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 skills/howdeploy/deploychan_mcp/openshell-pi-agentnpx skills add howdeploy/deploychan_mcp --skill openshell-pi-agentgit clone --depth 1 https://github.com/howdeploy/deploychan_mcpWhat 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 | $0.00080 | $0.03943 |
| Opus 5 | $0.00040 | $0.01972 |
| Sonnet 5 | $0.00016 | $0.00789 |
| Haiku 4.5 | $0.00008 | $0.00394 |
Grade C, and why
OpenShell + Pi: build an isolated coding-agent sandbox 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 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.
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 -LsSf https://raw.githubusercontent.com/NVIDIA/OpenShell/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 -LsSf https://raw.githubusercontent.com/NVIDIA/OpenShell/main/install.sh | sh How it starts
The opening of the file, as written. The whole thing — 521 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenShell + Pi
Build a useful Pi coding agent without giving the model ambient access to the host, arbitrary internet egress or real API credentials. Prefer the official Pi community sandbox first; create a custom image only when reproducibility or preinstalled tooling requires it.
This workflow intentionally contains no personal system prompt, private skill, named model vendor or account-specific provider. Select those from the user's own requirements.
Non-negotiable invariants
- Inspect the current machine and installed CLI before changing anything. OpenShell is
fast-moving; use
openshell <command> --helpas the local command contract. - Keep the gateway on loopback with mTLS unless the user explicitly designs a remote gateway topology.
- Use a rootless compute driver when the host supports it. For Podman, require Podman 5.x, cgroups v2, rootless networking and an active user socket.
- Keep
enable_bind_mounts = false. A host bind mount can negate the filesystem boundary. - Keep
policy_validation_failure_mode = "fail_closed". - Put real credentials in OpenShell provider records, never in
--env, images,settings.json,models.json, skills, prompts or project files. - Give the sandbox only explicit read-only/read-write paths and explicit egress.
- Run the agent as a non-root identity and prefer Landlock
hard_requirementon a known compatible Linux host. - Treat
/sandboxas persistent agent state and/tmpas ephemeral. Do not confusesandbox deletewith stop; deletion may remove the managed workspace. - Review every Pi extension before loading it. Extensions execute code with the agent user's sandbox permissions.
- Prove behavior with OS/network evidence. Do not accept “I tested it” from the sandboxed agent without checking the live runtime.
Authorization boundaries
Read-only discovery is safe to perform immediately. Before creating containers, enabling services, replacing policy, attaching credentials, restarting an active agent or changing firewall/network exposure, make sure that action is inside the user's request. Before any delete or workspace replacement, require explicit confirmation and a verified backup.
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 · 521 lines · 80 tokens per session scan C 348c23fd3a46
OpenShell + Pi: build an isolated coding-agent sandbox is a skill published in the GitHub repository howdeploy/deploychan_mcp (11 stars, last pushed 4d ago), licensed MIT. It adds 80 tokens to every session and 3,943 once invoked, about $0.0004 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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