frankenstein-code

Find open-source code that already solves part of a goal (new build, refactor or fix), vet it, take only the needed pieces, and stitch them in with provenance recorded.

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Repository: AjeyDS/skills
Last source activity: October 19, 2026 at 10:07
Detected SKILL.md language: English
Stars: 0
Forks: 0

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The review-first prompt is selected by default. You can switch to a direct command or download a local copy.

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Copy this prompt into the AI assistant you're using.

Follow https://skillsmp.com/skill-install/prompt.md to install only the Agent Skill at https://github.com/AjeyDS/skills/tree/main/skills/engineering/frankenstein-code.

A direct command skips the review prompt. Inspect the source before running it.

npx skills add https://github.com/AjeyDS/skills --skill frankenstein-code

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Prefer a local copy? Download the files currently available to SkillsMP.

Review the source files

Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.

SKILL.md

Source instructions · Read-only preview

name	frankenstein-code
description	Find open-source code that already solves part of a goal (new build, refactor or fix), vet it, take only the needed pieces, and stitch them in with provenance recorded.

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external-agent-delegation

Delegate repo work to parallel external coding agents (Codex CLI, Cursor CLI, Gemini or Antigravity CLI, or others) and calibrate how hard to review what they return. Use whenever the user says an external agent can pitch in, hands off a doc/task to one, reports a branch landed from one, asks whether an agent can handle a task, or wants to split a task across several agents. Also use when the main agent calls Codex or Cursor mid-session (codex exec / codex review, the Cursor plugin's cursor-rescue agent or /cursor:* commands, cursor-agent) for exploration, review, a second opinion, diagnosis or a bounded implementation slice ("ask codex", "have cursor review this"); when the user wants to refresh model knowledge or asks what coding model just came out ("refresh the models", "is there a newer Grok"); and to pick a review depth matched to the specific model that did the work instead of a blanket full re-check.

2026-10-19

ai-slop-detector

Audit a codebase for AI-generated quality decay and fix it, using deterministic analyzers first and reading second. Use this whenever the user wants to review, audit, or clean up code that AI agents wrote; complains that a codebase is bloating, sprawling, growing faster than it should, or "keeps getting bigger"; asks about AI slop, code duplication, dead code, over-engineering, or hallucinated/phantom packages (slopsquatting); wants a quality gate on agent output; or asks whether a given model's output can be trusted. Trigger even when the words "slop" or "AI" are absent -- "why is this repo so big", "clean up this codebase", "find dead code", "is this over-engineered", "review what Claude Code did", "the agent keeps duplicating things" all belong here. Also use when calibrating how hard to review a specific model's work, since a frontier model and a small model fail in opposite directions and need opposite checks.

2026-10-19

bootstrap-system-md

Explore a codebase and generate its first SYSTEM.md, a single tool-agnostic living reference any coding agent (Claude Code, Codex, Cursor, Aider, Gemini CLI) reads before working on the repo, or upgrade an existing SYSTEM.md to the current contract. Use when the user asks to "create a SYSTEM.md", "document this codebase for agents", "set up project context", "generate a CLAUDE.md / AGENTS.md", "upgrade my SYSTEM.md", or complains that agents keep re-learning the same things. Any language or size; ceremony scales to the repo. Output: SYSTEM.md, root shims, and a sized hygiene gate script.

2026-10-19

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frankenstein-code

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