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kapilvirenahuja
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infer-mvp-recommendation-from-code

Infer shipped MVP scope from scan-index.json evidence into Markdown artifacts.

3|Updated Jan 25, 2026
Search Tags:#scope definition#churn analysis#code evidence#deterministic planning#mvp inference#release signals#product-keeper
One-click install
npx skills add https://github.com/kapilvirenahuja/garura --skill infer-mvp-recommendation-from-code
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: infer-mvp-recommendation-from-code
Source: https://github.com/kapilvirenahuja/garura/tree/main/core/components/skills/infer-mvp-recommendation-from-code
Command: npx skills add https://github.com/kapilvirenahuja/garura --skill infer-mvp-recommendation-from-code

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It reconstructs what your codebase already treats as v1 by inferring primary and deferred capabilities from scan-index.json, so product-keeper can produce an MVP scope proposal grounded in real shipped behavior instead of guesswork.

Core Features & Use Cases

  • MVP reverse-engineering in brownfield codify: infers “what IS the MVP” from release signals, entry points, churn, and README feature enumeration.
  • Evidence-based classification: groups capabilities into primary use cases when churn+entry points/readme support exists, and flags deferred capabilities using thin-code signatures such as empty modules, disabled/commented routes, TODO-heavy files, or v0/experimental path patterns.
  • Guardrailed artifact generation: validates inputs, optionally halts if an authoritative MVP artifact already exists in product LTM, writes the inferred scope to STM, and emits both a decision manifest and a resolution trace for checkpoint review.

Example use case: during /codify, take scan-index.json for a mature repository and produce scope/mvp-recommendation.md that lists shipped MVP primary use cases and clearly separates deferred capabilities that are scaffolded or not truly released.

Quick Start

Ask the product-keeper workflow to run infer-mvp-recommendation-from-code for issue N using scan-index.json, and have it write scope/mvp-recommendation.md under the issue’s STM evidence directory.

Frequently Asked Questions about infer-mvp-recommendation-from-code

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

FAQPage Schema
How do I infer MVP scope from existing codebase evidence?▼

To infer MVP scope from existing codebase evidence, analyze repository scan-index.json files to reverse-engineer primary and deferred capabilities using release signals, entry points, and README feature enumeration, producing an evidence-grounded markdown artifact.

How do I reverse-engineer MVP features for a brownfield system?▼

Reverse-engineer MVP features for a brownfield system by scanning release history, code churn, and entry points to distinguish shipped primary use cases from deferred capabilities marked by empty modules or disabled routes.

Can I use churn analysis to identify deferred capabilities in a mature repository?▼

Yes, you can use churn analysis alongside thin-code signatures like empty modules, commented routes, and TODO-heavy files to classify deferred capabilities that are scaffolded but not truly released in a mature repository.

What is the best way to generate an MVP recommendation from code evidence?▼

The best way to generate an MVP recommendation from code evidence is to apply deterministic planning during codify workflows, validating inputs and emitting a decision manifest with a resolution trace for checkpoint review.

Does MVP inference work if an authoritative MVP artifact already exists in product LTM?▼

MVP inference can optionally halt if an authoritative MVP artifact already exists in product LTM, preventing overwrites and ensuring the new scope recommendation respects existing long-term memory constraints.

How do I classify primary use cases using code evidence during codify?▼

Classify primary use cases during codify by grouping capabilities where churn, entry points, and README enumeration align, while flagging experimental path patterns as deferred to ensure accurate scope definition.

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