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-quickstartgit 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-quickstart)<a href="https://agentmods.dev/skills/yoanbernabeu/grepai-skills/grepai-quickstart"><img src="https://agentmods.dev/badge/skills/yoanbernabeu/grepai-skills/grepai-quickstart/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-quickstart"><img src="https://agentmods.dev/badge/skills/yoanbernabeu/grepai-skills/grepai-quickstart.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk fail
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 | $0.00030 | $0.01379 |
| Opus 5 | $0.00015 | $0.00690 |
| Sonnet 5 | $0.00006 | $0.00276 |
| Haiku 4.5 | $0.00003 | $0.00138 |
Grade C, and why
grepai-quickstart scanned grade C with 2 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 10d 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -sSL https://raw.githubusercontent.com/yoanbernabeu/grepai/main/install.sh | sh Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sSL https://raw.githubusercontent.com/yoanbernabeu/grepai/main/install.sh | sh How it starts
The opening of the file, as written. The whole thing — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GrepAI Quickstart
This skill provides a complete walkthrough to get GrepAI running and searching your code in 5 minutes.
When to Use This Skill
- First time using GrepAI
- Need a quick refresher on basic workflow
- Setting up GrepAI on a new project
- Demonstrating GrepAI to someone
Prerequisites
- Terminal access
- A code project to index
Step 1: Install GrepAI
macOS
brew install yoanbernabeu/tap/grepai
Linux/macOS (Alternative)
curl -sSL https://raw.githubusercontent.com/yoanbernabeu/grepai/main/install.sh | sh
Windows
irm https://raw.githubusercontent.com/yoanbernabeu/grepai/main/install.ps1 | iex
Verify: grepai version
Step 2: Install Ollama (Local Embeddings)
macOS
brew install ollama
ollama serve &
ollama pull nomic-embed-text
Linux
curl -fsSL https://ollama.com/install.sh | sh
ollama serve &
ollama pull nomic-embed-text
Verify: curl http://localhost:11434/api/tags
Step 3: Initialize Your Project
Navigate to your project and initialize GrepAI:
cd /path/to/your/project
grepai init
This creates .grepai/config.yaml with default settings:
- Ollama as embedding provider
nomic-embed-textmodel- GOB file storage
- Standard ignore patterns
Step 4: Start Indexing
Start the watch daemon to index your code:
grepai watch
What happens:
- Scans all source files (respects
.gitignore) - Chunks code into ~512 token segments
- Generates embeddings via Ollama
- Stores vectors in
.grepai/index.gob
First indexing output:
🔍 GrepAI Watch
Scanning files...
Found 245 files
Processing chunks...
████████████████████████████████ 100%
Indexed 1,234 chunks
Watching for changes...
Background Mode
For long-running projects:
# Start in background
grepai watch --background
# Check status
grepai watch --status
# Stop when done
grepai watch --stop
Step 5: Search Your Code
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.
- 10d ago First seen · 253 lines · 30 tokens per session scan C 04ef147cc5cf
grepai-quickstart is a skill published in the GitHub repository yoanbernabeu/grepai-skills (20 stars, last pushed 7mo ago), licensed MIT. It adds 30 tokens to every session and 1,379 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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