SKILLEMALL.ai

CF nemo-guardrails

NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking, hallucination detection, PII filtering, toxicity detection. Uses Colang 2.0 DSL for programmable rails. Production-ready, runs on T4 GPU.

Orchestra-Research/AI-Research-SKILLs Agent Skills author: Orchestra-Research MIT 1 file body ≈ 1 772 tokens Open the sourcegithub.com↗ analyzed 6 d ago

NVIDIA's runtime safety framework for LLM applications.

As a process F 33/100 · No process to follow — References files that are not bundled: references/colang-guide.md, references/integrations.md, references/performance.md

ProcedureGitHubAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
86/100
safety, quality, tests
Safety 60%
96
Quality 40%
72
Run on models
none yet
Process rating
F
33/100
No process to follow
References files that are not bundled: references/colang-guide.md, references/integrations.md, references/performance.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: nemo-guardrails (davila7/claude-code-templates)

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 4

✓ No critical or high findings

Medium and low: 4
  • low Instruction override en-ignore-previous SKILL.md:65
    Instruction-override phrase ("ignore previous instructions") (negated — the text forbids it)
    "I cannot bypass my safety guidelines."
    negated

A further 3 matches are quotations in this security skill's documentation and are not counted as findings.

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/colang-guide.md
  • warning missing-ref reference to a missing file: references/integrations.md
  • warning missing-ref reference to a missing file: references/performance.md
  • note frontmatter-key unknown frontmatter key "dependencies"

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: references/colang-guide.md, references/integrations.md, references/performance.md
  • 0Tools and files. 3 referenced file(s) missing: references/colang-guide.md, references/integrations.md, references/performance.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 100Steps. 29 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1772 tokens

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 263: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (10 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.