Results for “mysqlbinlog”

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

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

Diagnose MSBuild build performance bottlenecks using binary log analysis, covering timeline analysis, performance summary interpretation, and seven common bottleneck categories.

name: sync-minecontext

Optimize MSBuild build parallelism by configuring /maxcpucount, graph build mode, project references, and analyzing binlogs to reduce multi-project solution build times.

MindOS 是用户的本地知识助手，也是跨会话、跨 Agent 共享的知识库。它保存决策记录、会议纪要、SOP、 排错经验、架构选型、调研结论和偏好设置。 仅 mindRoot 知识库内任务。不用于：改代码仓库、项目源码、KB 外路径。 核心概念：空间、指令(INSTRUCTION.md)、技能(SKILL.md)；笔记可承载指令与技能。 触发场景：保存或记录任何内容、搜索历史笔记或上下文、更新或编辑文件、整理或重组文件结构、 执行SOP或工作流、捕获对话中的决策、复盘或总结经验、追加表格或CSV数据、跨Agent交接上下文、 提炼经验教训、同步关联文档、查找之前是否讨论过某事、查询历史决策、查找模板或SOP、 为会议准备上下文、快速暂存到暂存台、整理暂存台、知识健康检查、检测知识冲突或矛盾、 查找过期内容。 触发词：帮我记下来、搜一下我的笔记、更新知识库、整理文件、执行工作流、保存到知识库、 记录一下、整理笔记、复盘、提炼经验、同步文档、查一下之前的记录、有没有相关的笔记、 我之前写过什么、把这个存起来、总结一下保存、交接给其他Agent、追加到表格、 放到暂存台、整理暂存台、知识健康检查、检测知识冲突。 主动行为——不要等用户提到 MindOS： (1) 用户的问题暗示可能存在历史记录（过去的决策、之前的讨论、会议纪要）→ 先搜 MindOS， 即使没有明确提到知识库。 (2) 完成有价值的工作后（修了 bug、做了决策、总结了经验、选定了架构、开完了会）→ 主动提议保存到 MindOS，方便以后查阅。 (3) 经历了较长或多主题的对话后 → 建议把关键决策和上下文持久化。

Extracts a specified URL parameter (such as loc) from a MySQL text column, derives the domain from each parameter value, and counts occurrences per domain, sorted descending.

Analyze Linux system logs including auth.log, syslog, systemd journal, and auditd to reconstruct user activity, detect unauthorized access, and establish event timelines on compromised systems.

Analyze WAF logs from ModSecurity, AWS WAF, or Cloudflare to detect SQL injection attack campaigns, classify injection types, and generate incident reports with OWASP classification.

Runs MySQL queries from an AI coding agent using the mysql2 Node.js library, with setup instructions for npm and TypeScript.

Hunt for adversary abuse of Living Off the Land Binaries (LOLBins) by analyzing endpoint process creation logs for suspicious execution patterns of legitimate Windows system binaries used for malicious purposes.

Logs board meeting decisions with a two-layer memory architecture, separating raw transcripts from approved decisions, and provides commands to review past decisions and overdue action items.

MySQL relational database. Covers queries, indexes, and optimization. Use when working with MySQL databases. USE WHEN: user mentions "mysql", "mariadb", asks about "AUTO_INCREMENT", "ON DUPLICATE KEY UPDATE", "GROUP_CONCAT", "mysql specific syntax" DO NOT USE FOR: PostgreSQL - use `postgresql` instead, MongoDB - use `mongodb` instead, Oracle - use `oracle` instead, SQL Server - use `sqlserver` instead

将 Dayflow 数据库增量同步到 Obsidian。当用户说"同步 dayflow"、"sync dayflow"或"/sync-dayflow"时使用此 skill。

Merges multiple diagnosis snapshots from dbs-save into a single, timestamped Markdown report organized by topic.

Streams MySQL or MariaDB row-level changes into Redpanda or Kafka via the mysql_cdc input, covering binlog setup, snapshots, checkpointing, per-table routing, AWS RDS IAM auth, and Enterprise lakehouse destinations.

**Server Logs:**

Restores the most recent diagnosis snapshot saved by dbs-save, allowing users to continue a previous diagnostic session.

Save the current diagnosis state to disk for cross-session recall, including conclusions, rejected directions, and next steps.

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

Analyzes Claude Code session logs to report token usage, tool and skill rankings, and session search by prompt text.

MySQL and MariaDB schema, query, indexing, transaction, replication, and connection-pool patterns for production backends.

Detects insider data exfiltration by analyzing DLP policy violations, file access patterns, upload volume anomalies, and off-hours activity in endpoint and cloud logs using pandas for behavioral analytics and statistical baselines.

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

Python logging with the standard library logging module and structlog. Covers log levels, handlers, formatters, structured logging, and production best practices for FastAPI/Django applications. USE WHEN: user mentions "python logging", "fastapi logging", "django logging", asks about "how to log in python", "python logging module", "logging configuration python" DO NOT USE FOR: Node.js logging - use `nodejs-logging` instead, Java logging - use `slf4j` or `logback`, structlog-specific - use `structlog` skill for deep dive

debug-logging

Essential fuzzing payloads: SQL injection, command injection, special characters. Curated essentials for vulnerability testing.

Log workouts, plan routines, track progress, and get intelligent coaching for any fitness level.

Detects DNS-based data exfiltration, tunneling, and DGA communication by analyzing query logs with entropy analysis, volume anomalies, and subdomain length detection in SIEM platforms.

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.

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.

SQL injection occurs when untrusted user input is interpolated directly into database queries, allowing attackers to alter query logic. Detect via single-quote errors, boolean-based blind responses (AND 1=1 vs AND 1=2), time-delay payloads (SLEEP, WAITFOR), UNION column enumeration, and error messages from MySQL, Oracle, MSSQL, PostgreSQL. Tools: sqlmap, sqlbftools, Burp Suite, wfuzz with SQLi fuzz strings.

Executes MySQL database development and review tasks based on user-provided rules, covering naming constraints, index design, and data archiving for large datasets.

Search and analyze conversation history stored in session JSONL files using jq and shell commands.

Analyzes Zeek conn.log connection intervals using statistical methods to detect C2 beaconing patterns, flagging periodic connections with low jitter.