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 iBrain-BVBA/gutt-claude-code-plugin --skill onboardgit clone --depth 1 https://github.com/iBrain-BVBA/gutt-claude-code-pluginWrote 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/ibrain-bvba/gutt-claude-code-plugin/onboard)<a href="https://agentmods.dev/skills/ibrain-bvba/gutt-claude-code-plugin/onboard"><img src="https://agentmods.dev/badge/skills/ibrain-bvba/gutt-claude-code-plugin/onboard/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/ibrain-bvba/gutt-claude-code-plugin/onboard"><img src="https://agentmods.dev/badge/skills/ibrain-bvba/gutt-claude-code-plugin/onboard.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 | $0.00048 | $0.01467 |
| Opus 5.5 | $0.00019 | $0.00587 |
| Sonnet 5.5 | $0.00010 | $0.00293 |
| Haiku 4.5 | $0.00005 | $0.00147 |
Grade B, and why
onboard scanned grade B with 1 finding 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
cat .claude/settings.json 2>/dev/null | grep -q "gutt" How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Onboard Skill
Announce: "Starting gutt memory onboarding..."
Walk the user through first-use setup and verification of the gutt memory integration.
Flow
Step 1: Detect MCP
Check if the gutt MCP server is configured in the project's settings.
# Check for gutt MCP configuration in settings
cat .claude/settings.json 2>/dev/null | grep -q "gutt"
- If configured: Announce "gutt MCP server found in settings." and proceed to Step 2.
- If NOT configured: Ask the user for their MCP server URL and guide them through setup:
- Ask: "What is your gutt MCP server URL? (e.g., https://your-instance.gutt.io/mcp)"
- Explain they can also run
/gutt-pro:setupto configure it. - Once URL is provided, help add it to
.claude/settings.json.
Step 2: Verify Connectivity
Run a test query to confirm the MCP connection is live:
search_memory_nodes(query="test connectivity", max_nodes=1)
| Result | Action |
|---|---|
| Success (any response) | "MCP connection verified." Proceed to Step 3. |
| Not configured error | "MCP server not configured. Run /gutt-pro:setup first." Stop. |
| Unreachable / timeout | "MCP server unreachable. Check your network and server URL." Stop. |
| Auth failure | "Authentication failed. Check your API key or token." Stop. |
Step 3: First Search
Demonstrate memory retrieval by searching the knowledge graph:
search_memory_nodes(query="recent decisions or lessons", max_nodes=5)
Show results formatted as:
## Your Memory Graph
Found [N] entries:
| Entity | Type | Summary |
| ------ | ------ | --------------- |
| [name] | [type] | [brief summary] |
Explain: "The gutt memory graph stores organizational knowledge -- lessons learned, decisions made, patterns discovered, and relationships between them. Every search, capture, and agent delegation flows through this graph."
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 · 166 lines · 48 tokens per session scan B 67485ed27a7d
onboard is a skill published in the GitHub repository iBrain-BVBA/gutt-claude-code-plugin (5 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 1,467 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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