exploration-logger

Document exploratory research spikes and experiments in a structured issue log.

Updated Oct 25, 2025
One-click install
npx skills add https://github.com/SoloXLab/perfetto-dsl --skill exploration-logger
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: exploration-logger
Source: https://github.com/SoloXLab/perfetto-dsl/tree/main/.agents/skills/exploration-logger
Command: npx skills add https://github.com/SoloXLab/perfetto-dsl --skill exploration-logger

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill eliminates the risk of losing track of exploratory work such as research spikes, technical investigations, and idea validation that does not have a formal delivery pull request, ensuring all hypotheses, experiments, and findings are documented in a single traceable log.

Core Features & Use Cases

  • Structured Exploration Logging: Tracks hypotheses, experiment plans, experimental evidence, and final conclusions in a single dedicated issue.
  • Clear Workflow Guardrails: Enforces separation between exploration and production delivery, with explicit handoff steps when moving to implementation.
  • Use Case: Use this skill when evaluating a new database for your project, running performance benchmarks on different caching strategies, or researching third-party API integrations to decide if they meet your requirements.

Quick Start

Use the exploration-logger skill to document your research on whether to adopt GraphQL for the new user profile API, including all test results and final recommendation.

Frequently Asked Questions about exploration-logger

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

FAQPage Schema
How do I document a research spike without creating a production code pull request?

To document a research spike without a production pull request, you can log hypotheses, experiment plans, and evidence in a single dedicated issue, ensuring traceable technical investigation without formal delivery artifacts.

What is the best way to track technical investigation findings and go/no-go decisions?

Tracking technical investigation findings and go/no-go decisions is best achieved by recording experimental evidence and final conclusions in a dedicated exploration log, maintaining auditable records before proceeding to implementation.

How do I structure idea validation logs before committing to implementation?

To structure idea validation logs before implementation, document your hypotheses, run experiments, and record evidence in a single issue, establishing clear workflow guardrails and explicit handoff steps for formal delivery.

When do I need a separate exploration log instead of a standard delivery workflow?

You need a separate exploration log instead of a standard delivery workflow when evaluating new technologies or running performance benchmarks, ensuring untracked exploratory work remains distinct from production code pull requests.

Can I use a structured logging approach for third-party API integration research?

Yes, you can use structured exploration logging for third-party API integration research to document test results, record evidence, and make informed go/no-go decisions without generating production code.

Why should exploration work be separated from production delivery workflows?

Exploration work should be separated from production delivery workflows to eliminate the risk of losing track of untracked technical investigations, enforcing clear guardrails until a formal implementation decision is made.