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runlog-record

Append skill execution metrics to a structured JSON log file.

52|3|Updated Feb 14, 2026
Search Tags:#automation#metrics#json#skill#tracking#log#omni-metrics
One-click install
npx skills add https://github.com/ZTE-AICloud/Co-OmniSpec --skill runlog-record
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: runlog-record
Source: https://github.com/ZTE-AICloud/Co-OmniSpec/tree/main/skills/runlog-record
Command: npx skills add https://github.com/ZTE-AICloud/Co-OmniSpec --skill runlog-record

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

统一记录 Skill 执行过程中的关键指标，并将结构化日志追加写入 FEATURE_DIR/.runs/metrics/omni-metrics-log.json，以便后续分析和追踪。

Core Features & Use Cases

  • 记录开始时间、结束时间、执行时长、输入、输出、以及执行结果，形成统一的 metrics 结构。
  • 支持跨技能的流程观测，帮助改进 AI 工作流的可靠性与可观测性。
  • Use Case：在自动化任务链中对每个 Skill 的执行过程进行完整日志记录，生成可检索的指标集合。

Quick Start

在 skill 运行结束后调用本技能以将执行数据追加写入 metrics 日志文件。

Frequently Asked Questions about runlog-record

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I log execution metrics for AI workflow automation to a JSON file?▼

Log execution metrics by capturing start_time, end_time, duration, inputs, outputs, and results, then appending this structured data to a JSON file for tracking AI workflow automation.

What is the best way to track skill execution duration and results without overwriting previous logs?▼

Track skill execution duration without overwriting logs by appending new metric entries to an existing structured JSON file, which preserves all historical execution records for analysis.

Does this metrics tracking skill require any specific dependencies or components to run?▼

This metrics tracking skill requires no external dependencies or components to run, allowing you to directly capture and persist execution data into your structured JSON log.

How do I record start and end times for an automated task chain in a structured format?▼

Record start and end times for an automated task chain by invoking a logging mechanism after skill execution completes, which appends structured timing data into a JSON metrics file.

Where are the captured execution metrics stored when tracking AI workflow observability?▼

Captured execution metrics for AI workflow observability are stored by appending data to a specific JSON log file located within the FEATURE_DIR/.runs/metrics/ directory structure.

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