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/nvidia/nemo-relay/maintain-packagingnpx skills add NVIDIA/NeMo-Relay --skill maintain-packaginggit clone --depth 1 https://github.com/NVIDIA/NeMo-RelayWrote 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/nvidia/nemo-relay/maintain-packaging)<a href="https://agentmods.dev/skills/nvidia/nemo-relay/maintain-packaging"><img src="https://agentmods.dev/badge/skills/nvidia/nemo-relay/maintain-packaging.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 | $0.00023 | $0.00496 |
| Opus 5 | $0.00012 | $0.00248 |
| Sonnet 5 | $0.00005 | $0.00099 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
maintain-packaging 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 3d 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
Maintain Release And Packaging Surfaces
Companion Guidance
Use karpathy-guidelines alongside this skill for implementation or review
work. Keep changes scoped, surface assumptions, and define focused validation
before editing.
Use this skill when a change affects how NeMo Relay is built, packaged, named, or consumed outside the source tree.
Audit Areas
- Rust
Cargo.tomlpackage names and workspace metadata - Python packaging in
pyproject.toml - Python worker plugin SDK packaging in
python/plugin/pyproject.toml - Go module path in
go/nemo_relay/go.mod - Node workspace metadata in root
package.jsonandpackage-lock.json - Node package metadata in
crates/node/package.json - FFI header and library naming
- CI workflows, install commands, and example commands
justfilebuild, test, clean, version, and package recipes for plugin crates and packages- Release tags, release-note surfaces, and registry-facing version translation
Checklist
- Package names, import paths, and module names are internally consistent
- Generated artifacts still land where downstream consumers expect
- Docs and examples use the current install/import/build commands
- CI references the same package names as local workflows
- Public packaging changes are reflected in release-facing docs
-
nemo-relay-pluginRust and Python packages track the project SemVer policy and Python wheels use valid PEP 440 translation - Release tags still use raw SemVer without a leading
v - Release history and release notes still point to GitHub Releases, not
CHANGELOG.mdor docs pages
References
pyproject.tomlpython/plugin/pyproject.tomlgo/nemo_relay/go.modpackage.jsonpackage-lock.jsoncrates/node/package.jsonRELEASING.md.github/workflows/ci_python.yml.github/workflows/ci.yaml.gitlab-ci.ymlmaintain-dynamic-plugins
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.
- 3d ago First seen · 59 lines · 23 tokens per session scan A c5087240edbe
maintain-packaging is a skill published in the GitHub repository NVIDIA/NeMo-Relay (132 stars, last pushed 4d ago), licensed Apache-2.0. It adds 23 tokens to every session and 496 once invoked, about $0.0001 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
web-app-penetration-testing
Pentest a web app or website end to end — black-box testing of a live URL, staging environment, or local dev server that finds and exploits real vulnerabilities (auth bypass, broken access control, IDOR, injection, XSS, SSRF, business logic) and proves each one with a working proof-of-concept instead of a signature…
azure-mgmt-botservice-dotnet
Azure Resource Manager SDK for Bot Service in .NET. Management plane operations for creating and managing Azure Bot resources, channels (Teams, DirectLine, Slack), and connection settings. Triggers: "Bot Service", "BotResource", "Azure Bot", "DirectLine channel", "Teams channel", "bot management .NET", "create bot".
babysit
Same-session monitoring loop for PRs, CI runs, tickets, and deployments using the monitorstart / monitorupdate / autonudgestop MCP tools. The loop re-injects your check instructions into THIS session on an idle interval — same context, same tools — and works from dashboard chat, Slack threads, and Discord DMs. Use…
kagent-dev
Development guide for kagent's v1alpha3 Harness and AgentTemplate CRDs, AgentInstance gRPC control plane, upstream A2A integration, Substrate runtime provisioning, tests, generation, and PR workflow. Use for any implementation, debugging, review, or CI task in the kagent repository.
ax-python-agent
Use when writing Python code with axllm for agents, child delegation, tools, MCP, citations, persistent playbook learning, stage instructions, runtime state, final typed responses, and direct-respond executor skipping.
tooluniverse-drug-research
Comprehensive drug profiling — mechanism, primary/secondary targets, drug interactions, clinical-trial status, adverse events (FAERS), pharmacogenomics, and approval history. Use for full drug investigation reports, 'tell me about drug X' queries, and assembling drug profiles for clinicians, researchers, or regulatory…