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.
git clone --depth 1 https://github.com/jmanhype/claude-code-plugin-marketplaceWrote 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/commands/jmanhype/claude-code-plugin-marketplace/export-monitor)<a href="https://agentmods.dev/commands/jmanhype/claude-code-plugin-marketplace/export-monitor"><img src="https://agentmods.dev/badge/commands/jmanhype/claude-code-plugin-marketplace/export-monitor/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/commands/jmanhype/claude-code-plugin-marketplace/export-monitor"><img src="https://agentmods.dev/badge/commands/jmanhype/claude-code-plugin-marketplace/export-monitor.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 | $0.00000 | $0.00886 |
| Opus 5 | $0.00000 | $0.00443 |
| Sonnet 5 | $0.00000 | $0.00177 |
| Haiku 4.5 | $0.00000 | $0.00089 |
Grade A, and why
export-monitor 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 11d 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Export Monitor Command
Export the optimized monitor as a reusable Claude Skill for integration with other projects.
Usage
/export-monitor --model models/gepa_optimized.json --output monitors/safety-monitor.skill [--include-weights]
Arguments
--model: Path to trained monitor model--output: Output path for Claude Skill--include-weights: Include fine-tuned weights (default: false)
What Is a Claude Skill?
A Claude Skill is a portable, reusable AI workflow that can be:
- Loaded in any Claude Code session
- Shared across projects
- Version controlled
- Composed with other skills
Example
# Export GEPA-optimized monitor
/export-monitor \
--model models/gepa_optimized.json \
--output monitors/safety-monitor-v1.skill
# Export with fine-tuned weights
/export-monitor \
--model models/gepa_finetuned.json \
--output monitors/safety-monitor-v1-ft.skill \
--include-weights
Output
Exporting monitor to Claude Skill...
Model: models/gepa_optimized.json
Output: monitors/safety-monitor-v1.skill
✓ Extracted optimized prompt
✓ Packaged configuration
✓ Generated skill manifest
Skill exported successfully!
Usage:
claude skill load monitors/safety-monitor-v1.skill
/scan-code your_code.py
Using Exported Skills
In Another Project
cd /path/to/another-project
# Load the skill
claude skill load /path/to/monitors/safety-monitor-v1.skill
# Use it
/scan-code src/api_handler.py
Share with Team
# Commit skill to git
git add monitors/safety-monitor-v1.skill
git commit -m "Add trained safety monitor skill"
git push
# Teammate uses it
git pull
claude skill load monitors/safety-monitor-v1.skill
Programmatic Usage
from claude_code.skills import load_skill
# Load skill
monitor_skill = load_skill("monitors/safety-monitor-v1.skill")
# Use it
result = monitor_skill.run(
command="scan-code",
args={"file_path": "code.py"}
)
Skill Contents
The exported skill includes:
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.
- 11d ago First seen · 167 lines · 0 tokens per session scan A 90cbfb8b184e
export-monitor is a command published in the GitHub repository jmanhype/claude-code-plugin-marketplace (27 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 886 tokens. 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.