reverse-engineer

Document unknown artifacts by separating observed facts from inferences with confidence levels.

1|Updated May 9, 2026

Search Tags:#uncertainty #reverse-engineer #artifact-analysis #observation-led #builder-hand-off #no-vision

Ready to run

npx skills add https://github.com/tonykoop/claude-skills --skill reverse-engineer-tonykoop

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: reverse-engineer
Source: https://github.com/tonykoop/claude-skills/tree/main/plugins/maker/skills/reverse-engineer
Command: npx skills add https://github.com/tonykoop/claude-skills --skill reverse-engineer-tonykoop

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill helps analysts turn ambiguous real-world artifacts into structured, uncertainty-aware notes by separating observed facts from inferences and documenting confidence levels, sources, and next steps.

Core Features & Use Cases

Structured observation ledger that catalogs what is seen, what is inferred, and what remains unknown.
Evidence-based reasoning with explicit confidence language and traceable sources, suitable for both in-depth teardown and high-level briefings.
No-vision intake path plus established workflows for handling images, descriptions, or dictated inputs, enabling analysis across platforms.

Quick Start

Describe an unknown artifact by separating observed facts from inferences, and outline the next measurements or tests needed to retire uncertainties.

Frequently Asked Questions about reverse-engineer

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

FAQPage Schema

How do I analyze an unknown artifact when I have limited information?▼

You can analyze an unknown artifact by documenting it through an observation-led process that separates observed facts from inferences. This approach uses a structured ledger to annotate claims as observed, inferred, assumed, or unknown, attaching explicit confidence language to each entry.

What is the best way to document uncertainty during artifact teardown?▼

The best way to document uncertainty is using an uncertainty-preserving ledger that categorizes every claim as observed, measured, inferred, assumed, or unknown. This evidence-based reasoning method attaches explicit confidence language and traceable sources to each documented observation.

How do I structure an observation ledger for reverse-engineering?▼

To structure an observation ledger, catalog what is seen, what is inferred, and what remains unknown. Outline targeted measurement requests and next tests needed to retire uncertainties, providing a clear handoff plan only when sufficient evidence exists to proceed.

When should I request additional data instead of proceeding with artifact analysis?▼

You should request additional data during artifact analysis when insufficient evidence exists to proceed with a handoff plan. The uncertainty-aware approach requires outlining specific measurement requests to retire unknowns before making downstream inferences or establishing next steps.

Can I use dictated inputs for artifact analysis without visual data?▼

Yes, artifact analysis features a no-vision intake path that handles dictated inputs and text descriptions without requiring visual data. This enables structured observation and evidence-based reasoning across platforms when images are unavailable.