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 humanerd-drew/opencode-drewgent --skill gbrain-integration-drewgentgit clone --depth 1 https://github.com/humanerd-drew/opencode-drewgentWrote 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/humanerd-drew/opencode-drewgent/gbrain-integration-drewgent)<a href="https://agentmods.dev/skills/humanerd-drew/opencode-drewgent/gbrain-integration-drewgent"><img src="https://agentmods.dev/badge/skills/humanerd-drew/opencode-drewgent/gbrain-integration-drewgent/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/humanerd-drew/opencode-drewgent/gbrain-integration-drewgent"><img src="https://agentmods.dev/badge/skills/humanerd-drew/opencode-drewgent/gbrain-integration-drewgent.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00046 | $0.01963 |
| Opus 5.5 | $0.00018 | $0.00785 |
| Sonnet 5.5 | $0.00009 | $0.00393 |
| Haiku 4.5 | $0.00005 | $0.00196 |
Grade A, and why
gbrain-integration-{{AGENT_NAME_LOWER}} scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GBrain Integration for {{AGENT_NAME}}
Integrate GBrain (by Garry Tan) as an MCP server into {{AGENT_NAME}}/Hermes for hybrid search over the .{{AGENT_NAME_LOWER}} Obsidian vault.
Prerequisites
- Homebrew
- Ollama running with embedding model (mxbai-embed-large or nomic-embed-text)
- Hermes Agent
Steps
1. Install Bun + GBrain
brew install oven-sh/bun/bun git clone https://github.com/garrytan/gbrain.git ~/gbrain cd ~/gbrain && bun install bun run build:all bun link
2. Initialize PGLite Brain
export PATH="$HOME/.bun/bin:$PATH" gbrain init --pglite --embedding-model openai:mxbai-embed-large --embedding-dimensions 1536
3. Configure Ollama as Embedding Backend
Write to ~/.gbrain/config.json with embedding_disabled: true, provider_base_urls: { openai: "http://localhost:11434/v1" }
Note: embedding_disabled: true because Ollama's OpenAI-compatible endpoint is rejected by OpenAI client key validation. Vector search needs real key.
4. Import Vault
gbrain sources add {{AGENT_NAME_LOWER}} --path ~/.{{AGENT_NAME_LOWER}} --name "{{AGENT_NAME}} Vault" gbrain sources default {{AGENT_NAME_LOWER}} gbrain import ~/.{{AGENT_NAME_LOWER}}/P0-brainstem --source {{AGENT_NAME_LOWER}} --yes --no-embed gbrain extract links --yes
5. Register MCP Server
Add to config.yaml under mcp_servers: gbrain: command: ~/.bun/bin/gbrain args: ["serve"] env: OPENAI_API_KEY: "ollama-local"
Set env via Python to ensure proper YAML dict format:
import yaml
with open('/.{{AGENT_NAME_LOWER}}/config.yaml') as f:
d = yaml.safe_load(f)
d['mcp_servers']['gbrain']['env'] = {'OPENAI_API_KEY': 'ollama-local'}
with open('/.{{AGENT_NAME_LOWER}}/config.yaml', 'w') as f:
yaml.dump(d, f, default_flow_style=False, allow_unicode=True, sort_keys=False)
6. Verify
Verify gbrain is connected via the MCP tools (check gbrain get_stats or gbrain search "test query"). The MCP server is configured in ~/.config/opencode/opencode.jsonc.
gbrain search "test query"
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 190 lines · 46 tokens per session scan A f3b4883e1854
gbrain-integration-{{AGENT_NAME_LOWER}} is a skill published in the GitHub repository humanerd-drew/opencode-drewgent (3 stars, last pushed 3mo ago), licensed MIT. It adds 46 tokens to every session and 1,963 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
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