Reverse-engineer codebases into evidence-first case studies with file:line citations.
npx skills add https://github.com/ahostbr/liteharness --skill ls-casestudy
Please help me install this Agent Skill. Skill: ls-casestudy Source: https://github.com/ahostbr/liteharness/tree/main/liteharness/catalog/skills/ls-casestudy Command: npx skills add https://github.com/ahostbr/liteharness --skill ls-casestudy
It helps you reverse-engineer an unfamiliar codebase or system into a trustworthy, evidence-backed case study so you can reuse its architecture as a reusable pattern reference.
Ask the AI to generate an evidence-first case study for the repository at a given local directory path or repo URL, including file:line citations for every claim.
High-intent search queries and answers about installing and using this skill.
To generate architecture documentation with file and line citations, you can reverse-engineer a codebase by mapping its structure, scanning API surfaces, and tracing runtime flow to produce an evidence-first markdown case study.
Evidence-first codebase analysis is the process of reverse-engineering a repository into a pattern reference where every claim is backed by a file path and line number. You need it for onboarding when you require traceable documentation instead of opinions.
Yes, you can extract reusable design patterns from a plugin or module by synthesizing structural mapping and API surface scans into design notes, deliberately focusing on architecture adaptation rather than performing a bug hunt.
Codebase reverse-engineering works for analyzing API surfaces and dependency mapping by deploying scouts to collect repository structure, scan exposed APIs, and trace lifecycle flow behavior, synthesizing these into a citation-heavy markdown output.
The best way to document an existing codebase for future pattern extraction is to synthesize structural findings and API behavior into an upfront evidence sources list with strict formatting, ensuring every architectural claim is traceable to specific file lines.
To trace runtime flow behavior and understand an unfamiliar repository architecture, reverse-engineering scouts map the codebase structure and collect lifecycle behavior when available, synthesizing the results into a strictly formatted, citation-heavy architectural case study.
ZTE-AICloudCollect code changes from an SDD branch into evaluation JSON.
nth5693Document solved problems with structured records for reusable solutions.
marcoguillermazScan codebases to identify dependency usage with file paths and line numbers.
mjrtlScore product strategy documents across five PRISM dimensions with evidence validation.
