BD kaggle-openmm-md-runbook
OpenMM 8.3.1 molecular dynamics runbook for Kaggle free GPU (P100 sm_60): 100 ns checkpoint/resume across ~12 h sessions, fact registry (24 traps / 20 rules / 23 errors, stable IDs) + query CLI for token-efficient grounding, 22-gate static preflight checker (incl. enable_gpu + CPU fail-fast), literature-verified calibration protocol (CAL-01..12, orlistat/1LPB positive control), append-only lesson log. Use when planning, executing, debugging, calibrating, or handing off an OpenMM MD run on Kaggle.
OpenMM 8.3.1 molecular dynamics runbook for Kaggle free GPU (P100 sm60): 100 ns checkpoint/resume across ~12 h sessions, fact registry (24 traps / 20 rules /…
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 17. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: OpenMM 8.3.1 molecular dynamics runbook for Kaggle free GPU (P100 … ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
body-longSKILL.md body ≈ 5167 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "categories" - note
frontmatter-keyunknown frontmatter key "topics"
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 18 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70Execution cost. Instruction body is 5167 tokens
- 100Steps. 54 steps
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 15 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 tags): a typed call is more reliable
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
- +1No license
- +2Single-language instructions
- +3Description length 501: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 54 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 4 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.