asta-software-experiment-runner（Asta 软件实验运行程序）

Run Experiments

Run a computational experiment. Given a research question that can be answered via software, this skill will write and run the necessary software and generate a report on the results.

This skill can also be used to analyze experimental data and generate a research report from it, even if the experiment itself was not run by Asta. In that case, the user can provide the experimental data as a file input, and Asta will analyze it and generate a report.

Installation

This skill requires the asta CLI:

# Install/reinstall at the correct version
PLUGIN_VERSION=0.13.0
if [ "$(asta --version 2>/dev/null | grep -oE '[0-9]+\.[0-9]+\.[0-9]+')" != "$PLUGIN_VERSION" ]; then
  uv tool install --force git+https://github.com/allenai/asta-plugins.git@v$PLUGIN_VERSION
fi

Prerequisites: Python 3.11+ and uv package manager

Workflow

The user will either:

1. describe the research task (TASK) and (optionally) background knowledge (BACKGROUND_KNOWLEDGE) or
2. provide paths to *files* that contain a. the task (TASK_FILE) b. (optionally) the background knowledge (BACKGROUND_KNOWLEDGE_FILE)

Default Output Locations

IMPORTANT: Always specify output locations to keep experiments organized in .asta/experiment/:

• OUTPUTS_DIR: .asta/experiment/<YYYY-MM-DD-slug>/ where:

- YYYY-MM-DD is the current date - slug is a short descriptive name derived from the task (e.g., "french-translation", "gpt4-eval")

• RESULT_FILE: <OUTPUTS_DIR>/result.json

Example directory structure:

.asta/experiment/
├── 2024-01-15-french-translation/
│   ├── result.json
│   └── [experiment outputs]
└── 2024-01-16-model-comparison/
    ├── result.json
    └── [experiment outputs]

The user may optionally override these locations by providing: 3. a custom directory for experimental outputs (OUTPUTS_DIR) 4. a custom path for the result summary JSON (RESULT_FILE)

Task and Background Knowledge

If the user describes a task and (optionally) provides background knowledge, then run as follows:

With default output locations (recommended):

# Create output directory with date and slug
OUTPUTS_DIR=".asta/experiment/$(date +%Y-%m-%d)-<task-slug>"
mkdir -p "$OUTPUTS_DIR"

asta experiment \
  --task "TASK" \
  --background_knowledge "BACKGROUND_KNOWLEDGE" \
  --force_report \
  --outputs_dir "$OUTPUTS_DIR" \
  --result_file "$OUTPUTS_DIR/result.json"

Example:

# Task: Assess GPT-4 translation quality
OUTPUTS_DIR=".asta/experiment/$(date +%Y-%m-%d)-gpt4-french-translation"
mkdir -p "$OUTPUTS_DIR"

asta experiment \
  --task "Perform an experiment to assess how good gpt-4o is at translating into French. Use just 5 test examples." \
  --force_report \
  --outputs_dir "$OUTPUTS_DIR" \
  --result_file "$OUTPUTS_DIR/result.json"

With custom output locations (if user specifies):

asta experiment \
  --task "TASK" \
  --background_knowledge "BACKGROUND_KNOWLEDGE" \
  --force_report \
  --outputs_dir "/custom/path/experiments/" \
  --result_file "/custom/path/result.json"

Task and Background Knowledge Files

When the user provides files containing the task and background knowledge:

With default output locations (recommended):

# Create output directory with date and slug (derived from task filename or content)
OUTPUTS_DIR=".asta/experiment/$(date +%Y-%m-%d)-<task-slug>"
mkdir -p "$OUTPUTS_DIR"

asta experiment \
  --task_file "TASK_FILE" \
  --background_knowledge_file "BACKGROUND_KNOWLEDGE_FILE" \
  --force_report \
  --outputs_dir "$OUTPUTS_DIR" \
  --result_file "$OUTPUTS_DIR/result.json"

Example:

# Files: my_project/task.txt, my_project/background_knowledge.txt
OUTPUTS_DIR=".asta/experiment/$(date +%Y-%m-%d)-custom-experiment"
mkdir -p "$OUTPUTS_DIR"

asta experiment \
  --task_file "my_project/task.txt" \
  --background_knowledge_file "my_project/background_knowledge.txt" \
  --force_report \
  --outputs_dir "$OUTPUTS_DIR" \
  --result_file "$OUTPUTS_DIR/result.json"

With custom output locations (if user explicitly specifies paths):

asta experiment \
  --task_file "my_project/task.txt" \
  --background_knowledge_file "my_project/background_knowledge.txt" \
  --force_report \
  --outputs_dir "my_project/experiments/" \
  --result_file "my_project/result.json"

Notes

• Output Directory: Always create .asta/experiment/<YYYY-MM-DD-slug>/ directory before running the experiment using mkdir -p
• Task Slug: Create a short descriptive slug from the task (e.g., "gpt4-translation", "model-comparison"). Keep it lowercase with hyphens.
• Result File: Always save to <OUTPUTS_DIR>/result.json for consistency
• Background Knowledge: Optional - can be omitted if not provided by user
• Custom Paths: If user explicitly provides custom output paths, use those instead of defaults
• Always return the result to the user and inform them where outputs were saved