# App Evolver

Improves an existing application using its code, product contract, authorized work...

- Repository: https://github.com/daymade/claude-code-skills (1509 stars)
- Category: Business
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add daymade/claude-code-skills --skill app-evolver -g -a claude-code -y`
Codex: `npx skills add daymade/claude-code-skills --skill app-evolver -g -a codex -y`
Cursor: `npx skills add daymade/claude-code-skills --skill app-evolver -g -a cursor -y`
Gemini CLI: `npx skills add daymade/claude-code-skills --skill app-evolver -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add daymade/claude-code-skills`

## Description

Improves an existing application using its code, product contract, authorized work history and competitor evidence. Use for 取长补短、取其精华去其糟粕、参考竞品优化应用 or evolving an app from successful and failed work. Carries authorized changes through implementation and user-result verification, including REA and reverse Skill composition; use skill-evolver for Skills.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# App Evolver

Improve the application's actual user result. Extract transferable mechanisms,
resolve their fit with the current product, implement authorized improvements,
and verify them through the application's consuming surface.

Use this as an orchestration Skill. Keep repository engineering, research,
history access and release operations with their existing owners. For a Skill
target use `skill-evolver`; for competitor intelligence alone use
`competitors-analysis`; for a new product specification use the available
requirements workflow. Do not replace those owners with another execution engine.

## 1. Bind the application and unfinished result

Before research or edits, establish:

- Exact application, repository/ref, platform and runtime or deployment identity.
- Original user request, current product contract and active stage; distinguish
  long-term positioning from the work selected now.
- User-visible improvement, falsifiable acceptance evidence, authorized
  deliverables, protected behavior/data and stopping condition.
- Analysis-only versus implementation authorization, and any unresolved
  product choice whose answer changes the outcome.
- Scope of the learning task. For a broad product or competitor learning
  effort, let the bound device and operator roles and the complete intended
  user result, with its impact judgments, constrain the research questions
  before selecting any single technical scenario for study. Keep a task about
  a single feature or a known defect narrow; do not expand it into a
  whole-product report.

Reuse earlier user decisions; ask in the current conversation only for missing
information or a real unresolved choice. Use the host's question tool when
available. State the evidence, alternatives, consequences and recommendation.
Do not delegate a user decision through another agent.

The rest: https://github.com/daymade/claude-code-skills/blob/HEAD/app-evolver/SKILL.md