autosearch:experience-capture

Append JSON execution events to per-skill patterns.jsonl files.

40|6|Updated Mar 26, 2026
One-click install
npx skills add https://github.com/0xmariowu/Autosearch --skill autosearch-experience-capture
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: autosearch:experience-capture
Source: https://github.com/0xmariowu/Autosearch/tree/main/autosearch/skills/meta/experience-capture
Command: npx skills add https://github.com/0xmariowu/Autosearch --skill autosearch-experience-capture

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Leaf skills in AutoSearch generate events, and this meta-skill logs a single execution event to the per-skill experience/patterns.jsonl file. This enables downstream compaction into experience.md digest and supports pattern mining across skill runs.

Core Features & Use Cases

  • Append-only per-skill execution event to patterns.jsonl
  • Monthly archival and rotation of patterns.jsonl for long-term analysis
  • Feeds the experience-compact workflow that builds the experience.md digest from raw events

Quick Start

Call capture_event after each leaf-skill execution to append a JSON line to the skill's patterns.jsonl.

Frequently Asked Questions about autosearch:experience-capture

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

FAQPage Schema
How do I log skill execution events to a local file for pattern mining?▼

You can log skill execution events by calling the capture_event function after each run, which appends a JSON line to the skill's patterns.jsonl file. This creates an append-only record for pattern mining.

What is a patterns.jsonl file used for in skill telemetry?▼

A patterns.jsonl file stores append-only JSON execution events for each skill run. It serves as raw telemetry input for downstream compaction into an experience.md digest to support pattern discovery.

Do I need network access or an LLM to capture skill execution logs?▼

Capturing skill execution logs requires no network access or LLMs. The process operates with fast, local writes to append execution events directly to the per-skill patterns.jsonl file.

How do I archive and rotate execution logs for long-term analysis?▼

Execution logs support monthly archival and rotation of the patterns.jsonl file. This manages file growth over time while preserving the raw event data needed for long-term pattern analysis.

How does logged telemetry get compacted into an experience digest?▼

Logged telemetry in patterns.jsonl feeds the experience-compact workflow, which compacts raw events into an experience.md digest. This digest summarizes execution patterns for downstream analytics.