Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· Developer Tools
Local-First LLM
Routes LLM requests to a local model (Ollama, LM Studio, llamafile) before falling back to cloud APIs. Tracks token savings and cost avoidance in a persisten...
skill openclawclawhub Free
Routes LLM requests to a local model (Ollama, LM Studio, llamafile) before falling back to cloud APIs. Tracks token savings and cost avoidance in a persisten...
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/local-providers.md, references/routing-logic.md, references/token-estimation.md, scripts/check_local.py, scripts/dashboard.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- joelnishanth
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Local-First LLM
Route requests to a local LLM first; fall back to cloud only when necessary. Track every decision to show real token and cost savings.
1. Check if a local LLM is running
python3 skills/local-first-llm/scripts/check_local.py Returns JSON: { "any_available": true, "best": { "provider": "ollama", "models": [...] } }
2. Route a request
python3 skills/local-first-llm/scripts/route_request.py \ --prompt "Summarize this meeting transcript" \ --tokens 800 \ --local-available \ --local-provider ollama Returns: { "decision": "local", "reason": "...", "complexity_score": -1 }
3. Log the outcome
After executing the request, record it: python3 skills/local-first-llm/scripts/track_savings.py log \ --tokens 800 \ --model gpt-4o \ --routed-to local
4. Show the dashboard
python3 skills/local-first-llm/scripts/dashboard.py
Full Routing Workflow
βββββββββββββββββββββββββββββββββββββββββββββββββββββββ β 1. check_local.py β is a local provider running? β β β β 2. route_request.py β local or cloud? β β - sensitivity check (private data β local) β β - complexity score (high score β cloud) β β - availability gate (no local β cloud) β β β β 3. Execute with the chosen provider β β β β 4. track_savings.py log β record the outcome β β β β 5. dashboard.py β show cumulative savings β βββββββββββββββββββββββββββββββββββββββββββββββββββββββ
Routing Rules (Summary)
ConditionRouteNo local provider availableβοΈ CloudPrompt contains sensitive data (password, secret, api key, ssn, etc.)π LocalComplexity score β₯ 3βοΈ CloudComplexity score < 3π Local For full scoring details, see references/routing-logic.md.
Executing with a Local Provider
Once route_request.py returns "decision": "local", send the request:
Ollama
curl http://localhost:11434/api/generate \ -d '{"model": "llama3.2", "prompt": "YOUR_PROMPT", "stream": false}'
LM Studio / llamafile (OpenAI-compatible)
curl http://localhost:1234/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{"model": "local-model", "messages": [{"role": "user", "content": "YOUR_PROMPT"}]}'
Dashboard
The dashboard reads from ~/.openclaw/local-first-llm/savings.json (auto-created). βββββββββββββββββββββββββββββββββββββββββββ β π§ Local-First LLM β Dashboard β βββββββββββββββββββββββββββββββββββββββββββ€ β Local LLM: β ollama (llama3.2...) β βββββββββββββββββββββββββββββββββββββββββββ€ β Total requests: 42 β β Routed locally: 31 (73.8%) β β Routed to cloud: 11 β βββββββββββββββββββββββββββββββββββββββββββ€ β Tokens saved: 84,200 β β Cost saved: $0.4210 β βββββββββββββββββββββββββββββββββββββββββββ Reset savings data: python3 skills/local-first-llm/scripts/track_savings.py reset
Additional References
Routing scoring details: references/routing-logic.md Local provider setup (Ollama, LM Studio, llamafile): references/local-providers.md Token estimation & cloud cost table: references/token-estimation.md
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
4 Docs2 Scripts
- SKILL.md
- references/local-providers.md
- references/routing-logic.md
- references/token-estimation.md
- scripts/check_local.py
- scripts/dashboard.py