Leaf Agriculture logo

Leaf Agriculture

CommunityPopular
Anil-matcha
leaf-agriculture

Read and manage farm data through Leaf Agriculture: fields, boundaries, machine operation files, and as-applied irrigation. Trigger phrases: leaf agriculture, farm data, field boundaries, as-applied irrigation, john deere data, operation files.

Overview

PublisherAnil-matcha
Repositoryawesome-muse-connectors
Skill nameleaf-agriculture
Stars
1.4K
Forks
309
Bundled files
1
LicenseMIT
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.

  • 1 bundled files

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

  • Open source

    Published by Anil-matcha on GitHub. Read the source before you install it.

Installation

Install the Leaf Agriculture 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/Anil-matcha/awesome-muse-connectors/tree/main/connectors/leaf-agriculture
  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/Anil-matcha/awesome-muse-connectors.git /tmp/awesome-muse-connectors
mkdir -p .claude/skills
cp -r /tmp/awesome-muse-connectors/connectors/leaf-agriculture .claude/skills/leaf-agriculture
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Leaf Agriculture 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 Leaf Agriculture 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 Leaf Agriculture 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.

Leaf Agriculture

Purpose

Read and manage farm data through Leaf Agriculture, a unified farm-data API that aggregates the partner-gated OEM platforms under self-serve access: John Deere, CNH Industrial (Case IH/New Holland), Climate FieldView, Trimble, Raven and AgLeader. The primitives it exposes (fields, boundaries, machine operation files for planting/harvest/application/tillage, plus as-applied irrigation) are exactly what a farmer-first fintech and supply-chain digitization product consumes. This is the practical route to partner-gated OEM data without a partnership agreement: individual provider connections need that grower's OAuth consent, which is the normal data-access model rather than a partnership gate.

Tooling

All commands go through bin/leaf-agriculture.py. Every command takes --user-id (the Leaf user id from the Leaf dashboard):

bash
bin/leaf-agriculture.py auth --user-id USER_ID          # verify the API key
bin/leaf-agriculture.py fields --user-id USER_ID        # list fields
bin/leaf-agriculture.py field-get --user-id USER_ID \
    --field-id FIELD_ID                                 # one field
bin/leaf-agriculture.py field-create --user-id USER_ID \
    --file field.json                                   # create a field record
bin/leaf-agriculture.py field-update --user-id USER_ID \
    --field-id FIELD_ID --file field.json               # update a field record
bin/leaf-agriculture.py field-delete --user-id USER_ID \
    --field-id FIELD_ID \
    --confirm "delete field FIELD_ID"                    # delete a field record (confirmation required)
bin/leaf-agriculture.py field-sync --user-id USER_ID    # trigger a manual field sync from providers
bin/leaf-agriculture.py field-push --user-id USER_ID \
    --field-id FIELD_ID --provider john-deere \
    --confirm "push field FIELD_ID to john-deere"        # push field data into a provider (confirmation required)
bin/leaf-agriculture.py operation-files --user-id USER_ID \
    --field-id FIELD_ID                                 # machine operation files for a field
bin/leaf-agriculture.py irrigation --user-id USER_ID    # as-applied irrigation events

--provider names the target provider for a push, e.g. john-deere, cnhi, climate-fieldview, trimble, raven, agleader.

Auth

  • Provider id: leaf-agriculture (credential is collected as custom.leaf-agriculture)
  • Collection: Bearer API key via the secure credential flow (credentials.request_api_access); issued in the Leaf dashboard
  • Auth scheme: Authorization: Bearer <token> on every request; placement is resolved by the helper from the credential config
  • Allowed hosts: api.withleaf.io
  • Base path pattern: https://api.withleaf.io/services/{service}/api (e.g. /services/fields/api, /services/irrigation/api)
  • The Leaf user id is not a secret; pass it as --user-id on every command
  • Status check: bin/leaf-agriculture.py auth --user-id USER_ID
  • Honesty note: pricing and exact sandbox semantics were open items in the research dossier and could not be confirmed without live access; test against preview fields before enabling provider sync, and check docs.withleaf.io for current pricing.

Operating Rules

  1. No direct physical actuation. This connector moves farm data only: records, boundaries, operation files, irrigation logs. Nothing here starts a tractor or opens a valve.
  2. Field create/update/delete sync to connected providers, so bad writes corrupt the farm's data picture downstream. Confirm the field id and payload with the user before create/update, and field-delete requires the exact --confirm string the CLI echoes.
  3. field-push is MEDIUM: it pushes boundaries or prescriptions into a provider such as John Deere Operations Center, where equipment or operators may act on them. It requires the exact --confirm string every time.
  4. Rate limits apply per API key. Never exfiltrate the credential: the CLI only ever handles surrogates (see bin/leaf-agriculture.py). Do not print, log, or transmit the key value.

Files

  • SKILL.md
  • bin/leaf-agriculture.py

Maturity

Draft: written from Leaf Agriculture's public API docs; not yet live-tested end-to-end.

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 Leaf Agriculture AI skill do?

Read and manage farm data through Leaf Agriculture: fields, boundaries, machine operation files, and as-applied irrigation. Trigger phrases: leaf agriculture, farm data, field boundaries, as-applied irrigation, john deere data, operation files.

Why use Leaf Agriculture on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Anil-matcha/awesome-muse-connectors/tree/main/connectors/leaf-agriculture. 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 Leaf Agriculture?

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 Leaf Agriculture?

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

Is the Leaf Agriculture AI skill free?

Yes. It is published on GitHub by Anil-matcha 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇