grim-dev-minion

name	grim:dev:minion
description	Minion: manual-only routing note for using built-in subagents first, or direct Codex, Claude, Cursor, Grok, LM Studio, Ollama, and OpenRouter runners when explicitly requested.
disable-model-invocation	true

Minion

Routing Rule

Prefer the current host agent's built-in subagent system first.

Long-Running and Parallel Minions

When this skill is explicitly triggered, ask the user whether they want:

• the host's built-in subagent tool
• a direct CLI Minion
• an LM Studio local Minion
• an Ollama local Minion
• or the OpenRouter helper

Use an external Minion route only when:

• the user asks for a specific CLI/model/harness/agent
• the current host has no useful built-in subagent tool
• a model/provider comparison is the point of the task
• we are trying to get multiple perspectives
• we are doing code review and want other opinions
• or the work needs an outside runner through OpenRouter
• or the work benefits from a local/offline LM Studio or Ollama model

Before launching any outside route, make the route explicit:

• runner
• model
• prompt
• optional: structured output
• whether it may edit files or must stay read-only
• whether this is a new conversation or a resumed one

When running multiple minions in parallel, do not wait for every model before responding. As soon as one useful review/result comes back, report the current finding to the user and say which minions are still running. Fold slower minion results into a follow-up when they finish.

Some high-reasoning models can run silently for a long time. Silence usually means it is still working. Do not interrupt or kill a minion just because it has not printed output yet. If you need to check, poll or check the corresponding chat logs. Poll gently and wait unless the user gives a deadline, asks to stop it, or the command returns a real error.

Direct CLI Routes

Codex CLI:

codex exec -C "$PWD" -s danger-full-access -m "<model>" "<prompt>"

Resume Codex CLI:

codex exec resume --last -m "<model>" "<prompt>"
codex exec resume "<session-id-or-thread-name>" -m "<model>" "<prompt>"

Claude CLI:

claude -p --permission-mode bypassPermissions --model "<model>" "<prompt>"

Claude Opus xhigh route:

claude -p --permission-mode bypassPermissions --model opus --effort xhigh "<prompt>"

Claude model alias notes:

• Use --model opus for the current local Claude Code Opus route.
• Use --effort xhigh when the user asks for xhigh reasoning.
• claude-opus-4.8 was rejected by the local Claude CLI on 2026-06-20. The CLI reported that Claude Opus 4 was retired and suggested using a newer model.
• Run claude --help if a requested alias fails; the help text currently lists aliases such as opus, sonnet, and fable, plus full model names such as claude-fable-5.

Resume Claude CLI:

claude -p --continue --permission-mode bypassPermissions --model "<model>" "<prompt>"
claude -p --resume "<session-id-or-search>" --permission-mode bypassPermissions --model "<model>" "<prompt>"

Claude background agents, when useful:

claude --bg --permission-mode bypassPermissions --model "<model>" "<prompt>"

Cursor

Cursor CLI:

cursor-agent -p --trust --force --sandbox disabled --workspace "$PWD" --model "<model>" "<prompt>"

Fast Cursor route:

cursor-agent -p --trust --force --sandbox disabled --workspace "$PWD" --model composer-2.5-fast "<prompt>"

Cursor model notes:

• composer-2.5-fast
  • good fast default for quick outside passes
  • passed the local Minion smoke test
• Cursor supports many other model IDs
  • run cursor-agent models to list current account options before choosing

Resume Cursor CLI:

cursor-agent -p --trust --force --sandbox disabled --workspace "$PWD" --model "<model>" --continue "<prompt>"
cursor-agent -p --trust --force --sandbox disabled --workspace "$PWD" --model "<model>" --resume "<chat-id>" "<prompt>"

Grok Build

Grok Build CLI:

grok --cwd "$PWD" --always-approve --permission-mode bypassPermissions --model "<model>" --single "<prompt>"

Resume Grok Build CLI:

grok --cwd "$PWD" --always-approve --permission-mode bypassPermissions --model "<model>" --resume --single "<prompt>"
grok --cwd "$PWD" --always-approve --permission-mode bypassPermissions --model "<model>" --resume "<session-id>" --single "<prompt>"

LM Studio Local Route

Use LM Studio when the user explicitly wants a local model, an offline/private outside opinion, or a quick local comparison against hosted routes.

Start LM Studio first:

• open LM Studio
• download or load a chat model
• start the local server
• keep the default native REST API URL unless you intentionally changed it

List chat models visible through the native local server:

python3 skills/dev/minion/scripts/lmstudio_minion.py --list-models

Run a local Minion prompt:

python3 skills/dev/minion/scripts/lmstudio_minion.py --model "<lm-studio-model-id>" "<prompt>"

If exactly one model is loaded in LM Studio, the helper can usually infer it:

python3 skills/dev/minion/scripts/lmstudio_minion.py "<prompt>"

Use the OpenAI-compatible endpoint instead when you specifically need that compatibility path:

python3 skills/dev/minion/scripts/lmstudio_minion.py --api-mode openai --model "<lm-studio-model-id>" "<prompt>"

Resume LM Studio helper:

python3 skills/dev/minion/scripts/lmstudio_minion.py --conversation "<name>" --model "<lm-studio-model-id>" "<prompt>"
python3 skills/dev/minion/scripts/lmstudio_minion.py --conversation "<name>" "<next prompt>"

List saved LM Studio conversations:

python3 skills/dev/minion/scripts/lmstudio_minion.py --list-conversations

Reset a saved LM Studio conversation:

python3 skills/dev/minion/scripts/lmstudio_minion.py --conversation "<name>" --reset-conversation --model "<lm-studio-model-id>" "<prompt>"

LM Studio conversations are saved under:

.agents/minion/lmstudio/<name>.json

LM Studio Notes

The helper uses LM Studio's native v1 REST API by default. Native mode calls:

• GET /api/v1/models
• POST /api/v1/chat

Native saved conversations store LM Studio's response_id and resume with previous_response_id.

Default local base URL:

http://127.0.0.1:1234/api/v1

OpenAI-compatible fallback base URL:

http://127.0.0.1:1234/v1

Optional defaults:

LMSTUDIO_API_MODE=native|openai
LMSTUDIO_BASE_URL
LMSTUDIO_MODEL
LMSTUDIO_API_KEY
LM_API_TOKEN

Native-only useful flags:

--context-length 8000
--no-store

Do not hard-code model recommendations here. Use LM Studio's loaded model list for the active machine, then route by task:

• coding review
• writing critique
• brainstorming
• privacy-sensitive local analysis
• fast local sanity check

Local models can be useful but uneven. For high-risk code review, security-sensitive work, or final product decisions, compare against a stronger hosted route before acting.

Ollama Local Route

Use Ollama when the user explicitly wants a local model through Ollama, or Ollama is the local runtime already installed on the machine.

Check that Ollama is available and see what models are pulled:

ollama list

Run a one-shot local Minion prompt directly through the CLI:

ollama run "<ollama-model>" "<prompt>"

Pull a model first if it is not installed yet:

ollama pull "<ollama-model>"

Ollama Via The Local Helper

Ollama serves an OpenAI-compatible endpoint, so the LM Studio helper works against it with a base URL override. This gives you saved conversations and resume support:

python3 skills/dev/minion/scripts/lmstudio_minion.py --api-mode openai --base-url http://127.0.0.1:11434/v1 --model "<ollama-model>" "<prompt>"

Resume an Ollama conversation:

python3 skills/dev/minion/scripts/lmstudio_minion.py --api-mode openai --base-url http://127.0.0.1:11434/v1 --conversation "<name>" --model "<ollama-model>" "<prompt>"
python3 skills/dev/minion/scripts/lmstudio_minion.py --api-mode openai --conversation "<name>" "<next prompt>"

Ollama Notes

• Default local endpoint: http://127.0.0.1:11434
• OpenAI-compatible base URL: http://127.0.0.1:11434/v1
• The Ollama server usually starts automatically with the desktop app; otherwise run ollama serve.
• Do not hard-code model recommendations here. Use ollama list on the active machine and route by task.
• The same caution as LM Studio applies: for high-risk review or final decisions, compare against a stronger hosted route.

OpenRouter

---

OpenRouter helper:

python3 skills/dev/minion/scripts/openrouter_minion.py --model "<provider/model>" "<prompt>"

---

Media

OpenRouter media helper:

python3 skills/dev/minion/scripts/openrouter_media.py list-images
python3 skills/dev/minion/scripts/openrouter_media.py list-videos

Generate image output:

python3 skills/dev/minion/scripts/openrouter_media.py image \
  --model "openai/gpt-image-2" \
  --prompt "<image prompt>" \
  --aspect-ratio 9:16 \
  --output output/openrouter/image.png

Image-to-image / reference image output:

python3 skills/dev/minion/scripts/openrouter_media.py image \
  --model "google/gemini-3.1-flash-image" \
  --prompt "<image prompt>" \
  --reference path/to/reference.png \
  --output output/openrouter/image.png

Submit and wait for a video job:

python3 skills/dev/minion/scripts/openrouter_media.py video \
  --model "google/veo-3.1-fast" \
  --prompt "<video prompt>" \
  --first-frame path/to/first-frame.png \
  --resolution 1080p \
  --aspect-ratio 9:16 \
  --duration 8 \
  --wait \
  --output output/openrouter/video.mp4

Resume or download a video job later:

python3 skills/dev/minion/scripts/openrouter_media.py video-status "<job-id-or-polling-url>" --wait --output output/openrouter/video.mp4

Thinking-model route with hidden reasoning:

python3 skills/dev/minion/scripts/openrouter_minion.py --model "<provider/model>" --reasoning-effort medium --reasoning-exclude "<prompt>"

Resume OpenRouter helper:

python3 skills/dev/minion/scripts/openrouter_minion.py --conversation "<name>" --model "<provider/model>" "<prompt>"
python3 skills/dev/minion/scripts/openrouter_minion.py --conversation "<name>" "<next prompt>"

If --model is omitted, the helper asks for one interactively when stdin is a terminal.

When using --conversation, the helper saves the conversation under:

.agents/minion/openrouter/<name>.json

List saved OpenRouter conversations:

python3 skills/dev/minion/scripts/openrouter_minion.py --list-conversations

Reset a saved OpenRouter conversation:

python3 skills/dev/minion/scripts/openrouter_minion.py --conversation "<name>" --reset-conversation --model "<provider/model>" "<prompt>"

OpenRouter Notes

The helper requires:

OPENROUTER_API_KEY

Optional defaults:

OPENROUTER_MODEL
OPENROUTER_SITE_URL
OPENROUTER_APP_NAME

For thinking models, prefer --reasoning-exclude unless the task explicitly needs raw reasoning tokens. Some OpenRouter providers can return message.reasoning with no message.content when reasoning is included; the helper now fails with a clear rerun hint instead of printing None. If hidden reasoning consumes the whole output budget, rerun with a larger --max-tokens, lower --reasoning-effort, or both.

Preferred OpenRouter coding models:

• z-ai/glm-5.2
  • first pick for project-level software engineering and long-context agent work
  • OpenRouter reports a 1M-token context window
  • current catalog benchmark notes include strong coding and Design Arena code/category rankings
• moonshotai/kimi-k2.7-code
  • first Kimi pick for coding-focused outside opinions
  • use when you specifically want Moonshot/Kimi behavior
  • current catalog describes it as built for end-to-end programming tasks over long contexts
• deepseek/deepseek-v4-pro
  • third coding contender when you want a DeepSeek outside opinion
  • use for comparison against GLM and Kimi before broadening to Claude/GPT/OpenRouter Fusion

Other useful fallback routes:

• openrouter/fusion
  • use for multi-model deliberation when the question benefits from routing rather than one model

OpenRouter Image And Video Notes

OpenRouter image and video generation use dedicated APIs, not the chat completions helper.

Image generation:

• Discover models with GET /api/v1/images/models.
• Generate with POST /api/v1/images.
• Responses return base64 image bytes under data[].b64_json.
• Common normalized fields include resolution, aspect_ratio, size, quality, output_format, background, output_compression, n, seed, input_references, stream, and provider.options.
• Use the model and endpoint records before assuming a parameter is supported.

Current image model examples from the June 25, 2026 catalog check:

• openai/gpt-image-2
• openai/gpt-image-1-mini
• openai/gpt-image-1
• google/gemini-3.1-flash-image
• google/gemini-3-pro-image
• sourceful/riverflow-v2.5-pro
• x-ai/grok-imagine-image-quality
• recraft/recraft-v4.1-pro-vector

Video generation:

• Discover models with GET /api/v1/videos/models.
• Submit jobs with POST /api/v1/videos.
• Video is asynchronous: submit, poll GET /api/v1/videos/{jobId}, then download from GET /api/v1/videos/{jobId}/content.
• Common normalized fields include duration, resolution, aspect_ratio, size, frame_images, input_references, generate_audio, seed, callback_url, and provider.
• frame_images are first/last exact frames for image-to-video.
• input_references are looser style/content references.
• If both are present, frame_images wins and the request is image-to-video.

Current video model examples from the June 25, 2026 catalog check:

• google/veo-3.1-fast
• google/veo-3.1
• openai/sora-2-pro
• bytedance/seedance-2.0
• alibaba/wan-2.7
• kwaivgi/kling-v3.0-pro
• x-ai/grok-imagine-video
• alibaba/happyhorse-1.1

Use openrouter_media.py list-images and openrouter_media.py list-videos before picking a model because media catalogs, pricing, and supported parameters move quickly.

References

• OpenRouter image generation docs: https://openrouter.ai/docs/guides/overview/multimodal/image-generation
• OpenRouter video generation docs: https://openrouter.ai/docs/guides/overview/multimodal/video-generation
• OpenRouter image input docs: https://openrouter.ai/docs/guides/overview/multimodal/images