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NeMo Guardrails Skill — measured AI agent skill | DecimalAI

a5c-ai/nemo-guardrails

SkillScore23Maintained

NVIDIA NeMo Guardrails configuration for conversational safety and control

by a5c-ai

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

AI Engineer pack

decimalai skills pull a5c-ai-nemo-guardrails

Get this skill — curl · raw file

curl -fsSL https://app.decimal.ai/s/a5c-ai-nemo-guardrails/SKILL.md

Raw file: /s/a5c-ai-nemo-guardrails/SKILL.md ↗ · machine-readable summary at /s/a5c-ai-nemo-guardrails.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

22 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 9d ago

Yes — +23% lift-9% tokens0% turns23% of whole cases pass with skill (5/22)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-01	✗→✓	▲ Improved	-29%	0%
case-02	✗→✓	▲ Improved	-48%	0%
case-07	✗→✓	▲ Improved	-4%	0%
case-08	✗→✓	▲ Improved	3%	0%
case-22	✗→✓	▲ Improved	-31%	0%

Showing 5 of 22 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 7/31/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

a5c-ai / babysitter

library/specializations/ai-agents-conversational/skills/nemo-guardrails/SKILL.md

View on GitHub ↗

License MITImported 7/31/2026Version v1

Skill contents

SKILL.md

NeMo Guardrails Skill

Capabilities

Configure NeMo Guardrails rails
Design Colang conversation flows
Implement input/output rails
Set up topic control
Configure jailbreak detection
Implement fact-checking rails

Target Processes

system-prompt-guardrails
content-moderation-safety

Implementation Details

Rail Types

Input Rails: Filter user inputs
Output Rails: Filter LLM outputs
Dialog Rails: Control conversation flow
Retrieval Rails: Filter retrieved content
Execution Rails: Control action execution

Colang Components

Flow definitions
Bot message templates
User message patterns
Actions and subflows

Configuration Options

Rails configuration
LLM selection
Embedding model
Action handlers
Custom rail implementations

Best Practices

Start with built-in rails
Design clear flows
Test with adversarial inputs
Monitor rail activations

Dependencies

nemoguardrails

Want to see if a5c-ai/nemo-guardrails would activate on your phrasing? Try it before you install — no LLM call, no signup.

Other measured skills in the registry, with their headline benchmark lift.