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 agentmods add commands/vishnu2kmohan/mcp-server-langgraph/deploy-devgit clone --depth 1 https://github.com/vishnu2kmohan/mcp-server-langgraphWhat 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 | $0.00007 | $0.00251 |
| Opus 5 | $0.00003 | $0.00125 |
| Sonnet 5 | $0.00001 | $0.00050 |
| Haiku 4.5 | $0.00001 | $0.00025 |
Grade A, and why
deploy-dev 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 2d 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.
What it actually says
Deploy to Development Environment
Execute the complete development deployment workflow.
Prerequisites Check
- Verify Kubernetes context is set to development cluster
- Check that all environment variables are configured
- Ensure Docker images are built
Deployment Steps
-
Validate Configurations
make validate-deployments -
Deploy to Development
make deploy-dev -
Verify Deployment
- Check pod status
- View logs for any errors
- Run health checks
-
Post-Deployment
make health-check
Troubleshooting
If deployment fails:
- Check pod events:
kubectl get events -n langgraph-agent-dev - View pod logs:
kubectl logs -f deployment/dev-langgraph-agent -n langgraph-agent-dev - Review configuration:
kubectl describe deployment dev-langgraph-agent -n langgraph-agent-dev
Summary
Provide:
- Deployment status (success/failure)
- Pod status and readiness
- Any warnings or errors encountered
- Next steps for testing the deployed application
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.
- 2d ago First seen · 50 lines · 7 tokens per session scan A ae2e2023cd5a
deploy-dev is a command published in the GitHub repository vishnu2kmohan/mcp-server-langgraph (4 stars, last pushed 9d ago), licensed MIT. It adds 7 tokens to every session and 251 once invoked, about $0.0000 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 2026-08-31.
Other commands, from other repositories
add-new-service
Add a new optional service called $ARGUMENTS to the Selfhost AI project.
containers
Apply the CLI runtime and safety contract before executing a command. Runtime --help is authoritative.
deploy-local-image
Apply the CLI runtime and safety contract before executing a command. Runtime --help is authoritative.
hal-voice-toggle
Toggle HAL 9000 voice clips on or off.
helmchart
Scaffold, lint, review, security-audit, test, and upgrade-verify Helm charts. Runs an interactive interview to build production-ready charts from scratch. Covers chart structure, values design, schema validation, kubeconform, helm diff, and multi-environment scaffolding. Use when asked to "create a helm chart", "lint…
chaos
Design, run, and debug Chaos Engineering experiments on Kubernetes using Litmus Chaos v3 and Chaos Mesh v2. Covers fault injection (pod-delete, network-loss, CPU stress, node-drain), steady-state hypothesis probes, GameDay runbooks, scheduled experiments, DORA feedback loop, and RBAC setup. Use when asked to "inject a…