Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add darrylmorley/ollama-plugin-cc/plugin install ollamaWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/darrylmorley/ollama-plugin-cc/ollama-cli-runtime)<a href="https://agentmods.dev/skills/darrylmorley/ollama-plugin-cc/ollama-cli-runtime"><img src="https://agentmods.dev/badge/skills/darrylmorley/ollama-plugin-cc/ollama-cli-runtime.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00019 | $0.00991 |
| Opus 5 | $0.00010 | $0.00495 |
| Sonnet 5 | $0.00004 | $0.00198 |
| Haiku 4.5 | $0.00002 | $0.00099 |
Grade A, and why
ollama-cli-runtime scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ollama Runtime
Use this skill only inside the ollama:ollama-rescue subagent.
Invoking the Companion Script
Primary helper:
node "${CLAUDE_PLUGIN_ROOT}/scripts/ollama-companion.mjs" task "<raw arguments>"
The companion script talks directly to Ollama's HTTP API. There is no broker process and no app-server to start or stop — Ollama itself must be running at OLLAMA_HOST before the companion is invoked.
Environment Variables
| Variable | Purpose | Default |
|---|---|---|
OLLAMA_HOST |
Base URL for the Ollama HTTP API | http://127.0.0.1:11434 |
OLLAMA_PLUGIN_DEFAULT_MODEL |
Default model when --model is not supplied |
none (required to be set or passed explicitly) |
OLLAMA_PLUGIN_JOB_DIR |
Override for background job storage directory | .ollama/companion-jobs/ inside workspace root |
OLLAMA_PLUGIN_LOG_LEVEL |
Verbosity: silent, error, info, debug |
info |
Selecting a Model
Pass --model <name> to override the default:
node "${CLAUDE_PLUGIN_ROOT}/scripts/ollama-companion.mjs" task --model qwen2.5-coder:14b "<task>"
If --model is omitted and OLLAMA_PLUGIN_DEFAULT_MODEL is not set, the companion exits with a non-zero status and a message directing the user to /ollama:setup.
See the ollama-model-prompting skill for model selection guidance.
Execution Rules
- The rescue subagent is a forwarder, not an orchestrator. Its only job is to invoke
taskonce and return that stdout unchanged. - Prefer the helper over hand-rolled
git, direct Ollama API calls, or any other Bash activity. - Do not call
setup,review,adversarial-review,status,result, orcancelfromollama:ollama-rescue. - Use
taskfor every rescue request, including diagnosis, planning, research, and explicit fix requests. - Leave model unset by default. Add
--modelonly when the user explicitly asks for one. - Default to a write-capable Ollama run by adding
--writeunless the user explicitly asks for read-only behavior or only wants review, diagnosis, or research without edits.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 66 lines · 19 tokens per session scan A abe34525918b
ollama-cli-runtime is a skill published in the GitHub repository darrylmorley/ollama-plugin-cc (4 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 19 tokens to every session and 991 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
agent-platform-rag-engine-management
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…
agent-platform-model-registry
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
google-cloud-solution-agentic-analytics-spark-knowledge-catalog
Discovers requirements and generates guidance to design and deploy a governed, secure agentic-analytics solution for data that's distributed across Google Cloud, other cloud providers, or on-premises. Data that's outside Google Cloud (such as data from Databricks, Snowflake, Salesforce, SAP, or Oracle systems) is…
training-check
Interactively monitor training metrics from the current Codex session, periodically checking WandB or fallback logs for NaN, divergence, plateaus, and broken runs.
nemo-automodel-launcher-config
Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.