Ollama

ollama-plugin-cc

Use a local Ollama model from Claude Code to review code or delegate tasks.

This plugin lets you run code reviews and background rescue tasks against an Ollama server — local by default, with optional access to hosted frontier models via Ollama Cloud (:cloud suffix). No OpenAI account, no API key plumbing, and your code stays on your hardware unless you explicitly choose a cloud-hosted model.

Quickstart

1. Install Ollama — download the desktop app or follow the CLI instructions at ollama.com.

2. Pull a model:

   ollama pull llama3.1:8b
   

3. Install the plugin (placeholder — update once published to a marketplace):

   /plugin install ollama@darrylmorley/ollama-plugin-cc
   

4. Run setup:

   /ollama:setup
   

   Setup checks that Ollama is installed, running, and has at least one model. It also lets you set a default model and optionally enable the stop-time review gate.

5. Try a review:

   /ollama:review
   

Commands

Command	What it does
/ollama:review	Read-only review of current uncommitted changes or a branch diff
/ollama:adversarial-review	Steerable review that challenges design decisions and tradeoffs
/ollama:rescue	Delegates a task to Ollama; runs an agentic tool-calling loop by default (--emit-patch for one-shot diff)
/ollama:status	Shows running and recent Ollama jobs for the current repo
/ollama:result	Shows the stored output for a finished job
/ollama:cancel	Cancels an active background job
/ollama:setup	Checks Ollama readiness, pulls models, sets defaults, toggles review gate

Model selection

See the ollama-model-prompting skill for full guidance. Short version:

Local models

Empirically battle-tested against a SQL-injection fixture. See docs/MODELS.md for the full results table and reproducer.

Model	Review	Adv. review	Rescue	Best for
gpt-oss:20b	✓ 26s	✓ 24s	✓ 4 iter / 20s	All-rounder, balanced size/quality
gemma4:26b	✓ 69s	✓ 110s	✓ 5 iter / 29s	Rescue when patches reject; reliable structured output
qwen3.5:9b	✓ 79s	✓ 74s	✓ 3 iter / 44s	VRAM-constrained rigs (6.6 GB)
qwen3.6:27b-coding-nvfp4	✗ schema	flaky	✓ 4 iter / 120s	Rescue only — review path unstable on Apple Silicon
batiai/qwen3.6-27b:q6	✗ schema	✗ schema	✓ 1 iter / 300s	Rescue only — review path drifts off schema

Tool-calling (used by agentic rescue) is reliable on Llama 3.1+, Qwen 2.5+/3+, DeepSeek-Coder-V2+, GPT-OSS, Gemma 3+, GLM 4+, Kimi K2+, and Granite 3. Smaller models (3B, 1B), thinking-token models (DeepSeek-R1 distills), and pre-3 Gemma fall back to patch-emit automatically.

Cloud models (Ollama Cloud)

If your hardware can't run a strong local model — or you want frontier-quality output for a tough adversarial review — Ollama Cloud exposes hosted models behind the same API via a :cloud suffix. The plugin treats them identically to local models; nothing in the plugin needs to change.

Model	Review	Adv. review	Rescue	Notes
qwen3-coder-next:cloud	✓ 6s	✓ 6s	✓ 3 iter / 9s	Fastest across the board — 80B FP8
glm-5.1:cloud	✓ 63s	✓ 47s	✓ 6 iter / 29s	Reliable structured output; strong rescue
kimi-k2.6:cloud	flaky	✓ 113s	✓ 3 iter / 13s	1T params; review schema drift, adversarial fine

Cloud models send your diff context to Ollama's hosted endpoint — opt in by passing one explicitly via --model or /ollama:setup --default-model. Everything else stays local.

Override the model on any command with --model <name>.

Configuration

Variable	Description
OLLAMA_HOST	Ollama server URL (default: http://127.0.0.1:11434)
OLLAMA_PLUGIN_DEFAULT_MODEL	Fallback model when --model is not passed and no per-workspace config is set
OLLAMA_PLUGIN_RESCUE_ALLOW_COMMANDS	Comma-separated list of extra commands for agentic rescue's run_command tool; use * to allow all

Per-workspace config (set via /ollama:setup --default-model) is stored in the plugin state directory and takes precedence over OLLAMA_PLUGIN_DEFAULT_MODEL.

Capabilities and limits

• Review and adversarial-review work on any model that produces valid JSON. Structured output uses Ollama's schema-constrained decoding (Ollama >= 0.5) for reliability.
• Rescue runs an agentic tool-calling loop by default: the model can read files, list directories, write files, apply patches, and run allowlisted commands autonomously (hard cap: 20 iterations). Use --emit-patch to force the legacy one-shot diff output instead. Models that do not support tool calling fall back to patch-emit automatically. Override the command allowlist with OLLAMA_PLUGIN_RESCUE_ALLOW_COMMANDS=cmd1,cmd2 (or =* for unrestricted).
• Stop-review gate uses a Stop hook — enable with /ollama:setup --enable-review-gate. It can create long Claude/Ollama loops; only enable when actively monitoring the session.
• Background jobs work for all long-running operations. Use --background and check progress with /ollama:status.
• Node.js 18.18 or later is required to run the companion script.

Orchestrator pipeline (v0.11+)

Beyond per-task dispatch, the plugin now supports a plan → execute → review pipeline that lets Claude delegate multi-step work to a chain of Ollama agents:

/ollama:plan "audit and fix error handling in lib/"     # planner reads the code, emits a structured plan
# Claude reviews. Looks good.
/ollama:execute-plan pln_abc                            # implement → verify → retry loop, autonomous per step
# Claude reviews the cumulative diff.

Three roles, three models (planner/implementer/verifier), Claude only at the gates. Typically 5–10× reduction in Claude tokens for refactors and audit-and-fix work. See docs/ORCHESTRATOR.md.

Documentation

• docs/ORCHESTRATOR.md — orchestrator pipeline user guide
• docs/MODELS.md — empirical model recommendations + battle-test results
• docs/API.md — public vs internal surface for v1.x
• docs/SMOKE-TEST.md — pre-release verification checklist
• docs/PLAN-v1.md — v0.1 → v1.0 roadmap and status
• docs/PLAN-orchestrator.md — orchestrator design rationale
• CHANGELOG.md — release notes

Credits

Ported from openai/codex-plugin-cc, Apache 2.0. See NOTICE for attribution. This project is not affiliated with OpenAI or Anthropic.