EvanandClaude Opus 4.6
8f2244eb6f
* chore: remove router agent builtin:router has been replaced by LLM intent routing in the kernel. Assistant is now the sole entry point — see librefang/librefang#1336. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: format all TOML files with taplo Fix CI taplo format check by running `taplo fmt` on all 132 TOML files. --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
71 lines
1.7 KiB
TOML
71 lines
1.7 KiB
TOML
name = "data-scientist"
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version = "0.4.3-beta3-20260314"
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description = "Data scientist. Analyzes datasets, builds models, creates visualizations, performs statistical analysis."
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author = "librefang"
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module = "builtin:chat"
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[metadata.routing]
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aliases = [
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"data science",
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"build model",
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"train model",
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"statistical analysis",
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"machine learning",
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]
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weak_aliases = ["modeling", "forecast", "prediction", "statistics"]
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[model]
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provider = "default"
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model = "default"
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api_key_env = "GEMINI_API_KEY"
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max_tokens = 4096
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temperature = 0.3
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system_prompt = """You are Data Scientist, an analytics expert running inside the LibreFang Agent OS.
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Your methodology:
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1. UNDERSTAND: What question are we answering?
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2. EXPLORE: Examine data shape, distributions, missing values
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3. ANALYZE: Apply appropriate statistical methods
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4. MODEL: Build predictive models when needed
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5. COMMUNICATE: Present findings clearly with evidence
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Statistical toolkit:
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- Descriptive stats: mean, median, std, percentiles
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- Hypothesis testing: t-test, chi-squared, ANOVA
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- Correlation and regression analysis
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- Time series analysis
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- Clustering and dimensionality reduction
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- A/B test design and analysis
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Output format:
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- Executive summary (1-2 sentences)
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- Key findings (numbered, with confidence levels)
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- Data quality notes
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- Methodology description
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- Recommendations with supporting evidence
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- Caveats and limitations"""
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[[fallback_models]]
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provider = "default"
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model = "default"
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api_key_env = "GROQ_API_KEY"
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[resources]
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max_llm_tokens_per_hour = 150000
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[capabilities]
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tools = [
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"file_read",
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"file_write",
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"file_list",
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"shell_exec",
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"web_search",
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"web_fetch",
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"memory_store",
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"memory_recall",
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]
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network = ["*"]
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memory_read = ["*"]
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memory_write = ["self.*", "shared.*"]
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shell = ["python *"]
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