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-optimizernpx skills add NVIDIA/NeMo-Relay --skill maintain-optimizergit clone --depth 1 https://github.com/NVIDIA/NeMo-RelayWhat 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 | $0.00031 | $0.00490 |
| Opus 5 | $0.00015 | $0.00245 |
| Sonnet 5 | $0.00006 | $0.00098 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
maintain-optimizer 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.
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Maintain Adaptive 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 changing adaptive config schema, built-in sections, shared plugin lifecycle, plugin registration, or binding-native helper APIs.
Public Boundary
The stable adaptive boundary is the config document plus the shared plugin lifecycle:
- Config types and policies
- Built-in adaptive section helpers
- Plugin registration and composition
- Plugin lifecycle
- Reports and diagnostics
There is no separate public adaptive runtime handle.
See docs/plugins/adaptive/configuration.md and
docs/about/concepts/plugins.md.
Keep In Sync
crates/adaptive- Shared plugin behavior in core and bindings
- Python adaptive/plugin wrappers in
python/nemo_relay/adaptive.pyandpython/nemo_relay/plugin.py - Go adaptive helpers under
go/nemo_relay/adaptiveplus shared plugin helpers ingo/nemo_relay - Node.js adaptive helpers and plugin wrappers
- Docs and examples that show canonical config shapes
Checklist
- Dynamic config shape still matches the documented canonical model
- Typed helper constructors still map cleanly to the same config document
- Plugin lifecycle is consistent across languages
- Plugin context surfaces remain aligned
- Validation/report behavior remains documented and tested
- Any new component kind has docs, examples, and binding coverage
Validation
- Run adaptive-focused Rust tests
- Run binding tests for every changed adaptive or plugin surface
- Update adaptive docs and any examples in the same branch
References
docs/plugins/adaptive/configuration.mddocs/plugins/adaptive/about.mddocs/plugins/adaptive/acg.mddocs/plugins/adaptive/adaptive-hints.mddocs/build-plugins/basic-guide.mddocs/build-plugins/validate-configuration.mddocs/about/concepts/plugins.mdvalidate-change
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 · 73 lines · 31 tokens per session scan A 2a8491fa503d
maintain-optimizer is a skill published in the GitHub repository NVIDIA/NeMo-Relay (132 stars, last pushed 3d ago), licensed Apache-2.0. It adds 31 tokens to every session and 490 once invoked, about $0.0002 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
agent-code-analyzer
Agent skill for code-analyzer - invoke with $agent-code-analyzer.
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
haiku
When writing a haiku for this bot, follow these conventions.
deploy-docker-compose
Run the Omnigent server as a Docker compose stack (server + Postgres) on any Docker host — your laptop, a VPS, EC2 by hand, or as the base layer of any container-platform deploy. Invoke when the user wants to build the image, bring up the compose stack, debug the stack on a host they already have, or extend the stack…
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".
dogfood
Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to dogfood, QA, exploratory test, find issues, bug hunt, or test this app on mobile.