Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add yoanbernabeu/grepai-skills --skill grepai-ollama-setupgit clone --depth 1 https://github.com/yoanbernabeu/grepai-skillsWrote 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/yoanbernabeu/grepai-skills/grepai-ollama-setup)<a href="https://agentmods.dev/skills/yoanbernabeu/grepai-skills/grepai-ollama-setup"><img src="https://agentmods.dev/badge/skills/yoanbernabeu/grepai-skills/grepai-ollama-setup/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yoanbernabeu/grepai-skills/grepai-ollama-setup"><img src="https://agentmods.dev/badge/skills/yoanbernabeu/grepai-skills/grepai-ollama-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
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 | $0.00033 | $0.01349 |
| Opus 5 | $0.00016 | $0.00674 |
| Sonnet 5 | $0.00007 | $0.00270 |
| Haiku 4.5 | $0.00003 | $0.00135 |
Grade A, and why
grepai-ollama-setup 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 12d 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 — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ollama Setup for GrepAI
This skill covers installing and configuring Ollama as the local embedding provider for GrepAI. Ollama enables 100% private code search where your code never leaves your machine.
When to Use This Skill
- Setting up GrepAI with local, private embeddings
- Installing Ollama for the first time
- Choosing and downloading embedding models
- Troubleshooting Ollama connection issues
Why Ollama?
| Benefit | Description |
|---|---|
| 🔒 Privacy | Code never leaves your machine |
| 💰 Free | No API costs |
| ⚡ Fast | Local processing, no network latency |
| 🔌 Offline | Works without internet |
Installation
macOS (Homebrew)
# Install Ollama
brew install ollama
# Start the Ollama service
ollama serve
macOS (Direct Download)
- Download from ollama.com
- Open the
.dmgand drag to Applications - Launch Ollama from Applications
Linux
# One-line installer
curl -fsSL https://ollama.com/install.sh | sh
# Start the service
ollama serve
Windows
- Download installer from ollama.com
- Run the installer
- Ollama starts automatically as a service
Downloading Embedding Models
GrepAI requires an embedding model to convert code into vectors.
Recommended Model: nomic-embed-text
# Download the recommended model (768 dimensions)
ollama pull nomic-embed-text
Specifications:
- Dimensions: 768
- Size: ~274 MB
- Performance: Excellent for code search
- Language: English-optimized
Alternative Models
# Multilingual support (better for non-English code/comments)
ollama pull nomic-embed-text-v2-moe
# Larger, more accurate
ollama pull bge-m3
# Maximum quality
ollama pull mxbai-embed-large
| Model | Dimensions | Size | Best For |
|---|---|---|---|
nomic-embed-text |
768 | 274 MB | General code search |
nomic-embed-text-v2-moe |
768 | 500 MB | Multilingual codebases |
bge-m3 |
1024 | 1.2 GB | Large codebases |
mxbai-embed-large |
1024 | 670 MB | Maximum accuracy |
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.
- 12d ago First seen · 232 lines · 33 tokens per session scan E d5afd61c4b0e
grepai-ollama-setup is a skill published in the GitHub repository yoanbernabeu/grepai-skills (20 stars, last pushed 7mo ago), licensed MIT. It adds 33 tokens to every session and 1,349 once invoked, about $0.0002 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 2026-08-30.
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