| name | scientist-plotting |
| description | Use when the user asks to '聚合作图', '补图表', '整理实验图', or wants experiment outputs converted into plots + plotting scripts directly in Copilot. Triggers on: 'aggregate plots', 'make figures from results'. Copilot-native — Copilot designs the figure and edits the script; the terminal only runs the Python plotting code. Do NOT use without existing experiment outputs. |
| version | 0.2.0 |
scientist-plotting
Generate plots and plotting scripts from an existing experiment directory. Model judgment and figure design are done by Copilot in-session.
Execution model
This is a Copilot-native model task. Copilot reads results, decides figure structure, writes / edits plotting code; the terminal only runs pure-Python plotting scripts.
Workflow
- Read the experiment directory's summary JSON, logs, CSVs, NPY files, or existing plots.
- Decide which metrics and comparisons to display.
- Create or edit matplotlib / seaborn / pandas plotting code directly.
- Run the plotting script and inspect the output.
- If the figure is unclear, iterate.
Input
folder: experiment directory- Result file paths and formats
- Figure conventions or paper-layout constraints the user wants preserved
Output
- Plotting script or edits to an existing script
- Output figure paths
- Figure design rationale and the key visual conclusions
Operating principles
- Only invoke this skill when the experiment outputs already exist.
- If result files are incomplete, flag the gap; NEVER fabricate plots.
Forbidden
- NEVER call any workspace-custom plotting model pipeline.
- NEVER use custom model calls in workspace code to "auto-plot."
Deliverable requirements
- Report figure paths.
- Name the source result files used.
- If a figure failed to render, return the real error and a suggested next step.
