ollama-handoff
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Alternatives to ollama-handoff
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- AlicenseBqualityCmaintenanceDelegates heavy, repetitive, and verifiable tasks like PDF extraction, code analysis, and log processing to a local LLM to reduce token consumption for frontier AI models, while keeping decision-making with the main AI.8MIT
- AlicenseAqualityBmaintenanceEvaluates task suitability for local models before cloud API calls, routing to Ollama or similar to reduce costs.157 npmMIT
- AlicenseAqualityCmaintenanceEnables Claude Code to offload routine code generation and text processing tasks to a local Ollama LLM, saving Cloud API tokens and costs with automatic model selection and security features.1163 npm4Apache 2.0
- AlicenseAqualityDmaintenanceOptimizes token costs by intelligently delegating low-complexity tasks to local LLMs via LiteLLM, enabling cost-effective development workflows.31MIT
- AlicenseNot gradedqualityDmaintenanceEnables Claude to delegate coding tasks to local Ollama models, reducing API token usage by up to 98.75% while leveraging local compute resources. Supports code generation, review, refactoring, and file analysis with Claude providing oversight and quality assurance.383 npm25AGPL 3.0
- AlicenseNot gradedqualityAmaintenanceEnables Claude Code to hand off bulk, mechanical, read-heavy tasks to a local model, including agentic loops that can read, write, and run commands sandboxed at zero cloud token cost.MIT
TDQS
Scored across 8 tools
Each task-specific tool (summarize, code_review, draft_commit_message, extract) has a clear purpose, and ask_local vs chat_local cleanly separate one-shot from multi-turn. The main overlap is that ask_local is framed as a catch-all ('simple extractions, formatting'), which could lead an agent to use it instead of the more specialized extract or code_review tools.
Most operational tools follow a verb_object_local pattern (ask_local, chat_local, summarize_local, extract_local), and all names use snake_case. Deviations include code_review_local and server_info, which don't fit the verb-object shape, and list_models/server_info lack the _local suffix.
Eight tools is well-scoped: six local-model task tools plus two discovery/config tools. Each tool has a distinct role with no obvious redundancy or missing foundational piece.
The set covers generic one-shot generation, multi-turn chat, summarization, extraction, code review, commit messages, model listing, and server config—strong coverage for a local handoff server. It lacks more advanced Ollama operations like streaming, model management, or embeddings, but those appear outside the declared handoff purpose.