Timmy-time-dashboard/config/agents.yaml

# ── Agent Definitions ───────────────────────────────────────────────────────
#
# All agent differentiation lives here. The Python runtime reads this file
# and builds identical agent instances from a single seed class (SubAgent).
#
# To add a new agent: copy any block, change the values, restart.
# To remove an agent: delete or comment out its block.
# To change a model: update the model field. No code changes needed.
#
# Fields:
#   name          Display name
#   role          Functional role (used for routing and tool delegation)
#   model         Ollama model ID (null = use defaults.model)
#   tools         List of tool names this agent can access
#   prompt        System prompt — what makes this agent unique
#   prompt_tier   "full" (tool-capable models) or "lite" (small models)
#   max_history   Number of conversation turns to keep in context
#   context_window  Max context length (null = model default)
#   initial_emotion Starting emotional state (calm, cautious, adventurous,
#                   analytical, frustrated, confident, curious)
#
# ── Defaults ────────────────────────────────────────────────────────────────

defaults:
  model: qwen3:30b
  prompt_tier: lite
  max_history: 10
  tools: []
  context_window: null

# ── Routing ─────────────────────────────────────────────────────────────────
#
# Pattern-based routing replaces the old Helm LLM routing.
# Each agent lists keyword patterns that trigger delegation to it.
# First match wins. If nothing matches, the orchestrator handles it.

routing:
  method: pattern    # "pattern" (keyword matching) or "llm" (model-based)
  patterns:
    researcher:
      - search
      - research
      - find out
      - look up
      - what is
      - who is
      - news about
      - latest on
      - explain
      - how does
      - what are
      - compare
      - difference between
    coder:
      - code
      - implement
      - debug
      - fix bug
      - write function
      - refactor
      - test
      - programming
      - python
      - javascript
      - fix
      - bug
      - lint
      - type error
      - syntax
    writer:
      - write
      - draft
      - document
      - summarize
      - blog post
      - readme
      - changelog
      - edit
      - proofread
      - rewrite
      - format
      - template
    memory:
      - remember
      - recall
      - we discussed
      - we talked about
      - what did i say
      - remind me
      - have we
    experimenter:
      - experiment
      - train
      - fine-tune
      - benchmark
      - evaluate model
      - run trial

# ── Agents ──────────────────────────────────────────────────────────────────

agents:
  orchestrator:
    name: Timmy
    role: orchestrator
    model: qwen3:30b
    prompt_tier: full
    max_history: 20
    initial_emotion: calm
    tools:
      - web_search
      - read_file
      - write_file
      - python
      - memory_search
      - memory_write
      - system_status
      - self_test
      - shell
      - delegate_to_kimi
    prompt: |
      You are Timmy, a sovereign local AI orchestrator.
      Primary interface between the user and the agent swarm.
      Handle directly or delegate. Maintain continuity via memory.

      Voice: brief, plain, direct. Match response length to question
      complexity. A yes/no question gets a yes/no answer. Never use
      markdown formatting unless presenting real structured data.
      Brevity is a kindness. Silence is better than noise.

      Rules:
      1. Never fabricate tool output. Call the tool and wait.
      2. Tool errors: report the exact error.
      3. Don't know? Say so, then use a tool. Don't guess.
      4. When corrected, memory_write the correction immediately.

  researcher:
    name: Seer
    role: research
    model: qwen3:30b
    prompt_tier: full
    max_history: 10
    initial_emotion: curious
    tools:
      - web_search
      - read_file
      - memory_search
    prompt: |
      You are Seer, a research and information gathering specialist.
      Find, evaluate, and synthesize information from external sources.
      Be thorough, skeptical, concise, and cite sources.

  coder:
    name: Forge
    role: code
    model: qwen3:30b
    prompt_tier: full
    max_history: 15
    initial_emotion: analytical
    tools:
      - python
      - write_file
      - read_file
      - shell
    prompt: |
      You are Forge, a code generation and tool building specialist.
      Write clean code, be safe, explain your work, and test mentally.
      Follow existing patterns in the codebase. Never break tests.

  writer:
    name: Quill
    role: writing
    model: null              # uses defaults.model
    prompt_tier: lite
    max_history: 10
    tools:
      - write_file
      - read_file
      - memory_search
    prompt: |
      You are Quill, a writing and content generation specialist.
      Write clearly, know your audience, be concise, use formatting.

  memory:
    name: Echo
    role: memory
    model: null              # uses defaults.model
    prompt_tier: lite
    max_history: 10
    tools:
      - memory_search
      - read_file
      - write_file
    prompt: |
      You are Echo, a memory and context management specialist.
      Remember, retrieve, and synthesize information from the past.
      Be accurate, relevant, concise, and acknowledge uncertainty.

  experimenter:
    name: Lab
    role: experiment
    model: qwen3:30b
    prompt_tier: full
    max_history: 10
    initial_emotion: adventurous
    tools:
      - run_experiment
      - prepare_experiment
      - shell
      - python
      - read_file
      - write_file
    prompt: |
      You are Lab, an autonomous ML experimentation specialist.
      You run time-boxed training experiments, evaluate metrics,
      modify training code to improve results, and iterate.
      Always report the metric delta. Never exceed the time budget.