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Dicklesworthstone
wrangler

Deploy and manage Cloudflare Workers, Pages, R2, D1, KV. Use when working with wrangler, Cloudflare Workers, or edge deployments.

Overview

PublisherDicklesworthstone
Repositoryagent_flywheel_clawdbot_skills_and_integrations
Skill namewrangler
Stars
73
Forks
16
Bundled files
4
Links
  • 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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Dicklesworthstone on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Dicklesworthstone/agent_flywheel_clawdbot_skills_and_integrations/tree/main/skills/wrangler
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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/Dicklesworthstone/agent_flywheel_clawdbot_skills_and_integrations.git /tmp/agent_flywheel_clawdbot_skills_and_integrations
mkdir -p .claude/skills
cp -r /tmp/agent_flywheel_clawdbot_skills_and_integrations/skills/wrangler .claude/skills/wrangler
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wrangler 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 Wrangler 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 Wrangler 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.

Using Wrangler

Version: 4.59.2+ (Jan 2026). Config format: wrangler.jsonc recommended over .toml.

Quick Start

bash
# Create new project
npx create-cloudflare@latest my-worker

# Local dev
wrangler dev

# Deploy
wrangler deploy

# View logs
wrangler tail

THE EXACT PROMPT — Deploy a Worker

Deploy Worker to Cloudflare:
1. Check wrangler.jsonc exists with name, main, compatibility_date
2. wrangler deploy (auto-provisions KV/R2/D1 bindings if IDs missing)
3. wrangler tail to verify

Core Commands

TaskCommand
Local devwrangler dev
Deploywrangler deploy
View logswrangler tail
Add secretwrangler secret put NAME
List secretswrangler secret list
Generate typeswrangler types
Check configwrangler check startup

Config (wrangler.jsonc)

jsonc
{
  "name": "my-worker",
  "main": "src/index.ts",
  "compatibility_date": "2025-01-01",

  // Routes
  "routes": [
    { "pattern": "example.com/*", "zone_name": "example.com" }
  ],

  // Bindings (IDs optional - auto-provisioned on deploy)
  "kv_namespaces": [{ "binding": "KV", "id": "..." }],
  "r2_buckets": [{ "binding": "BUCKET", "bucket_name": "my-bucket" }],
  "d1_databases": [{ "binding": "DB", "database_id": "..." }],

  // Environment variables
  "vars": { "ENV": "production" }
}

Auto-Provisioning (v4.57+)

Add bindings WITHOUT IDs — Wrangler creates resources on deploy:

jsonc
{
  "kv_namespaces": [{ "binding": "CACHE" }],  // No id - auto-created
  "r2_buckets": [{ "binding": "ASSETS" }],    // No bucket_name - auto-created
  "d1_databases": [{ "binding": "DB" }]       // No database_id - auto-created
}

Hidden/Experimental Flags

FlagPurpose
--x-provisionForce auto-provision resources
--x-auto-createAuto-create bindings with new resources
--x-autoconfigAuto-detect framework (Next.js, Remix, etc.)

Environment Variables

VariablePurpose
CLOUDFLARE_API_TOKENAuth for CI/CD
CLOUDFLARE_ACCOUNT_IDOverride account

Decision Tree

What to do?
├─ New project → npx create-cloudflare@latest
├─ Local dev → wrangler dev
├─ Deploy → wrangler deploy
├─ Add secret → wrangler secret put NAME
├─ View logs → wrangler tail
├─ Database ops → wrangler d1 ...
├─ Storage ops → wrangler r2 ... or wrangler kv ...
└─ Scheduled jobs → Add [triggers] to config

Common Patterns

Add a Secret

bash
wrangler secret put API_KEY
# Enter value when prompted (or pipe: echo "value" | wrangler secret put API_KEY)

Multiple Environments

jsonc
{
  "name": "my-worker",
  "env": {
    "staging": {
      "vars": { "ENV": "staging" },
      "routes": [{ "pattern": "staging.example.com/*" }]
    },
    "production": {
      "vars": { "ENV": "production" },
      "routes": [{ "pattern": "example.com/*" }]
    }
  }
}
bash
wrangler deploy --env staging
wrangler deploy --env production

D1 Database

bash
wrangler d1 create my-db
wrangler d1 execute my-db --file schema.sql
wrangler d1 execute my-db --command "SELECT * FROM users"

R2 Storage

bash
wrangler r2 bucket create my-bucket
wrangler r2 object put my-bucket/file.txt --file ./local.txt
wrangler r2 object get my-bucket/file.txt

AGENTS.md Blurb

Copy this to your project's AGENTS.md:

markdown
### Cloudflare Wrangler

Wrangler is installed and authenticated.

R2 bucket: `<BUCKET_NAME>`
Account ID: `<ACCOUNT_ID>`

Common commands:

\`\`\`bash
wrangler r2 object put <BUCKET>/<path> --file ./local-file
wrangler r2 object get <BUCKET>/<path> --file ./downloaded
wrangler r2 bucket list
wrangler d1 execute <DB> --command "SELECT * FROM users"
wrangler deploy
\`\`\`

Reference Index

TopicReference
All commandsCOMMANDS.md
Config optionsCONFIG.md
Pages deploymentPAGES.md

Gotchas

  • Dashboard changes overwritten: Add "keep_vars": true to preserve dashboard edits
  • Secrets not in config: Use wrangler secret put, never put secrets in config
  • Types outdated: Run wrangler types after config changes
  • Old compatibility_date: Update yearly for new features

Sources

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 Wrangler AI skill do?

Deploy and manage Cloudflare Workers, Pages, R2, D1, KV. Use when working with wrangler, Cloudflare Workers, or edge deployments.

Why use Wrangler on TypingMind?

Because you install it once and use it with any model. Wrangler 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 Wrangler in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Dicklesworthstone/agent_flywheel_clawdbot_skills_and_integrations/tree/main/skills/wrangler. 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 Wrangler?

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 Wrangler?

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

Is the Wrangler AI skill free?

It is published on GitHub by Dicklesworthstone. Check the repository for licensing terms. 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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