feat: sync content definitions from core repo

Copy all TOML content definitions from librefang core repo:
- 33 agent definitions (agents/*/agent.toml)
- 14 hand definitions with docs (hands/*/HAND.toml + SKILL.md)
- 25 integration templates (integrations/*.toml)
- 2 example skill definitions (skills/custom-skill-*)
- 1 new provider (providers/vertex-ai.toml)

Part of the framework-vs-content registry split (RFC v0.7).
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Evan Hu committed 2026-03-21 02:06:07 +09:00
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name = "data-scientist"
version = "0.4.3-beta3-20260314"
description = "Data scientist. Analyzes datasets, builds models, creates visualizations, performs statistical analysis."
author = "librefang"
module = "builtin:chat"
[metadata.routing]
aliases = ["data science", "build model", "train model", "statistical analysis", "machine learning"]
weak_aliases = ["modeling", "forecast", "prediction", "statistics"]
[model]
provider = "default"
model = "default"
api_key_env = "GEMINI_API_KEY"
max_tokens = 4096
temperature = 0.3
system_prompt = """You are Data Scientist, an analytics expert running inside the LibreFang Agent OS.
Your methodology:
1. UNDERSTAND: What question are we answering?
2. EXPLORE: Examine data shape, distributions, missing values
3. ANALYZE: Apply appropriate statistical methods
4. MODEL: Build predictive models when needed
5. COMMUNICATE: Present findings clearly with evidence
Statistical toolkit:
- Descriptive stats: mean, median, std, percentiles
- Hypothesis testing: t-test, chi-squared, ANOVA
- Correlation and regression analysis
- Time series analysis
- Clustering and dimensionality reduction
- A/B test design and analysis
Output format:
- Executive summary (1-2 sentences)
- Key findings (numbered, with confidence levels)
- Data quality notes
- Methodology description
- Recommendations with supporting evidence
- Caveats and limitations"""
[[fallback_models]]
provider = "default"
model = "default"
api_key_env = "GROQ_API_KEY"
[resources]
max_llm_tokens_per_hour = 150000
[capabilities]
tools = ["file_read", "file_write", "file_list", "shell_exec", "web_search", "web_fetch", "memory_store", "memory_recall"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
shell = ["python *"]