Competition Template Render Path

CommunityPopular

zhaoxuya520

competition-template-render-path

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for SSR, template rendering, route loaders, hydration payloads, server-client render boundaries, and template-to-handler enforcement gaps. Use when the user asks to inspect SSR or template routes, trace render context or hydration data, compare template gating with handler enforcement, explain preview or hidden-route rendering, or connect render pipeline behavior to the decisive branch. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

Overview

Publisher	zhaoxuya520
Repository	`reverse-skill`
Skill name	`competition-template-render-path`
Stars	36.3K
Forks	5K
Bundled files	2
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by zhaoxuya520 on GitHub. Read the source before you install it.

Installation

Install the Competition Template Render Path AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/zhaoxuya520/reverse-skill/tree/main/CTF-Sandbox-Orchestrator/competition-template-render-path

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/zhaoxuya520/reverse-skill.git /tmp/reverse-skill
mkdir -p .claude/skills
cp -r /tmp/reverse-skill/CTF-Sandbox-Orchestrator/competition-template-render-path .claude/skills/competition-template-render-path

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competition Template Render Path in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Competition Template Render Path on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Competition Template Render Path is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Competition Template Render Path

Use this skill only as a downstream specialization after $ctf-sandbox-orchestrator is already active and has established sandbox assumptions, node ownership, and evidence priorities. If that has not happened yet, return to $ctf-sandbox-orchestrator first.

Use this skill when the decisive bug or artifact lives in route resolution, server render context, template data, or hydration handoff rather than in a plain JSON API alone.

Reply in Simplified Chinese unless the user explicitly requests English.

Quick Start

Map the render chain in order: route resolution, loader or data fetch, template or component context, response HTML, hydration payload, and client takeover.
Record host, route params, preview toggles, tenant or host switches, and server-only variables before mutating anything.
Compare template gating with loader or handler enforcement.
Preserve one successful render and one failing render path with the smallest delta.
Reproduce the smallest request-to-render branch that proves the decisive behavior.

Workflow

1. Map Route To Render Context

Record host, path, route match, loader, template, layout, hydration blob, and client boot chunk for the active view.
Note whether the response is SSR HTML, static HTML plus hydration, edge-rendered content, or a template fragment used by another route.
Keep server-only context and client-visible context separate.

2. Trace Template And Enforcement Boundaries

Show where permissions, feature flags, preview state, tenant selection, or host-based switches are applied.
Compare template-level gating, loader-level gating, and backend handler enforcement instead of trusting any one layer.
Record hidden fields, inline data, hydration JSON, meta tags, or alternate partials that expose the decisive branch.

3. Reduce To The Decisive Render Path

Compress the result to the smallest sequence: request -> route match -> loader or template context -> rendered output or hidden data -> resulting effect.
State clearly whether the decisive weakness lives in route selection, template context construction, server-client hydration handoff, or mismatched enforcement between render and handler.
If the task becomes mostly emitted bundle recovery or source map reconstruction, hand off to the tighter bundle skill.

Read This Reference

Load references/template-render-path.md for the render checklist, hydration checklist, and evidence packaging.

What To Preserve

Route names, loader names, templates, layouts, hydration keys, and host or preview switches
One success or failure pair that shows where render-layer behavior diverges
One minimal request-to-render sequence that reaches the decisive branch

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Competition Template Render Path AI skill do?

Why use Competition Template Render Path on TypingMind?

Because you install it once and use it with any model. Competition Template Render Path is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Competition Template Render Path in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhaoxuya520/reverse-skill/tree/main/CTF-Sandbox-Orchestrator/competition-template-render-path. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Competition Template Render Path?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Competition Template Render Path?

As many as you like. As long as a model supports skills, you can use Competition Template Render Path with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Competition Template Render Path AI skill free?

Yes. It is published on GitHub by zhaoxuya520 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Competition Template Render Path

Quick Start

Workflow

1. Map Route To Render Context

2. Trace Template And Enforcement Boundaries

3. Reduce To The Decisive Render Path

Read This Reference

What To Preserve

Bundled files

Frequently asked questions

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