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Aiwg Refresh

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jmagly
aiwg-refresh

Update AIWG CLI and redeploy frameworks/tools to current project without leaving the session

Overview

Publisherjmagly
Repositoryaiwg
Skill nameaiwg-refresh
Stars
225
Forks
34
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 jmagly on GitHub. Read the source before you install it.

Installation

Install the Aiwg Refresh 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/jmagly/aiwg/tree/main/agentic/code/addons/aiwg-utils/skills/aiwg-refresh
  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/jmagly/aiwg.git /tmp/aiwg
mkdir -p .claude/skills
cp -r /tmp/aiwg/agentic/code/addons/aiwg-utils/skills/aiwg-refresh .claude/skills/aiwg-refresh
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aiwg Refresh 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 Aiwg Refresh 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 Aiwg Refresh 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.

Deterministic execution (#1267): this skill has a script: entrypoint that shells out to aiwg refresh "$@". Prefer aiwg run skill aiwg-refresh -- <flags> when a platform supports it; on platforms without a deployed command stub (e.g. hermes) invoke the CLI directly. The CLI owns the deterministic execution step: version/channel resolution, CLI update, framework redeploy, provider detection, and exit codes. The skill owns the agentic layer around that step: intent alignment, output formatting, workspace-state reconciliation, summary, next actions, gates, and recovery. Do not reimplement the refresh manually or add redundant permission prompts before calling the CLI for execution.

Refresh AIWG Deployment

Update the AIWG CLI and/or redeploy frameworks, agents, commands, and tools to the current project without leaving the agentic session.

Use Cases

  • After AIWG updates: Get latest framework features without restarting
  • After switching branches: Ensure deployed content matches expectations
  • After manual edits: Restore canonical AIWG content
  • Provider switch: Redeploy for different platform (Claude → Factory)
  • Model selection: Redeploy with different AI models for each tier

Parameters

FlagDescription
--update-cliUpdate AIWG CLI to latest version before redeploying
--allRedeploy all installed frameworks
--sdlcRedeploy SDLC framework only
--marketingRedeploy Marketing framework only
--utilsRedeploy aiwg-utils addon only
--provider <name>Target platform: claude, factory, openai, cursor, warp (default: auto-detect)
--reasoning-model <name>Override model for reasoning agents (opus tier)
--coding-model <name>Override model for coding agents (sonnet tier)
--efficiency-model <name>Override model for efficiency agents (haiku tier)
--filter <pattern>Only deploy agents matching glob pattern (e.g., *architect*)
--filter-role <role>Only deploy agents of specified role: reasoning, coding, efficiency
--savePersist model selection to project models.json
--forceForce redeploy even if already up-to-date
--dry-runShow what would be done without executing

Execution Steps

Step 1: Show Current Status

Run status check and report current state:

bash
aiwg -status

Report:

text
AIWG Refresh - Current Status
==============================

CLI Version: 1.2.3 (stable channel)
Workspace: /path/to/project/.aiwg

Installed Frameworks:
  - sdlc-complete v1.0.0 (58 agents, 48 commands)
  - aiwg-utils v1.0.0 (3 agents, 25 commands)

Platform: Claude Code (.claude/)
  - Agents: 61 deployed
  - Commands: 73 deployed

Step 2: Update CLI (if --update-cli)

If --update-cli flag is set:

bash
aiwg -update

Report update status:

text
Checking for updates...
  Current: 1.2.3
  Latest:  1.2.5

Updating AIWG CLI...
✓ Updated to v1.2.5

Changes in v1.2.5:
  - New mutation-analyst agent
  - Testing-quality addon
  - Bug fixes

If already up-to-date:

text
AIWG CLI is up-to-date (v1.2.3)

Step 3: Determine What to Redeploy

Based on flags, determine scope:

FlagsAction
No flagsShow status only, prompt for action
--allRedeploy all installed frameworks
--sdlcRedeploy sdlc-complete only
--marketingRedeploy media-marketing-kit only
--utilsRedeploy aiwg-utils addon only
MultipleRedeploy specified frameworks

If no framework flags and not --dry-run, ask user:

text
What would you like to refresh?

[1] All frameworks (sdlc-complete, aiwg-utils)
[2] SDLC framework only
[3] Utils addon only
[4] Just show status (no changes)

Choice:

Step 4: Detect Target Platform

If --provider not specified, auto-detect:

  1. Check existing deployments:

    • .claude/agents/ exists → claude
    • .factory/droids/ exists → factory
    • .codex/agents/ exists → openai
    • .cursor/rules/ exists → cursor
  2. If multiple detected, ask user:

    text
    Multiple platforms detected:
    [1] Claude Code (.claude/)
    [2] Factory AI (.factory/)
    
    Which platform to refresh?
  3. If none detected, default to claude

Report:

text
Target platform: Claude Code
Deployment paths:
  - Agents: .claude/agents/
  - Commands: .claude/commands/

Step 5: Execute Redeploy

For each framework to deploy:

bash
# SDLC Framework
aiwg use sdlc --provider <platform> --force [model-flags] [filter-flags]

# Marketing Framework
aiwg use marketing --provider <platform> --force [model-flags] [filter-flags]

# Utils (included with sdlc)
# No separate command needed

Model flags (if specified):

  • --reasoning-model <name> - applies to all opus-tier agents
  • --coding-model <name> - applies to all sonnet-tier agents
  • --efficiency-model <name> - applies to all haiku-tier agents

Filter flags (if specified):

  • --filter <pattern> - only deploys matching agents
  • --filter-role <role> - only deploys agents of specified role

If --dry-run: Show commands without executing:

text
Dry Run - Would execute:
========================

1. aiwg use sdlc --provider claude --force --reasoning-model opus-4-2
   → Deploy 58 agents to .claude/agents/ (reasoning tier with opus-4-2)
   → Deploy 48 commands to .claude/commands/

2. aiwg use marketing --provider claude --force --reasoning-model opus-4-2
   → Deploy 37 agents to .claude/agents/ (reasoning tier with opus-4-2)
   → Deploy 20 commands to .claude/commands/

No changes made (dry run mode)

Progress Reporting:

text
Refreshing AIWG Deployment
==========================

[1/2] Deploying sdlc-complete...
  → Copying 58 agents...
  → Copying 48 commands...
  → Copying 12 templates...
  ✓ sdlc-complete deployed

[2/2] Deploying aiwg-utils...
  → Copying 3 agents...
  → Copying 25 commands...
  ✓ aiwg-utils deployed

Step 6: Verify Deployment

After deployment, verify:

bash
# Count deployed assets
ls .claude/agents/*.md 2>/dev/null | wc -l
ls .claude/commands/*.md 2>/dev/null | wc -l

Report:

text
Verification
============

Deployed Assets:
  - Agents: 95 files
  - Commands: 93 files

Platform Files:
  - CLAUDE.md: Present
  - .claude/settings.local.json: Present

All assets deployed successfully!

Step 7: Summary Report

text
AIWG Refresh Complete
=====================

CLI:
  Version: 1.2.5 (updated from 1.2.3)

Frameworks Deployed:
  ✓ sdlc-complete v1.0.0 (58 agents, 48 commands)
  ✓ aiwg-utils v1.0.0 (3 agents, 25 commands)

Platform: Claude Code
  - .claude/agents/: 61 files
  - .claude/commands/: 73 files

New capabilities available:
  - /setup-tdd - TDD enforcement setup
  - /flow-test-strategy-execution - Test execution workflow
  - mutation-analyst agent - Test quality analysis

Session ready - new features are now available!

If the installation update fails but re-deployment completes, do not use the unqualified AIWG Refresh Complete summary above. Report AIWG Refresh Partial Recovery, repeat the update failure, and warn that AIWG may remain on the previous version. When relaying quiet output, preserve the CLI status refreshed-with-update-failure so automation can distinguish this result from a successful package update.

Examples

bash
# Check status only
/aiwg-refresh

# Update CLI and redeploy everything
/aiwg-refresh --update-cli --all

# Just redeploy SDLC framework
/aiwg-refresh --sdlc

# Switch to Factory AI deployment
/aiwg-refresh --all --provider factory

# Preview what would happen
/aiwg-refresh --all --dry-run

# Force refresh even if up-to-date
/aiwg-refresh --all --force

# Redeploy with custom reasoning model
/aiwg-refresh --all --reasoning-model claude-opus-4-2

# Redeploy with custom models for all tiers
/aiwg-refresh --all --reasoning-model opus-4-2 --coding-model sonnet-5 --efficiency-model haiku-4

# Redeploy and save model selection for future deploys
/aiwg-refresh --all --coding-model claude-sonnet-5-0 --save

# Only update architect agents with new reasoning model
/aiwg-refresh --sdlc --filter "*architect*" --reasoning-model opus-4-2

# Only update reasoning-tier agents
/aiwg-refresh --all --filter-role reasoning --reasoning-model custom-reasoning

Natural Language Triggers

This command should activate when user says:

  • "refresh aiwg" / "update aiwg"
  • "redeploy frameworks" / "redeploy agents"
  • "get latest aiwg features"
  • "update my aiwg tools"
  • "sync aiwg deployment"
  • "change agent models" / "switch to opus" / "use different model"
  • "redeploy with custom models"
  • "update reasoning agents" / "update architect agents"

Error Handling

ConditionAction
AIWG CLI not foundError: "AIWG CLI not installed. Run: curl -fsSL ... | bash"
Network or package error on updateWarn, continue re-deployment, and report partial recovery with refreshed-with-update-failure
Framework not installedOffer to install: "SDLC not installed. Install now? [y/N]"
Permission deniedError with specific file/directory that failed
Invalid providerError listing valid providers

Post-Refresh Recommendations

After refresh, suggest:

text
Recommended next steps:
1. Review new features: aiwg -help
2. Check framework docs: /aiwg-kb sdlc
3. Run health check: aiwg doctor

References

  • @$AIWG_ROOT/docs/development/file-placement-guide.md - Correct file placement workflow
  • @$AIWG_ROOT/agentic/code/addons/aiwg-utils/commands/aiwg-regenerate.md - Context file regeneration
  • @$AIWG_ROOT/docs/CLI_USAGE.md - Full CLI documentation

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 Aiwg Refresh AI skill do?

Update AIWG CLI and redeploy frameworks/tools to current project without leaving the session

Why use Aiwg Refresh on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jmagly/aiwg/tree/main/agentic/code/addons/aiwg-utils/skills/aiwg-refresh. 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 Aiwg Refresh?

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 Aiwg Refresh?

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

Is the Aiwg Refresh AI skill free?

Yes. It is published on GitHub by jmagly 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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