daplug

Delegate prompts to Codex, Gemini, Z.AI, Synthetic, or local models from Claude Code — with worktree isolation and Ralph-Wiggum-inspired verification loops.

Installation

From Marketplace (Recommended)

Run these commands in your terminal (not inside Claude Code):

# Add the marketplace (SSH)
claude plugin marketplace add cruzanstx/daplug

# Or via HTTPS
claude plugin marketplace add https://github.com/cruzanstx/daplug

# Install daplug
claude plugin install daplug@cruzanstx

Manual Installation

Clone/copy this plugin to one of:

• ~/.claude/plugins/daplug/ (user scope)
• .claude/plugins/daplug/ (project scope)

OpenCode Compatibility

OpenCode does not load Claude marketplace plugins, so daplug's namespaced commands (for example /daplug:run-prompt) are not available and will fail with Command or skill not found.

To use daplug commands in OpenCode, install bridge commands using the built-in command (from Claude Code):

/install-bridges opencode

Or run the generator script directly:

# Default output: ~/.config/opencode/commands/
python3 scripts/generate-opencode-bridges.py

# Custom output directory (example: project-local)
python3 scripts/generate-opencode-bridges.py .opencode/commands

# Remove stale daplug bridges before regenerating
python3 scripts/generate-opencode-bridges.py --clean

Bridges contain an absolute @ reference to daplug's real commands/*.md specs, so there's no command duplication.

Command name mapping:

• Claude Code: /daplug:run-prompt
• OpenCode: /daplug-run-prompt

What's Included

Commands (21)

Command	Description
/daplug:check-config	Verify daplug configuration status and detect legacy settings
/daplug:cclimits	Check AI CLI usage/quota (Claude, Codex, Gemini, Z.AI, Synthetic)
/daplug:check-updates	Check if plugin has updates available
/daplug:codex-cli	Run task with OpenAI Codex CLI
/daplug:create-at-prompt	Create an agent-team orchestration bundle (orchestrator prompt + sub-prompts)
/daplug:create-llms-txt	Research and generate llms_txt documentation
/daplug:create-prompt	Create optimized, XML-structured prompts
/daplug:devstral-cli	Run task with local Devstral model via Codex CLI
/daplug:detect-clis	Scan and manage available AI coding CLIs
/daplug:gemini-cli	Run task with legacy Google Gemini CLI
/daplug:handoff	Create a compact, evidence-backed session handoff checkpoint outside tracked Git state
/daplug:install-bridges	Install daplug command bridges for other runtimes (e.g. OpenCode)
/daplug:migrate-config	Migrate legacy CLAUDE.md settings to <daplug_config>
/daplug:prompts	Analyze prompts folder and recommend next steps
/daplug:qwen-cli	Run task with local Qwen model via Codex CLI
/daplug:resume-handoff	Validate and load a compact session handoff checkpoint with Git drift detection
/daplug:run-at-prompt	Run existing prompts with agent-team orchestration (phase groups + auto-deps)
/daplug:run-prompt	Execute prompts with various AI models
/daplug:sprint	Automated sprint planning from specs or existing prompts
/daplug:uvc	Update docs and push to version control

Agents (5)

Agent	Description
frontend-build-optimizer	Optimize frontend build times (SvelteKit, Next.js, Vite)
go-build-optimizer	Optimize Go compilation and Docker builds
infra-troubleshooter	Diagnose infrastructure issues
k8s-cicd-troubleshooter	Troubleshoot Kubernetes and CI/CD pipelines
readonly-log-watcher	Monitor prompt execution logs without touching files

Skills (9)

Skill	Description
ai-usage	Check AI CLI usage/quota (Claude, Codex, Gemini, Z.AI, Synthetic)
config-reader	Read and manage daplug config from CLAUDE.md (<daplug_config>)
handoff	Create, validate, and resume compact provider-neutral session handoff checkpoints
prompt-executor	Execute prompts with AI models, worktrees, tmux
prompt-finder	Find and resolve prompts in ./prompts/ directory
prompt-manager	CRUD operations for prompts with subfolder support
sprint	Automated sprint planning, dependency graphs, execution plans
tmux-manager	Manage tmux sessions for background tasks
worktree	Manage git worktrees for isolated development

Hooks

• hooks/hooks.json - PostToolUse hook that nudges Claude to spawn pipeline-deploy-monitor after successful git push
• hooks/scripts/post-push-detect.sh - Detects git push and respects auto_pipeline_monitor: disabled in <daplug_config>

MCP Servers

• servers.json - Placeholder MCP config (disabled by default)

Showcase

Commands below are shown without the /daplug: prefix for readability. In Claude Code, use /daplug:<command> if you prefer namespaced commands.

Create & Execute Prompts

/create-prompt generates XML-structured prompts optimized for each task type, then /run-prompt executes them with your chosen model.

Multi-Model Delegation

Run prompt batches across Claude, Codex, Gemini, Z.AI, or Synthetic with parallel execution and quota-aware routing.

Worktree Isolation

Execute prompts in isolated git worktrees to keep your main branch clean while tasks run.

Verification Loops

Re-run prompts until tests pass with --loop and completion-marker detection.

Quota Awareness

Check usage across all AI CLIs and pick the model with the most headroom.

LLMS.txt Generation

/create-llms-txt scaffolds research prompts in your llms_txt repo and supports cross-repo execution.

Quick Examples

Generate a Feature Prompt

# In Claude Code:
/create-prompt "add user authentication with JWT"

Run Across Multiple Models

/run-prompt 005 --model codex        # OpenAI Codex
/run-prompt 005 --model cc-sonnet    # Claude Code CLI (Sonnet)
/run-prompt 005 --model cc-opus      # Claude Code CLI (Opus)
/run-prompt 005 --model gemini       # Google Gemini (agy preferred, Gemini CLI fallback)
/run-prompt 005 --model opencode     # Z.AI GLM-4.7 (recommended)
/run-prompt 005 --model zai          # Z.AI GLM-4.7 (via Codex)

Local Models (OpenCode Default)

Local models (local, qwen, devstral) now run through OpenCode by default (LMStudio-backed). You can override the CLI wrapper with --cli.

# Defaults to OpenCode + LMStudio
/run-prompt 005 --model local
/run-prompt 005 --model qwen
/run-prompt 005 --model devstral

# Legacy Codex wrapper (if you need it)
/run-prompt 005 --model local --cli codex

Parallel Execution

/run-prompt 001 002 003 --parallel --worktree

Check Quota Before Running

/cclimits
# Shows: Claude: 18% | Codex: 0% | Gemini: 7% | Z.AI: 1%

Recent Changes

v0.23.5 (2026-02-15)

• Claude Code CLI execution: Run prompts headlessly through the local claude CLI
  • New executor --cli override: --cli claude (aliases: claudecode, cc)
  • New model shorthands: cc-sonnet and cc-opus

v0.23.4 (2026-02-15)

• /install-bridges command: Install daplug command bridges for other AI coding runtimes (currently supports OpenCode)
• Test suites: 21 tests for post-push hook, 22 tests for bridge generator
• PostToolUse git push hook (Issue #7): Auto-triggers pipeline-deploy-monitor after git push
• OpenCode bridge generator (Issue #8): scripts/generate-opencode-bridges.py for cross-runtime compatibility

v0.23.0 (2026-02-07)

• OpenCode as default for local models: local, qwen, devstral now route through OpenCode CLI (LMStudio-backed)
• --cli override flag: --cli codex restores legacy behavior, --cli opencode forces OpenCode
• New local models: glm-local (GLM-4.7-Flash), qwen-small (Qwen3-4B haiku-tier)
• Bumped default Codex model to gpt-5.3-codex

v0.20.0 (2026-01-18)

• OpenCode CLI support: New opencode model for Z.AI GLM-4.7 via OpenCode CLI
• Recommended for Z.AI: OpenCode handles GLM-4.7 message format correctly (fixes GitHub Issue #4)
• PTY wrapper: Automatic pseudo-terminal wrapping for CLIs that require it
• New tests: 7 unit tests for model configuration and PTY command wrapping

v0.19.0 (2026-01-18)

• Sprint from existing prompts: New --from-existing flag analyzes prompts already in prompts/ instead of generating from a spec
• Prompt filtering: --prompts 001-005,010, --folder providers/, --exclude 003,007 for precise selection
• Dependency detection: Scans prompt content for depends on, requires, @file references
• Run script generation: Produces executable run-sprint.sh for batch execution

v0.18.0 (2026-01-17)

• Sprint command: New /sprint command for automated sprint planning from technical specifications
• 5-phase workflow: Spec analysis → prompt generation → dependency graph → model assignment → execution plan
• State management: Persistent .sprint-state.json for pause/resume/status tracking
• Sub-commands: status, add, remove, replan, pause, resume, cancel, history

v0.15.0 (2026-01-11)

• Subfolder support: Organize prompts into topic-based subfolders (e.g., prompts/providers/, prompts/backend/)
• New flags: --folder/-f for create, --tree for list, --folder for next-number
• Folder-aware resolution: find 011 searches all folders, find providers/011 targets specific folder
• Range expansion: providers/011-013 expands correctly with folder prefix
• Auto-create folders: Folders created automatically on first prompt
• JSON output: Now includes folder, path, status fields
• Branch naming: Includes folder path to avoid collisions (e.g., prompt/providers/001-name)

v0.14.1 (2026-01-10)

• Fix: Corrected marketplace name in /check-updates command (cruzanstx not daplug)

v0.14.0 (2026-01-10)

• GPT-5.2 model support: Added gpt52, gpt52-high, gpt52-xhigh for planning and research tasks
• Model management utility: New scripts/manage-models.py for listing, checking, and adding models
• Documentation: Added "Managing Models" section to CLAUDE.md with checklist and templates

v0.13.0 (2026-01-05)

• New config format: Settings now stored in <daplug_config> XML blocks in CLAUDE.md files
• Migration command: /daplug:migrate-config automatically converts legacy plaintext settings
• Config detection: /daplug:check-config verifies config status and detects legacy settings
• New skill: config-reader: Python-based config parsing with project → user fallback

v0.12.9 (2026-01-04)

• Central llms_txt prompts: /create-llms-txt now creates prompts in $LLMS_TXT_DIR/prompts/ (the llms_txt repo) instead of the current project's ./prompts/
• Auto-discovery: Reads llms_txt_dir from ~/.claude/CLAUDE.md, offers clone/configure flow if not set
• Cross-repo execution: Uses --prompt-file flag for running prompts from external repos

v0.12.8 (2026-01-03)

• New skill: prompt-manager: Python-based CRUD for prompts (create, list, find, complete, delete)
• Centralized git root detection: All prompt operations now use prompt-manager, fixing zsh parsing issues
• /create-prompt and prompt-finder updated to use prompt-manager

v0.12.7 (2026-01-03)

• Zsh compatibility: Fixed parse error when $() command substitution passed through eval in zsh

v0.12.5 (2026-01-03)

• Prompts always at git root: /create-prompt now saves to {git_root}/prompts/ instead of ./prompts/ (relative to cwd)
• Error handling: /run-prompt now reports errors clearly instead of attempting manual CLI execution
• Models will no longer go off-script when executor fails to find prompts

v0.12.4 (2026-01-01)

• Made monitor spawning mandatory in Step 2 of /run-prompt
• Auto-verify monitor permissions before spawning agents

v0.12.2 (2025-12-31)

• Added readonly-log-watcher agent for lightweight monitoring
• Refactored /create-llms-txt to generate prompts for /run-prompt

Customization

1. Edit .claude-plugin/plugin.json to change name, version, description, author
2. Add more commands in commands/
3. Add agents in agents/
4. Add skills in skills/<skill-name>/SKILL.md
5. Add hooks in hooks/
6. Configure MCP servers in mcp/servers.json

plugin.json Schema

{
  "name": "plugin-name",
  "version": "1.0.0",
  "description": "What the plugin does",
  "author": {
    "name": "Your Name",
    "email": "[email protected]",
    "url": "https://your-site.com"
  },
  "homepage": "https://docs.example.com",
  "repository": "https://github.com/you/plugin",
  "license": "MIT",
  "keywords": ["utility", "helper"]
}

Field	Required	Description
name	Yes	Unique identifier (kebab-case)
version	No	Semantic version (e.g., "1.0.0")
description	No	Brief plugin purpose
author	No	Object with name, email, url
homepage	No	Documentation URL
repository	No	Source code URL
license	No	License identifier
keywords	No	Discovery tags array

Custom paths (optional): commands, agents, skills, hooks, mcpServers, outputStyles, lspServers

INVALID fields (will cause installation to fail): manifest_version, type, permissions, entry

Distribution

Via Marketplace (Recommended)

This repo is configured as a Claude Code marketplace. Run in terminal:

# Add marketplace (SSH)
claude plugin marketplace add cruzanstx/daplug

# Or via HTTPS
claude plugin marketplace add https://github.com/cruzanstx/daplug

# Install the plugin
claude plugin install daplug@cruzanstx

Via Git Clone

git clone cruzanstx/daplug
cp -r daplug ~/.claude/plugins/

Symlink for Development

ln -s $(pwd) ~/.claude/plugins/daplug

Team Auto-Install

Add to your project's .claude/settings.json:

{
  "plugins": {
    "marketplaces": {
      "extraKnown": ["cruzanstx/daplug"]
    }
  },
  "enabledPlugins": ["daplug@cruzanstx"]
}

Or install manually for each team member:

claude plugin marketplace add cruzanstx/daplug
claude plugin install daplug@cruzanstx

Updating

Claude Code doesn't have built-in plugin update notifications yet (feature request #10265). Here are workarounds:

Manual Update

# Uninstall, refresh marketplace, then reinstall
claude plugin uninstall daplug@cruzanstx
claude plugin marketplace update cruzanstx
claude plugin install daplug@cruzanstx

Important: You must uninstall first - claude plugin install won't overwrite an existing cached version.

Option 1: GitLab CI Notification

Add to .gitlab-ci.yml to notify your team when the plugin version changes:

notify-plugin-update:
  stage: notify
  rules:
    - changes:
        - .claude-plugin/plugin.json
  script:
    - |
      VERSION=$(jq -r '.version' .claude-plugin/plugin.json)
      echo "daplug updated to v${VERSION}"
      # Slack notification (uncomment and configure):
      # curl -X POST -H 'Content-type: application/json' \
      #   --data "{\"text\":\"daplug plugin updated to v${VERSION} - run: claude plugin uninstall daplug@cruzanstx && claude plugin marketplace update cruzanstx && claude plugin install daplug@cruzanstx\"}" \
      #   $SLACK_WEBHOOK_URL

      # Email notification (uncomment and configure):
      # echo "daplug v${VERSION} released" | mail -s "Plugin Update" [email protected]

Option 2: Check Command (Included)

This plugin includes /daplug:check-updates which compares your installed version against the marketplace:

/daplug:check-updates

Output:

daplug: v0.3.0 -> v0.3.0
UP_TO_DATE

Or when an update is available:

daplug: v0.2.0 -> v0.3.0
NEEDS_UPDATE

Update available! Run:
  claude plugin uninstall daplug@cruzanstx && claude plugin marketplace update cruzanstx && claude plugin install daplug@cruzanstx

Then resume session:
  claude --resume

Running --resume without an ID shows available sessions to pick from.

Note: The uninstall is required because claude plugin install won't overwrite an existing cached version.

Option 3: Notification Hook (Limited)

Claude Code hooks can't trigger on startup, but you can create a reminder that fires on specific events. Add hooks/update-reminder.json:

{
  "name": "update-reminder",
  "description": "Periodic reminder to check for plugin updates",
  "hooks": [
    {
      "matcher": {
        "type": "event",
        "event": "Notification"
      },
      "hooks": [
        {
          "type": "command",
          "command": "echo 'Tip: Run /daplug:check-updates to check for plugin updates'"
        }
      ]
    }
  ]
}

Note: This approach is limited since there's no "on startup" or "periodic" hook event. It only triggers when Claude sends a notification.

Recommended Setup

For teams, combine:

1. GitLab CI (Option 1) - Automatic team-wide notifications on release
2. Check command (Option 2) - On-demand version checking for individuals

First-Run Setup

On first use, daplug prompts for user settings and saves them to ~/.claude/CLAUDE.md under a <daplug_config> block:

<daplug_config>
preferred_agent: codex
worktree_dir: .worktrees/
llms_txt_dir: /storage/projects/docker/llms_txt
ai_usage_awareness: enabled
cli_logs_dir: ~/.claude/cli-logs/
agy_print_timeout: 60m
agy_inactivity_timeout:
</daplug_config>

Setting	When Prompted	Default
preferred_agent	Running /daplug:prompts	Asks user to choose
worktree_dir	Running /daplug:run-prompt --worktree	../worktrees
llms_txt_dir	Running /daplug:create-llms-txt	../llms_txt
ai_usage_awareness	Running /daplug:create-prompt (when choosing executor)	Asks user (enabled/disabled)
cli_logs_dir	Not prompted (advanced)	~/.claude/cli-logs/
agy_print_timeout	Not prompted (advanced)	60m
agy_inactivity_timeout	Not prompted (advanced)	(disabled)
auto_pipeline_monitor	Not prompted (advanced)	enabled

Settings are checked in order: project ./CLAUDE.md → user ~/.claude/CLAUDE.md

If you still have legacy plaintext settings, run /daplug:migrate-config to upgrade them.

AI Usage Awareness

Daplug integrates with cclimits (npm) to provide real-time quota monitoring across all AI CLI tools.

What is cclimits?

A standalone CLI tool that checks quota/usage for AI coding tools:

• Claude Code - 5-hour and 7-day rolling windows
• OpenAI Codex - Primary and secondary rate limits
• Google Gemini CLI - Per-model quotas (3-Flash, Flash, Pro tiers)
• Z.AI - Token quota percentage
• Synthetic - Request subscription quota via GET https://api.synthetic.new/v2/quotas
• OpenRouter - Account balance

Integration with daplug:

When ai_usage_awareness is enabled, /create-prompt will:

• Run npx cclimits --json before presenting model options
• Show quota percentages for each AI model
• Warn about models near their limits (>70% ⚠️, >90% 🔴)
• Suggest fallback models when preferred agent is unavailable
• Show individual Gemini model quotas

You can also check usage directly:

# Via daplug command
/daplug:cclimits

# Or directly via npx
npx cclimits              # Detailed output
npx cclimits --oneline    # Compact one-liner
npx cclimits --json       # JSON for scripting

Example output:

Claude: 4.0% (5h) ✅ | Codex: 0% (5h) ✅ | Z.AI: 1% ✅ | Synthetic: 12/100 ✅ | Gemini: ( 3-Flash 7% ✅ | Flash 1% ✅ | Pro 10% ✅ )

Status icons:

Icon	Meaning
✅	Under 70% - plenty of capacity
⚠️	70-90% - moderate usage
🔴	90-100% - near limit
❌	100% or unavailable

Toggle setting:

Update ~/.claude/CLAUDE.md under <daplug_config>:

<daplug_config>
ai_usage_awareness: enabled   # or 'disabled'
</daplug_config>

Learn more: cclimits on GitHub | cclimits on npm

Codex CLI Prerequisites

Commands that use Codex CLI (codex-cli, qwen-cli, zai-cli) check for required config on first run:

For qwen-cli (LMStudio):

# ~/.codex/config.toml
[model_providers.lmstudio-remote]
name = "LMStudio"
base_url = "http://YOUR_IP:1234/v1"
env_key = "LMSTUDIO_API_KEY"
wire_api = "chat"

[profiles.local]
model_provider = "lmstudio-remote"
model = "qwen/qwen3-coder-next"

[env]
LMSTUDIO_API_KEY = "lm-studio"

For zai-cli (Z.AI):

# ~/.codex/config.toml
[model_providers.zai]
name = "Z.AI"
base_url = "https://api.z.ai/api/coding/paas/v4"
env_key = "ZAI_KEY"
wire_api = "chat"

[profiles.zai]
model_provider = "zai"
model = "glm-4.7"

[env]
ZAI_KEY = "your-api-key"  # Get from https://z.ai/manage-apikey

If config is missing, the commands will prompt you to set it up.

Known Limitations

Plugin Path References

Commands that reference internal plugin files (like run-prompt.md calling executor.py) should read the install path from Claude's manifest:

# Get exact install path from Claude's tracking
PLUGIN_ROOT=$(jq -r '.plugins."daplug@cruzanstx"[0].installPath' ~/.claude/plugins/installed_plugins.json)
EXECUTOR="$PLUGIN_ROOT/skills/prompt-executor/scripts/executor.py"
python3 "$EXECUTOR" 123 --model codex

Why read from installed_plugins.json?

The cache directory may contain multiple plugin versions (0.1.0, 0.2.0, 0.3.0, etc.) after upgrades. Glob patterns would expand to ALL versions:

# BAD - expands to multiple paths
echo ~/.claude/plugins/cache/.../*/...executor.py
# Result: "/path/0.1.0/.../executor.py /path/0.2.0/.../executor.py ..."

Reading from installed_plugins.json:

• Uses Claude's own tracking of the active install path
• No glob expansion issues
• Single source of truth

Why not use ${CLAUDE_PLUGIN_ROOT}?

Claude Code provides a ${CLAUDE_PLUGIN_ROOT} variable, but there's a known bug (#9354) where it doesn't work in command markdown files.

Where ${CLAUDE_PLUGIN_ROOT} works: Hooks JSON, MCP configs, LSP configs

Where it doesn't work: Command .md files

Prompt Execution

The executor uses stdin for codex models to avoid shell escaping issues with complex prompts:

# Codex: uses stdin with '-' flag
codex exec --full-auto -  # reads from stdin

# Antigravity: uses --print with the prompt as the flag value
agy --model "Gemini 3.8 Flash (High)" --dangerously-skip-permissions --print "prompt content"

# Legacy Gemini CLI fallback: uses -p for headless mode
gemini -y -p "prompt content"

This prevents issues with prompts containing newlines, quotes, backticks, and XML tags.

Sandbox Authentication

When --sandbox is enabled (Linux/bubblewrap), each CLI receives only the minimum host credentials it needs:

• Claude Code: ~/.claude/.credentials.json + ~/.claude.json (read-only bind)
• Antigravity (agy): ~/.gemini/antigravity-cli/antigravity-oauth-token (read-only bind on a tmpfs; conversations and databases stay outside)
• OpenCode/Codex: env-keyed credentials via --setenv; no host credential files bound

Writable tool-state binds are CLI-scoped: opencode_state/opencode_cache/opencode_config are only bound for opencode children. Preflight probes (claude auth status, agy models) verify authentication before real runs and fail fast with an actionable message.

Model Tiers

These tables are generated from scripts/models.json.

Claude

Shorthand	Model	Best For
claude	claude	Complex reasoning in current Claude Code context
cc-sonnet	claude-sonnet-5-5 (Sonnet 5.5)	Claude Code CLI Sonnet 5.5 runs
cc-opus	opus (currently Opus 5.5; floating alias)	Claude Code CLI Opus runs
fable	fable (currently Fable 5.1; floating alias)	Hardest reasoning tasks via Claude Code CLI; currently Fable 5.1 with 1M context and 128K max output
fable51	claude-fable-5-1 (Fable 5.1 pin)	Hardest reasoning tasks pinned to Fable 5.1 (1M context, 128K max output, adaptive thinking, efforts low/medium/high/xhigh/max, $10/MTok in, $50/MTok out)

OpenAI

Shorthand	Model	Best For
codex	gpt-5.6-terra	Fast coding execution (default Codex shorthand)
codex-spark	gpt-5.3-codex-spark	Lowest-latency quick edits
codex-high	gpt-5.6-terra	Complex coding
codex-xhigh	gpt-5.6-terra	Large refactors
sol	gpt-6-sol	Hardest agentic coding tasks
terra	gpt-5.6-terra	Balanced everyday coding (codex default)
luna	gpt-6-luna	Fast, cost-efficient coding
astra	gpt-6-astra	GPT-6 Astra coding
gpt54	gpt-5.4	Explicit GPT-5.4 shorthand
gpt54-high	gpt-5.4	Deep reasoning with GPT-5.4
gpt54-xhigh	gpt-5.4	Maximum reasoning with GPT-5.4
gpt55	gpt-5.5	Explicit GPT-5.5 shorthand
gpt55-high	gpt-5.5	Deep reasoning with GPT-5.5
gpt55-xhigh	gpt-5.5	Maximum reasoning with GPT-5.5
gpt52	gpt-5.2	Planning, research, analysis
gpt52-high	gpt-5.2	Deep reasoning
gpt52-xhigh	gpt-5.2	Maximum reasoning (30+ min)

Google Gemini

Shorthand	Model	Best For
gemini	gemini-3.8-flash	Fast daily driver, high reasoning (default)
gemini-high	gemini-2.5-pro	Stable, more capable
gemini-xhigh	gemini-3-pro-preview	Most capable Gemini fallback
gemini25pro	gemini-2.5-pro	Explicit stable Pro selection
gemini25flash	gemini-2.5-flash	Fast, cost-effective
gemini25lite	gemini-2.5-flash-lite	Fastest Gemini option
gemini3flash	gemini-3-flash-preview	Explicit 3 Flash selection
gemini3pro	gemini-3-pro-preview	Explicit 3 Pro selection
gemini31pro	gemini-3.1-pro-preview	Latest Pro model (if available)
gemini37	gemini-3.8-flash	Latest Flash tier, high reasoning (default 3.7 Flash alias)
gemini37-high	gemini-3.8-flash	Latest Flash tier, high reasoning
gemini37-medium	gemini-3.8-flash	Latest Flash tier, balanced reasoning
gemini37-low	gemini-3.8-flash	Latest Flash tier, fast low-reasoning
argon	gemini-4-argon-high	Argon high reasoning (AGY only)
argon-high	gemini-4-argon-high	Argon high reasoning (AGY only)
argon-medium	gemini-4-argon-medium	Argon medium reasoning (AGY only)
argon-low	gemini-4-argon-low	Argon low reasoning (AGY only)
agy	gemini-3.8-flash	Antigravity default (same as gemini/gemini37)

Z.AI / OpenCode

Shorthand	Model	Best For
zai	glm-4.7	General coding fallback
glm5	glm-5.3	Latest GLM 5.x tasks via OpenCode
glm52	glm-5.2	Explicit GLM-5.2 pin via OpenCode
glm53	glm-5.3	Explicit GLM-5.3 pin via OpenCode
flash	glm-5.3-flash	Fast multimodal GLM-5.3-Flash tasks via OpenCode (1M context, 3x quota, reasoning effort max recommended)
glm53-flash	glm-5.3-flash	Explicit GLM-5.3-Flash pin via OpenCode (multimodal, 1M context, 3x quota, reasoning effort max recommended)
kimi	kimi-k2.5	Kimi K2.5 via OpenCode
opencode	glm-4.7	Recommended OpenCode JSON runner

Synthetic

Synthetic shorthands route through OpenCode's synthetic provider and require SYNTHETIC_API_KEY.

Shorthand	Model	Best For
synthetic	syn:large:text	Synthetic floating alias — currently DeepSeek V4.1 Flash
syn-flash	syn:small:text	Synthetic floating alias — currently GLM-4.7-Flash
syn-kimi	syn:large:vision	Synthetic floating alias — currently Kimi-K3 (prefer syn-kimi3)
syn-kimi3	hf:moonshotai/Kimi-K3	Kimi-K3 flagship, vision, 512k context
syn-qwen	syn:small:vision	Synthetic floating alias — currently Qwen3.8-27B
syn-minimax	hf:MiniMaxAI/MiniMax-M3	MiniMax-M3 vision, cheap all-rounder
syn-nemotron	hf:nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4	Nemotron-3-Super-120B, cheapest large text
syn-glm53	hf:zai-org/GLM-5.3	Beta text-only GLM-5.3, 512k context, 64k max output ($1.40/MTok in, $0.26/MTok cached, $4.40/MTok out)
syn-glm53-flash	hf:zai-org/GLM-5.3-Flash	Beta vision GLM-5.3-Flash, low-cost ($0.15/MTok in, $0.04/MTok cached, $0.50/MTok out)
syn-ds41-flash	hf:deepseek-ai/DeepSeek-V4.1-Flash	DeepSeek V4.1 Flash, vision, 512k context, tools/structured outputs, reasoning efforts none/low/high/xhigh/max
deepseek	hf:deepseek-ai/DeepSeek-V4.1-Flash	Everyday DeepSeek V4.1 Flash alias (vision, 512k context, identical route to syn-ds41-flash)

Local

Shorthand	Model	Best For
local	qwen3.6-35b-a3b	Local qwen-coder model with no quota
qwen	qwen3.6-35b-a3b	Local qwen-coder model with no quota
devstral	devstral-small-2-2512	Local Devstral model with no quota
glm-local	glm-4.7-flash	Local GLM-4.7 Flash model with no quota
qwen-small	qwen3-4b-2507	Small/fast local Qwen model
qwen36	qwen3.6-35b-a3b	Best local coding model, MoE 35B, no quota
qwen36-27b	qwen3.6-27b	Local Qwen 3.6 dense 27B, no quota

When to use GPT-5.2 vs GPT-5.5:

• GPT-5.5: Best when plans are clear, need fast execution (combines codex + reasoning)
• GPT-5.2: Best for ambiguous problems, research, methodical analysis

Worktree Auto-Install

When using --worktree, the executor automatically detects and installs project dependencies after creating the worktree. This ensures verification commands (build, test, lint) work correctly in the isolated environment.

Supported Package Managers

Type	Lock File	Install Command	Search Dirs
npm	package-lock.json	npm ci	., frontend, web, client, app
pnpm	pnpm-lock.yaml	pnpm install --frozen-lockfile	same
yarn	yarn.lock	yarn install --frozen-lockfile	same
Go	go.mod	go mod download	.
pip	requirements.txt	pip install -r requirements.txt	.
poetry	poetry.lock	poetry install	.
uv	uv.lock	uv sync	.

Behavior

• Runs automatically after worktree creation (no flag needed)
• Logs progress to stderr: [Worktree] Detected: frontend/package-lock.json (npm)
• Install failures are logged but don't block prompt execution
• Results included in JSON output under dependencies_installed

Example Output

[Worktree] Installing dependencies...
[Worktree]   Detected: frontend/package-lock.json (npm)
[Worktree]   Running: npm ci
[Worktree]   npm ci completed (23.4s)
[Worktree] Dependencies installed successfully

---

Verification Loop

The --loop flag enables iterative execution where prompts re-run until they report completion. Useful for test/build tasks that may need multiple attempts.

Inspiration

This feature is inspired by the ralph-wiggum plugin from Anthropic's official plugin collection. Ralph-wiggum implements a "self-referential feedback loop" that re-runs Claude until a completion promise is found.

Compare & Contrast:

Aspect	ralph-wiggum	daplug --loop
Mechanism	Stop hooks intercept Claude's exit	Python loop in executor.py
Loop control	Hook script feeds prompt back to Claude	Executor re-runs CLI directly
State file	.claude/ralph-loop.local.md	~/.claude/loop-state/{num}.json
Completion marker	<promise>COMPLETE</promise>	<verification>VERIFICATION_COMPLETE</verification>
Works with	Claude Code only	Any CLI (codex, agy/gemini, zai, etc.)
Runs in	Interactive Claude session	Background process

Why no hooks? Ralph-wiggum's hook approach only works within Claude Code sessions. Our implementation needs to support external CLIs (Codex, Antigravity/Gemini, Z.AI) that don't have Claude's hook system. The Python-based loop runs the CLI, waits for completion, checks logs for markers, and re-runs if needed - all without requiring hooks.

Usage

/daplug:run-prompt 123 --model codex --loop
/daplug:run-prompt 123 --model codex --loop --max-iterations 5

Completion Markers

The executor wraps your prompt with verification protocol instructions. The agent signals completion by outputting:

<!-- Success - task complete -->
<verification>VERIFICATION_COMPLETE</verification>

<!-- Retry needed - explain why -->
<verification>NEEDS_RETRY: Tests failing - 3 auth tests need fixing</verification>

How It Works

1. Your prompt is wrapped with verification instructions
2. Agent runs and outputs a completion marker
3. If VERIFICATION_COMPLETE found → loop ends successfully
4. If NEEDS_RETRY found or no marker → loop continues
5. Retry reasons are passed into the next iteration as feedback
6. Each iteration sees previous work (files, git history)
7. Loop ends at max iterations (default: 3)

Loop State

State is persisted in ~/.claude/loop-state/{prompt-number}.json:

{
  "prompt_number": "123",
  "iteration": 3,
  "max_iterations": 3,
  "status": "running",
  "last_updated_at": "2025-12-29T18:30:00",
  "history": [
    {"iteration": 1, "exit_code": 0, "marker_found": false, "retry_reason": "Tests failing"},
    {"iteration": 2, "exit_code": 1, "marker_found": false, "retry_reason": "Lint errors remain"}
  ],
  "suggested_next_steps": [
    {"text": "Deploy to staging", "original": "1) Deploy to staging", "source_iteration": 1}
  ]
}

Check status: python3 "$EXECUTOR" 123 --loop-status

The executor also extracts "Next steps" / "TODO" suggestions from logs and returns them in the loop result JSON so follow-up prompts can be created automatically.

Writing Verification-Aware Prompts

For best results with --loop:

1. Include explicit verification steps - List what must pass (tests, build, lint)
2. Make verification checkable - Use commands that return clear pass/fail
3. Be specific about "done" - Avoid ambiguous completion criteria

Example prompt structure:

## Requirements
- Add login/logout endpoints
- Password hashing with bcrypt

## Verification Criteria
- [ ] All tests pass: `npm test`
- [ ] Build succeeds: `npm run build`
- [ ] No lint errors: `npm run lint`

When ALL criteria verified, output:
<verification>VERIFICATION_COMPLETE</verification>