lmstudio-subagents
Reduces token usage from paid providers by offloading work to local LM Studio models.
Skill by carboon
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/carboon-lmstudio-subagents
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About
Use cases: backend
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Node.js package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/lmstudio-subagents
What's inside
- Skill name
lmstudio-subagents- Description
- Reduces token usage from paid providers by offloading work to local LM Studio models. Use when: (1) Cutting costs—use local models for summarization, extraction, classification, rewriting, first-pass review, brainstorming when quality suffices, (2) Avoiding paid API calls for high-volume or repetitive tasks, (3) No extra model configuration—JIT loading and REST API work with existing LM Studio setup, (4) Local-only or privacy-sensitive work. Requires LM Studio 0.4+ with server (default :1234). No CLI required.
- License
- MIT
- Instructions
- 92 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
- Instructions call the network
Agent Skills spec issues
- name: "lmstudio-subagents" does not match folder "lm-studio-subagents"
Files (4)
- origin.json · .clawhub/
- README.md
- SKILL.md
- lmstudio-api.mjs · scripts/
SKILL.md (first lines)
# LM Studio Models
Offload tasks to local models when quality suffices; avoid web/proprietary/high-stakes.
## Key Terms
- **model**: From GET models key; use in chat and optional load.
- **lm_studio_api_url**: Default http://127.0.0.1:1234 (paths /api/v1/...).
- **response_id** / **previous_response_id**: Chat returns response_id; pass as previous_response_id for stateful.
- **instance_id**: loaded_instances[].id or model_instance_id; for unload.
Trigger in frontmatter; below = implementation.
## Prerequisites
LM Studio 0.4+, server :1234, models on disk; load/unload via API (JIT optional); Node for script (curl ok).
## Complete Workflow
### Step 0: Preflight
GET <base>/api/v1/models; non-200 or connection error = server not ready.
```bash
exec command:"curl -s -o /dev/null -w '%{http_code}' -H 'Authorization: Bearer lmstudio' http://127.0.0.1:1234/api/v1/models"
```
### Step 1: List Models and Check Loaded
```bash
exec command:"curl -s -H 'Authorization: Bearer lmstudio' http://127.0.0.1:1234/api/v1/models"
```
Parse models[] (key, type, loaded_instances, max_context_length, capabilities, params_string). If a model has loaded_instances.length > 0 and fits task, skip to Step 5; else pick key for chat (and optional load). Note loaded_instances[].id for optional unload.
### Step 2: Model Selection
Pick key from GET response; use as model in chat (optional load). Constraints: vision -> capabilities.vision; embedding -> type=embedding; context -> max_context_length. Prefer loaded (loaded_instances non-empty), smaller for speed/larger for reasoning; fallback primary. Optional POST load; else JIT on first chat.
### Step 3: Load Model (optional)
Optional: POST /api/v1/models/load { model, context_length?, ... }. JIT: first chat loads; explicit load only for specific options.
### Step 4: Verify Loaded (optional)
If explicit load: GET models, confirm loaded_instances. If JIT: no verify; first chat returns model_instance_id, stats.model_load_time_seconds.
### Step 5: Call API
From the skill folder: node scripts/lmstudio-api.mjs <model> '<task>' [options].
```bash
exec command:"node scripts/lmstudio-api.mjs <model> '<task>' --temperature=0.7 --max-output-tokens=2000"
```
Stateful: add --previous-response-id=<response_id>. Curl: POST <base>/api/v1/chat, body model, input, store, temperature, max_output_tokens; optional previous_response_id. Parse: output (type message) -> content; response_id, model_instance_id, stats. Script outputs content, model_instance_id, response_id, usage.
### Step 6: Unload (optional)
Optional: POST /api/v1/models/unload { instance_id }. instance_id from loaded_instances[].id or chat model_instance_id. JIT+TTL auto-unload; explicit when needed.
```bash
exec command:"curl -s -X POST http://127.0.0.1:1234/api/v1/models/unload -H 'Content-Type: application/json' -H 'Authorization: Bearer lmstudio' -d '{\"instance_id\": \"<instance_id>\"}'"
```
## Error Handling
- Model not found -> pick another model from GET response.
- API/server errors -> GET models, check URL.
- Invalid output -> retry.
- Memory -> unload or smaller model.
- Unload fails -> instance_id must match loaded_instances[].id.
## Examples
GET /api/v1/models, then script with model key and task. Optional unload per Step 6 (instance_id from response or GET).
```bash
exec command:"curl -s -H 'Authorization: Bearer lmstudio' http://127.0.0.1:1234/api/v1/models"
exec command:"node scripts/lmstudio-api.mjs meta-llama-3.1-8b-instruct 'Summarize and extract 5 key points' --temperature=0.7 --max-output-tokens=2000"
```
## LM Studio API Details
Helper/API: see Step 5. Output: content, model_instance_id, response_id, usage. Auth: Bearer lmstudio. List GET /api/v1/models. Load POST /api/v1/models/load (optional). Unload POST /api/v1/models/unload { instance_id }.
## Notes
- LM Studio 0.4+.
- JIT (first chat loads; model_load_time_seconds in stats); stateful (response_id / previous_response_id).From carboon/openclaw-workspace, MIT.
Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Feb 2, 2026 (8 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/carboon/openclaw-workspace
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
lmstudio-subagents skill. Agent Mart. https://agentmart.dev/skills/carboon-lmstudio-subagents (last updated 2026-10-24)