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OpenClaw

cannon

Cannon package manager for Ethereum deployments. Use when building, testing, deploying, or inspecting Cannon packages. Covers cannonfile syntax, CLI commands (build, run, test, publish, inspect), actions (deploy, invoke, clone, pull, router, diamond), and package workflows. NOT for general Solidity development questions.

dbeal-eth0 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install dbeal-eth/cannon

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

Cannon

⚠️ CRITICAL: Read This First

Some Cannon commands are IRREVERSIBLE and handle real value. Be careful with:

  • cannon build (without --dry-run) — deploys contracts on real networks
  • cannon publish — publishes to on-chain registry (permanent)
  • cannon register — registers package names on-chain
  • cannon publishers — manages package publisher permissions

Safe commands: cannon build --dry-run, cannon inspect, cannon run, cannon test, cannon decode, cannon trace, cannon clean

Rules:

  1. Always use --dry-run first — Simulate before executing on real networks
  2. Make every operation clear to the user — Explain what will happen before running
  3. Confirm before deploying — Never use a real private key without explicit approval
  4. Test locally first — Use chain 13370 (Cannon Network) before target chains
  5. Protect private keys — Use CANNON_PRIVATE_KEY env var or --impersonate (recommended)

Model Recommendation

Use state-of-the-art models for Cannon tasks. Deployment scripts handle real value — don't skimp on model quality. Prefer Claude, GPT-4, or equivalent high-capability models over cheaper alternatives.

Schema Reference

For complete cannonfile syntax validation and autocomplete, refer to the official JSON schemas:

For editor validation, add the schema reference at the top of your cannonfile.toml:

#:schema https://raw.githubusercontent.com/usecannon/cannon/refs/heads/dev/packages/lsp/src/schema.json

name = "my-package"
version = "1.0.0"
...

This enables autocomplete and validation in editors with TOML LSP support (like taplo).


Cannon is a package manager and deployment system for Ethereum smart contracts. It uses declarative can...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/dbeal-eth/cannon
Version
—
Commit
f63cfaceafdda1f7f57b0075d651cb8bbd4dee48
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

README

@usecannon/skill

AI agent skill for Cannon. Enables AI assistants (Claude, GPT-4, etc.) to help with Ethereum deployments using Cannon.

What is this?

This package contains a skill definition that can be used with AI agent frameworks like OpenClaw. The skill provides:

  • Complete Cannon CLI reference
  • Cannonfile syntax documentation
  • Deployment workflows and best practices
  • Debugging and troubleshooting guides
  • GitOps and migration patterns

Usage

OpenClaw

Copy SKILL.md and the references/ folder to your OpenClaw skills directory:

cp -r packages/skill/* ~/.openclaw/workspace/skills/cannon/
Other AI Frameworks

The SKILL.md file is designed to be used as a system prompt or context document for AI assistants. Point your AI framework to this file when working on Cannon-related tasks.

Contents

  • SKILL.md - Main skill definition with safety warnings, CLI reference, and workflows
  • references/cli.md - Detailed CLI command reference
  • references/cannonfile.md - Complete cannonfile specification
  • references/testing.md - Testing patterns with cannon-std
  • references/registry.md - Registry and publishing guide

Safety

⚠️ Blockchain deployments are irreversible. This skill includes prominent safety warnings and requires AI assistants to:

  1. Explain operations before executing
  2. Use dry-run mode first
  3. Confirm before deploying with real keys
  4. Test locally before mainnet

License

MIT

Contenu extrait

SKILL.md
# Cannon

## ⚠️ CRITICAL: Read This First

**Some Cannon commands are IRREVERSIBLE and handle real value.** Be careful with:

- `cannon build` (without `--dry-run`) — deploys contracts on real networks
- `cannon publish` — publishes to on-chain registry (permanent)
- `cannon register` — registers package names on-chain
- `cannon publishers` — manages package publisher permissions

Safe commands: `cannon build --dry-run`, `cannon inspect`, `cannon run`, `cannon test`, `cannon decode`, `cannon trace`, `cannon clean`

Rules:
1. **Always use `--dry-run` first** — Simulate before executing on real networks
2. **Make every operation clear to the user** — Explain what will happen before running
3. **Confirm before deploying** — Never use a real private key without explicit approval
4. **Test locally first** — Use chain 13370 (Cannon Network) before target chains
5. **Protect private keys** — Use `CANNON_PRIVATE_KEY` env var or `--impersonate` (recommended)

## Model Recommendation

**Use state-of-the-art models for Cannon tasks.** Deployment scripts handle real value — don't skimp on model quality. Prefer Claude, GPT-4, or equivalent high-capability models over cheaper alternatives.

## Schema Reference

For complete cannonfile syntax validation and autocomplete, refer to the official JSON schemas:

- **Full schema:** https://raw.githubusercontent.com/usecannon/cannon/refs/heads/dev/packages/lsp/src/schema.json
- **Fragment schema:** https://raw.githubusercontent.com/usecannon/cannon/refs/heads/dev/packages/lsp/src/schema-fragment.json

For editor validation, add the schema reference at the top of your `cannonfile.toml`:

```toml
#:schema https://raw.githubusercontent.com/usecannon/cannon/refs/heads/dev/packages/lsp/src/schema.json

name = "my-package"
version = "1.0.0"
...
```

This enables autocomplete and validation in editors with TOML LSP support (like taplo).

---

Cannon is a package manager and deployment system for Ethereum smart contracts. It uses declarative can...
README
# @usecannon/skill

AI agent skill for Cannon. Enables AI assistants (Claude, GPT-4, etc.) to help with Ethereum deployments using Cannon.

## What is this?

This package contains a skill definition that can be used with AI agent frameworks like OpenClaw. The skill provides:

- Complete Cannon CLI reference
- Cannonfile syntax documentation
- Deployment workflows and best practices
- Debugging and troubleshooting guides
- GitOps and migration patterns

## Usage

### OpenClaw

Copy `SKILL.md` and the `references/` folder to your OpenClaw skills directory:

```bash
cp -r packages/skill/* ~/.openclaw/workspace/skills/cannon/
```

### Other AI Frameworks

The `SKILL.md` file is designed to be used as a system prompt or context document for AI assistants. Point your AI framework to this file when working on Cannon-related tasks.

## Contents

- `SKILL.md` - Main skill definition with safety warnings, CLI reference, and workflows
- `references/cli.md` - Detailed CLI command reference
- `references/cannonfile.md` - Complete cannonfile specification
- `references/testing.md` - Testing patterns with cannon-std
- `references/registry.md` - Registry and publishing guide

## Safety

⚠️ **Blockchain deployments are irreversible.** This skill includes prominent safety warnings and requires AI assistants to:

1. Explain operations before executing
2. Use dry-run mode first
3. Confirm before deploying with real keys
4. Test locally before mainnet

## License

MIT

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