.

Build comprehensive forensic super-timelines using Plaso (log2timeline) to correlate events across file systems, logs, and artifacts into a unified chronological view.

Build forensic super timelines from disk images using Plaso (log2timeline) and triage them in Timesketch.

Investigate Active Directory compromise by analyzing authentication logs, replication metadata, Group Policy changes, and Kerberos ticket anomalies to identify attacker persistence and lateral movement paths.

Analyzes short-video scripts for logical flow, information density, and oral fluency to identify moments where viewers might lose interest.

Reads and analyzes application logs for debugging and monitoring.

Diagnose MSBuild build failures by analyzing .binlog files using an MCP server or text-log replay.

Search and analyze your own session logs (older/parent conversations) using jq.

Investigate a problem, log it to the debug changelog, cross-check past issues, and suggest a non-duplicate fix.

Query and filter Datadog logs from the shell using the Composio CLI. Run scoped log searches, pivot across services/environments, and export structured JSON for incident investigation and diagnostics.

Diagnoses a reported bug, error, test failure, or unexpected behavior through a 4-phase root-cause analysis before any code changes.

Search and analyze your own session logs (older/parent conversations) using jq.

Analyze gc log analyzer operations. Auto-activating skill for Performance Testing. Triggers on: gc log analyzer, gc log analyzer Part of the Performance Testing skill category. Use when analyzing or auditing gc log analyzer. Trigger with phrases like "gc log analyzer", "gc analyzer", "analyze gc log r".

Parses Simplicité log files from raw .txt format, filters fields to reduce noise, and outputs structured JSON for efficient AI context usage.

**Server Logs:**

Diagnose your own behavior by reading the structured logs you leave behind — turns.jsonl, events.jsonl, chat_history.jsonl, scheduler.yaml. Use when something has gone wrong (a message didn't land, a scheduled job isn't firing, a communication pattern feels off), when you need to understand a pattern over many turns, or when cost / token usage needs auditing. Covers jq query recipes and points at the debugging-jobs / debugging-communication / debugging-drift companion guides for specific failure modes.

debug-logging

Build ontology logs (ologs) from problem descriptions using categorical foundations. Use when designing problem taxonomies, classifying tasks for routing, building knowledge libraries, establishing formal analogies between domains via functor search, or translating between natural language and database schemas. NOT for OWL/RDF ontology work, query tuning, or graph modeling without functional-arrow discipline.

Operations, debugging, and optimization for DAG workflows. Performs root cause analysis on failures, profiles execution performance, aggregates results from parallel branches, bridges context between nodes, and learns patterns from execution history. Activate on "DAG failed", "why did it fail", "root cause", "performance profile", "aggregate results", "merge branches", "execution patterns", "optimize DAG". NOT for planning DAGs (use dag-planner), executing DAGs (use dag-runtime), or validating outputs (use dag-quality).

Log and search local text entries from the command line. Use when adding quick notes, searching past entries, or exporting a simple activity log.

Analyzes codebases to understand existing features, tracing entry points, execution paths, architecture layers, patterns, and dependencies before new development.

Structured logging strategy — levels, correlation IDs, context propagation, PII avoidance. Use when designing a logging approach, reviewing log statements, setting up log aggregation (ELK, Loki, CloudWatch), adding correlation IDs to a distributed system, or deciding what to log and what to keep out.

Configures monitoring systems, implements structured logging pipelines, creates Prometheus/Grafana dashboards, defines alerting rules, and instruments distributed tracing.

Search and analyze your own session logs (older/parent conversations) using jq.

Search and analyze your own session logs (older/parent conversations) using jq.

Debug issues by investigating logs, database state, and git history

Query and filter Datadog logs from the shell using the Composio CLI. Run scoped log searches, pivot across services/environments, and export structured JSON for downstream agents instead of click-driving the Datadog UI.