Use this skill when baseline NeMo Relay instrumentation exists and the user wants to configure or evaluate adaptive plugin behavior, including telemetry, state, adaptive_hints, tool_parallelism, ACG, hint consumption, or measured rollout.
SkillScore95Maintained
Automatic
◆AI Engineer pack
Last verified 8/12/2026
What it changes
Passed 21 of 22 test cases with the skill, and 9 of 22 without it.
Without skill41%
With skill95%
Checks it passed that the model alone missed
The answer specifies nemo-relay-node/adaptive.
The plugin configuration specifies kind: adaptive.
The response directs the team to references/config.md.
and 11 more in the full report
12 fixed9 passed either way1 still failing0 broke
Pass-rate lift
+55 pp
Tokens
-7%
Agent turns
0%
Response time
-56%
Model gemini-3.6-flashMeasured 8/12/2026v121 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 12 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 12
Prompt
Which Rust crate provides the first-party helper APIs for consuming adaptive signals in a Rust NeMo Relay application?
What was checked, without and with the skill
Checked
Without skill
With skill
The answer specifies nemo_relay_adaptive as the Rust library.
Missed
Passed
case-17 · gemini-3.6-flash · 8/12/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md94 lines3 files
Tune Adaptive Plugin Behavior
Use This When
Use this skill when a user has baseline NeMo Relay instrumentation and wants to
improve latency, parallelism, prompt-cache behavior, or model-request behavior
from runtime signals.
Keep adaptive behavior measured against a known baseline.
Do Not Use This When
Do not use this skill when the application is not instrumented yet. Start with
nemo-relay-instrument-calls or nemo-relay-get-started first.
Default Guidance
Observe first, compare against a baseline, then enable one behavior change at
a time.
Use the adaptive plugin component rather than inventing separate tuning logic
or hand-registering adaptive behavior at every call site.
Start with in-memory state and telemetry-only behavior for local development.
Move to persistent state only when learned signals must survive restarts or be
shared across workers.
Add active behavior only after representative runtime events show what should
change.
Embedded Adaptive Model
Adaptive behavior is configured through the first-party plugin component with
kind adaptive.
Adaptive requires existing NeMo Relay scopes and at least one relevant
managed tool or LLM lifecycle event stream because it learns from runtime
signals.
Main configuration areas are state, telemetry, adaptive hints, tool
parallelism, Adaptive Cache Governor (ACG), and rollout policy.
State backends are in_memory and redis.
Tool-parallelism modes are observe_only, inject_hints, and schedule.
Adaptive Cache Governor providers are passthrough, anthropic, and
openai; omit ACG until prompt-cache planning is needed.
Helper APIs exist in Rust nemo_relay_adaptive, Python nemo_relay.adaptive,