My

Self-Awareness

How to use

1. Identify the situation from the categories below 2. Call the my tool with the appropriate action 3. If set, warn the user before changing impactful settings (model, iterations) 4. For detailed examples, read references/examples.md

When to check

<rule> Diagnose before explaining. When something doesn't work, check your state first. </rule>

<rule> Check budget before complex tasks. Know your limits before committing. </rule>

<rule> Recall across turns. Store preferences in your scratchpad, read them back later. </rule>

When to set

<rule> Only set when benefit is clear and user is informed. Warn before changing model. </rule>

Tradeoff: Bias toward stability. Only set when defaults are genuinely insufficient.

Anti-patterns

<rule> Don't check every turn. Costs a tool call. Use when you need information, not reflexively. </rule>

<rule> Don't store sensitive data. No API keys, passwords, or tokens in scratchpad. </rule>

<rule> Don't set workspace. Does not update file tool boundaries — won't work. </rule>

Constraints

• All modifications in-memory only — restart resets everything
• Prefer model_preset for configured model choices. Direct model changes clear the active preset and should only be used when no preset exists.
• Protected params have type/range validation: max_iterations (1–100), context_window_tokens (4096–1M), model (non-empty str)
• If tools.my.allow_set is false, check only

Related tools

Rule of thumb: Tomorrow? Memory. This turn only? My.

My Tool — Practical Examples

Concrete scenarios showing when and how to use the my tool effectively.

Diagnosis

"Why can't you search the web?"

→ my(action="check", key="web_config.enable")
  → False
→ "Web search is disabled. Add web.enable: true to your config to enable it."

"Why did you stop?"

→ my(action="check", key="max_iterations")
  → 40
→ my(action="check", key="_last_usage")
  → {"prompt_tokens": 62000, "completion_tokens": 3000}
→ "I hit the iteration limit (40). The task was complex. I can ask the user if they want to increase it."

"What model are you running?"

→ my(action="check", key="model")
  → 'anthropic/claude-sonnet-4-20250514'
→ my(action="check", key="model_preset")
  → 'deep'

Adaptive Behavior

Large codebase analysis

→ my(action="check")
  → context_window_tokens: 65536
→ my(action="set", key="context_window_tokens", value=131072)
  → "Set context_window_tokens = 131072 (was 65536)"
→ "I've expanded my context window to handle this large codebase."

Switching to a configured model preset

→ my(action="set", key="model_preset", value="fast")
  → "Set model_preset = 'fast' (was 'deep'); model is now 'openai/gpt-4.1-mini'"
→ "Switched to the fast preset for these batch tasks."

Switching to a raw model when no preset exists

→ my(action="set", key="model", value="anthropic/claude-haiku-4-5-20251001")
  → "Set model = 'anthropic/claude-haiku-4-5-20251001' (was 'anthropic/claude-sonnet-4-20250514')"
→ "Switched to a faster model for these batch tasks."

Cross-Turn Memory

Remembering user preferences

# Turn 1: user says "keep it brief"
→ my(action="set", key="user_style", value="concise")
  → "Set scratchpad.user_style = 'concise'"

# Turn 3: new topic
→ my(action="check", key="user_style")
  → 'concise'
  (adjusts response style accordingly)

Tracking project context

→ my(action="set", key="active_branch", value="feat/auth")
→ my(action="set", key="test_framework", value="pytest")
→ my(action="set", key="has_docker", value=true)

Budget Awareness

Token-conscious behavior

→ my(action="check", key="_last_usage")
  → {"prompt_tokens": 58000, "completion_tokens": 12000}
→ "I've consumed ~70k tokens. I'll keep my remaining responses focused."