Canton Network Repos logo

Canton Network Repos

Organization
aiskillstore
canton-network-repos

Use when working with Canton Network participants, DAML smart contracts, Splice applications, or debugging LF version and package ID issues.

Overview

Publisheraiskillstore
Repositorymarketplace
Skill namecanton-network-repos
Stars
427
Forks
45
Bundled files
1
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 aiskillstore on GitHub. Read the source before you install it.

Installation

Install the Canton Network Repos 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.
  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/aiskillstore/marketplace.git /tmp/marketplace
mkdir -p .claude/skills
cp -r /tmp/marketplace/skills/0xbigboss/canton-network-repos .claude/skills/canton-network-repos
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Canton Network Repos 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 Canton Network Repos 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 Canton Network Repos 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.

Canton Network Repositories

Repository Hierarchy

Splice (e.g., 0.5.4)     github.com/digital-asset/decentralized-canton-sync
  └─ depends on
Canton (e.g., 3.4.9)     github.com/digital-asset/canton
  └─ depends on
DAML SDK (e.g., 3.4.9)   github.com/digital-asset/daml

Version Mapping

SpliceCantonDAML SDKProtocolLF DefaultLF Available
0.5.43.4.93.4.9PV342.1*2.2 (verified)
0.5.33.4.83.4.8PV342.1*2.2
0.4.x3.3.x3.3.xPV332.12.1

*Open-source Splice 0.5.4 ships with SDK snapshot 3.3.0-snapshot.20250502 (pre-dates LF 2.2). LF 2.2 was added to the SDK on 2025-10-03. Updating to SDK 3.4.9 enables LF 2.2 builds.

Key Configuration Files

PurposeRepoFile
LF version definitionsdamlsdk/daml-lf/language/.../LanguageVersion.scala
damlc target validationdamlsdk/compiler/damlc/lib/DA/Cli/Options.hs
Canton versioncantonVERSION
Built-in DARscantoncommunity/common/src/main/daml/
Splice LF configspliceproject/CantonDependencies.scala
Package targetssplicedaml/*/daml.yaml
Docker buildssplicecluster/images/*/Dockerfile

Splice LF config (project/CantonDependencies.scala):

scala
val daml_language_versions = Seq("2.1")  // ← LF target; change to "2.2" for upgrade
val daml_compiler_version = sys.env("DAML_COMPILER_VERSION")

Package ID Derivation

Package IDs are cryptographic hashes of: source content + LF version (--target) + SDK/stdlib version + dependency package IDs.

Changing LF version = different package IDs = incompatible packages. Canton validates that upgraded packages use equal or newer LF version; mixing LF versions on the same ledger causes validation failures.

Enterprise vs Community Canton

FeatureEnterpriseCommunity
Transaction processingParallelSequential
DatabasePostgreSQL, OraclePostgreSQL only
HA DomainSupportedEmbedded only
PruningFullLimited

Build Commands

bash
# Community Canton participant
cd canton && sbt "community/app/assembly"
# Output: community/app/target/scala-2.13/canton-community.jar

# Splice applications (requires DAML_COMPILER_VERSION env var)
cd decentralized-canton-sync && sbt compile

Upgrading to LF 2.2 (Verified with SDK 3.4.9)

  1. project/CantonDependencies.scala: val daml_language_versions = Seq("2.2")
  2. nix/daml-compiler-sources.json: { "version": "3.4.9" }
  3. All daml/*/daml.yaml: set sdk-version: 3.4.9 and --target=2.2
  4. Remove -Wno-ledger-time-is-alpha from all daml.yaml files (not in SDK 3.4.9)
  5. Build: daml build -p daml/splice-util && daml build -p daml/splice-amulet

Community-built DARs have identical package IDs to enterprise at the same LF version (verified 2025-12-24).

Troubleshooting

"Unknown Daml-LF version: 2.2": damlc binary doesn't support 2.2. Check daml damlc --help for supported targets; upgrade to SDK 3.4.9.

Package ID mismatch: different --target values between builds. Check: unzip -p package.dar META-INF/MANIFEST.MF | grep Sdk-Version

Upgrade validation failed: swapping enterprise (LF 2.2) with community (LF 2.1) packages. Use DAR injection to maintain LF 2.2 compatibility.

References

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 Canton Network Repos AI skill do?

Use when working with Canton Network participants, DAML smart contracts, Splice applications, or debugging LF version and package ID issues.

Why use Canton Network Repos on TypingMind?

Because you install it once and use it with any model. Canton Network Repos 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 Canton Network Repos in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aiskillstore/marketplace/tree/main/skills/0xbigboss/canton-network-repos. 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 Canton Network Repos?

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 Canton Network Repos?

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

Is the Canton Network Repos AI skill free?

It is published on GitHub by aiskillstore. 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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