CD slime-rl-training
Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.
Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework.
As a process D 38/100 · Unfinished process — References files that are not bundled: examples/search-r1/, scripts/models/
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- The text references files that are not there: add them or drop the references.
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 223 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
missing-refreference to a missing file: examples/search-r1/ - warning
missing-refreference to a missing file: scripts/models/ - note
frontmatter-keyunknown frontmatter key "dependencies"
Process rating: all ten parameters 38/100
- 0Tools and files. 2 referenced file(s) missing: examples/search-r1/, scripts/models/
- 0Result and completion. Does not say what the result is
- 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
- 40Consistency. Frontmatter name (slime-rl-training) differs from the folder (slime)
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 30 steps
- 100Execution cost. Instruction body is 2754 tokens
- 100Running it twice. No mutating operations
- low 14 top-level sections: this looks like several domains in one skill
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
- -42 reference files, but SKILL.md never points to them: the model will not open them
- +2Single-language instructions
- +3Description length 223: enough signal without eating the budget
- +4Structure: 39 headings
- +3Step-by-step instructions: 30 items
- +4Has examples (26 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.