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BF nemo-rl-auto-research

Autonomous NeMo-RL research agent workflow for directed hypothesis testing and open-ended discovery. Guides agents through the full experiment lifecycle: understanding recipes and environments, wiring RL or NeMo-gym runs, launching reproducible baselines and iterations, analyzing results, preserving human oversight, and using git plus TSV logs as the research ledger. Do NOT use for: bug fixes, code review, documentation, refactoring, dependency updates, or single-file changes.

ClawHub Agent Skills author: NVIDIA 1 file body ≈ 2 103 tokens Open the sourceclawhub.ai↗ analyzed 28 h ago

Autonomous NeMo-RL research agent workflow for directed hypothesis testing and open-ended discovery.

As a process F 57/100 · Will not run — References files that are not bundled: examples/run_grpo.py, examples/nemo_gym/, references/git-workflow.md

ProcedureSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
F
57/100
Will not run
References files that are not bundled: examples/run_grpo.py, examples/nemo_gym/, references/git-workflow.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
30
the three weakest of ten parameters · all ten

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 · 0

✓ No critical or high 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: examples/run_grpo.py
  • warning missing-ref reference to a missing file: examples/nemo_gym/
  • warning missing-ref reference to a missing file: references/git-workflow.md
  • warning missing-ref reference to a missing file: references/exploration-ideas.md
  • warning missing-ref reference to a missing file: references/experiment-log-template.md

Process rating: all ten parameters 57/100

Will not run. References files that are not bundled: examples/run_grpo.py, examples/nemo_gym/, references/git-workflow.md
  • 0Tools and files. 5 referenced file(s) missing: examples/run_grpo.py, examples/nemo_gym/, references/git-workflow.md
  • 0Result and completion. Does not say what the result is
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 70Failures and branches. 4 branches
  • 100Steps. 40 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2103 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress

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
  • +3Output format is not stated: the model decides each time
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 481: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 40 items
  • +4Has examples (1 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.