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 AnastasiyaW/codex-claude-code-config --skill remote-compute-opsgit clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-configWrote 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/anastasiyaw/codex-claude-code-config/remote-compute-ops)<a href="https://agentmods.dev/skills/anastasiyaw/codex-claude-code-config/remote-compute-ops"><img src="https://agentmods.dev/badge/skills/anastasiyaw/codex-claude-code-config/remote-compute-ops.svg" alt="Measured on agentmods" 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 | $0.00132 | $0.02590 |
| Opus 5 | $0.00066 | $0.01295 |
| Sonnet 5 | $0.00026 | $0.00518 |
| Haiku 4.5 | $0.00013 | $0.00259 |
Grade A, and why
remote-compute-ops 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 7d 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 — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Remote compute operations
Use this skill as the provider-neutral workflow for remote GPU and server work. The provider is an adapter, not the name of the skill: RunPod, Massed Compute, and an owned/virtual server must all follow the same evidence, transport, lifecycle, and handoff rules.
When auditing this skill or designing a plan offline, do not call a provider, SSH, or bridge at all; state that live mode/identity is unproven. The read-only lookup below applies only when the user explicitly asks to inspect live remote state.
Non-negotiable transport rule
Reuse the already-created bridge or live connection before opening a new one. The purpose is reliable, rate-limit-compliant operation and avoiding unnecessary authentication attempts; never disguise traffic, evade a provider limit, rotate identities, or bypass a ban.
- Inspect the local connection registry/bridge health when one exists. A registry is
a coordination hint, not proof that a tunnel is alive. Resolve the existing
helper through
%USERPROFILE%\\.claude\\scripts\\conn_registry.pyon Windows or$HOME/.claude/scripts/conn_registry.pyon POSIX when that file exists; if it is not discoverable, report “registry unavailable” instead of guessing a path. - In a read-only investigation, do not create or re-register a bridge. If a live route is required, allow at most one explicitly authorized health probe. Record the host alias/route, registry entry age, session owner, local PID/service or control-socket metadata when available, target identity, last probe result, and whether a probe was permitted; never record credentials.
- Use one persistent provider client/session per task phase. Group compatible read-only queries and reuse keep-alive connections; do not create a client or authenticate once per command.
- The bridge probe has the stricter budget: local registry/config inspection is network-free, but SSH/tunnel health is at most one attempt total per target and phase, with no SSH retry after a timeout or connection error. The API-read retry budget in transport-safety.md does not apply to that probe.
- Batch related remote shell checks into one SSH invocation. Use
ControlMaster/ControlPersistonly after the exact route has passed a health check. If multiplexing fails on the platform or bridge, do not retry it blindly: use one batched command over the known working bridge. - Do not fan out API or SSH calls merely to reduce wall-clock time. Parallelism is allowed only when the provider documents it, the connection budget allows it, and the calls cannot duplicate a mutation.
- For
429,503, connection resets, or transport timeouts, stop increasing the request rate. HonorRetry-After, use bounded exponential backoff with jitter, and record the retry budget. See transport-safety.md.
What ships with it
4 files 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.
- 7d ago First seen · 204 lines · 132 tokens per session scan A 67ba007753ea
remote-compute-ops is a skill published in the GitHub repository AnastasiyaW/codex-claude-code-config (149 stars, last pushed yesterday), licensed MIT. It adds 132 tokens to every session and 2,590 once invoked, about $0.0007 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 2026-08-30.
Other skills, from other repositories
ai-content-filter
Professional Ai Content Filter Expert skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
ai-engineer
Professional Ai Engineer skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
ai-product-manager
Professional Ai Product Manager Expert skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
embedding-architect
Professional Embedding Architect skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
eval-harness
Professional Eval Harness Expert skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
feature-engineer
Professional Feature Engineer skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.