This skill should be used when the user asks to "analyze experimental results", "run strict statistical analysis", "compare model performance", "generate scientific figures", "check significance", "do ablation analysis", or mentions interpreting experiment data with rigorous statistics and visualization. It focuses on strict analysis bundles, not Results-section prose.
SkillScore82Maintained
Automatic
◆Research pack
Last verified 8/8/2026
What it changes
Passed 16 of 20 test cases with the skill, and 7 of 20 without it.
Refers manuscript drafting requests to ml-paper-writing.
and 11 more in the full report
10 fixed8 passed either way4 still failing0 broke
Pass-rate lift
+45 pp
Tokens
+39%
Agent turns
0%
Response time
-22%
Model gemini-3.6-flashMeasured 8/8/2026v118 of 22 cases passed with skill · 20 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 10
Prompt
We are performing the final quality check on our generated analysis bundle output folder before completing the task. What negative constraint must be verified regarding narrative text?
What was checked, without and with the skill
Checked
Without skill
With skill
Verifies that manuscript prose sections are excluded from the output bundle.
Missed
Passed
case-21 · gemini-3.6-flash · 8/8/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md202 lines7 files
Results Analysis
Run strict, evidence-first experimental analysis for ML/AI research.
Use this skill to produce a strict analysis bundle:
analysis-report.md
stats-appendix.md
figure-catalog.md
figures/
Do not use this skill to draft a paper Results section or a full experiment wrap-up report. Those belong to ml-paper-writing or results-report.
Core contract
This skill is responsible for
validating experiment artifacts and comparison units,
running rigorous descriptive and inferential statistics,
generating real scientific figures when data/logs are available,
writing figure purposes, caption requirements, and interpretation checklists,
surfacing limits, blockers, and missing evidence explicitly.
This skill is not responsible for
paper-ready Results prose,
manuscript narrative polishing,
project-level experiment retrospectives.
If the user wants the complete post-experiment summary report, hand off to results-report after this bundle is ready.
Non-negotiable quality bar
Prefer real figures over figure specs.
If the data can be read, generate real figures. Do not stop at “recommended visualization”.
Never fabricate statistics.
If sample size, seeds, or raw metrics are missing, state the blocker clearly.
Report complete statistics.
Do not report only best scores or only p-values.
Interpret every main figure.
Every major figure must have purpose, caption requirements, and post-figure interpretation notes.
Separate evidence from prose.
This skill produces analysis artifacts; it does not write manuscript sections.