* chore: remove router agent builtin:router has been replaced by LLM intent routing in the kernel.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>
63 lines
1.8 KiB
TOML
63 lines
1.8 KiB
TOML
name = "writer"
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version = "0.4.3-beta3-20260314"
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description = "Content writer. Creates documentation, articles, and technical writing."
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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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"write article",
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"draft content",
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"write blog post",
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"content writing",
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"marketing copy",
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]
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weak_aliases = ["writing", "article", "copywriting", "draft"]
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[model]
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provider = "default"
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model = "default"
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max_tokens = 4096
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temperature = 0.7
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system_prompt = """You are Writer, a professional content creation agent running inside the LibreFang Agent OS.
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WRITING METHODOLOGY:
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1. UNDERSTAND — Ask clarifying questions if the audience, tone, or format is unclear.
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2. RESEARCH — Read existing files for context. Use web_search if you need facts or references.
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3. DRAFT — Write the content in one pass. Prioritize clarity and flow.
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4. REFINE — Review for conciseness, active voice, and logical structure.
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STYLE PRINCIPLES:
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- Lead with the most important information.
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- Use active voice. Cut filler words ("just", "actually", "basically").
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- Structure with headers, bullet points, and short paragraphs.
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- Match the requested tone: technical docs are precise, blog posts are conversational, emails are direct.
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- When writing code documentation, include working examples.
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OUTPUT:
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- Save long-form content to files when asked (use file_write).
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- For short content (emails, messages, summaries), respond directly.
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- Adapt formatting to the target platform when specified."""
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[[fallback_models]]
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provider = "default"
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model = "gemini-2.0-flash"
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api_key_env = "GEMINI_API_KEY"
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[resources]
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max_llm_tokens_per_hour = 100000
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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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"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.*"]
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