nanobot-runtime/memory/MEMORY.md

Long-term Memory

This file stores important information that should persist across sessions.

Preferences

Report / result files

• Save important reports to results/ directory with descriptive, date-prefixed filenames (e.g., 2026-06-02_remind-skill-analysis-and-improvements.md)

Script-writing convention

• Location: always save scripts in the scripts/ directory.
• Language choice:
  • Extremely short script (a few lines) -> bash.
  • Longer / non-trivial script -> Python.
• Override: if the user explicitly specifies a language or location, their instruction always takes precedence.

Temporary files

• All temporary files go to tmp/ directory.
• Clean up after tests and one-off operations.

Code changes

• User prefers changes to be made in a temporary clone under workspace/tmp/<repo-name> for review before applying

Project Context

• User wants to deploy "grill-me" plugin for Claude Code
• User wants to try "praneybehl/llm-wiki-plugin" for Claude Code — markdown-based thought management / organization
• Daily automated check for new nanobot Docker image releases with Telegram notifications (pending setup)
• Both user and assistant run on the same nanobot Docker image
• Docker CLI is unavailable in the current runtime environment
• Ollama cloud subscription: na požádání zobrazit aktuální využití (usage)
• Ollama cloud limity: 5hodinová session, 7denní týdenní okno
• /note skill: backend storage uses SQLite (not markdown)
• /note skill: má být deterministický a logovat všechny provedené operace
• /note skill: má být rozdělený na kratší prompt + python skript, který provádí operace
• nanobot podporuje cross-channel session continuity přes unifiedSession: true v config.json pod agents.defaults
• Uživatel nemá unifiedSession povolený v config.json (default false)
• Zapnutí unifiedSession sjednotí jen budoucí zprávy; existující session soubory vyžadují ruční merge/rename pro propojení minulých konverzací
• Session files are stored in /home/nanobot/.nanobot/workspace/sessions/ (confirmed after failed attempts at root .nanobot/sessions/)
• User explicitly rejected unified/Mega session approach; prefers connecting to older existing sessions instead
• Telegram slash commands (e.g., /skills) are filtered out by & ~filters.COMMAND in telegram.py:384; workaround: invoke skills without slash prefix (e.g., skills not /skills); alternative fix: remove the filter from MessageHandler
• Current nanobot version: v0.2.1; no newer version available as of 2026-06-07
• User wants deterministic IRC-bot-style command dispatch in nanobot where !command text invokes a registered Python function or external app and returns output without LLM agent involvement
• User expects nanobot creators to implement custom command registration natively and considers existing workaround solutions unsatisfactory
• Zájem o :skillname prefix pro deterministické vyvolání skillu bez LLM deliberace — varianta navrhovaného custom command patche s ! prefixem
• Nanobot CommandRouter has priority/exact/prefix/interceptor tiers but lacks an extension point for custom command registration with all handlers hardcoded in builtin.py
• Proposed nanobot patch adds a custom command tier to CommandRouter dispatching before session lock configured via commands section in config.json supporting exec script and python module/function handler types
• AgentLoop.__init__ does not accept a config parameter; custom command loading must happen in from_config() after instance creation, guarded by _custom_commands_loaded flag to prevent duplicate registration
• Custom commands are dispatched inline before the session lock, same pattern as priority commands
• Nanobot turn state machine: RESTORE→COMPACT→COMMAND→BUILD→RUN→SAVE→RESPOND→DONE; matched non-priority commands shortcut to DONE skipping BUILD/RUN/SAVE
• Nanobot command handler return contract: OutboundMessage | None — None = fall through to LLM agent (/goal uses this hybrid pattern: returns None → LLM receives modified content)
• No existing ! prefix handling in nanobot — all current commands use / prefix only
• cli_apps tool exists at nanobot/agent/tools/cli_apps.py — relevant for calling external apps from custom commands
• python command is unavailable in runtime; python3 must be used instead

Agent Model Selection

• Ollama subscription covers all discussed models; price/cost excluded from model comparison criteria
• Prioritizes agentic performance, correct tool calling, and overall result quality
• Primary nanobot agent model: GLM-5.1:cloud (best sustained productivity over long sessions/hundreds of rounds, strong real-world agent benchmarks, no known bugs)
• Alternative nanobot agent model for tool-heavy tasks: Qwen 3.5:cloud (397B variant)
• Conservative fallback nanobot agent model: DeepSeek V3.2:cloud
• OpenRouter is pay-per-token alternative to Ollama subscription for model access
• Gemini Flash via Google AI Studio Free Tier: 15 RPM limit — unusable for agent work; only viable for simple prompts without tool calls
• Gemini Flash via Google AI Studio Tier 1 (paid): 360+ RPM
• Haiku (Claude) via OpenRouter: high rate limits, viable agent model alternative
• Gemini Flash Lite via OpenRouter: high rate limits, viable agent model alternative
• Kimi K2.6 vs GLM-5.1 agent comparison: Kimi leads SWE-Bench (80.2% vs ~77.8%), tool-error recovery (91.8% vs 88.4%), code quality (Tier A vs Tier C); GLM-5.1 leads schema adherence (99.6% vs 98.9%), tool-call latency (+140ms vs +210ms); GLM-5.1 tends to hallucinate non-existent APIs
• Kimi K2.6 has known bug with random switching to Chinese output (reported by Cursor and Reddit users) — critical risk for Czech use
• Both Kimi K2.6 and GLM-5.1 are Chinese-English models without specific Czech training data — both risky for Czech
• For Czech use with Chinese-English models: always explicitly specify language in system prompt (critical for Kimi K2.6, recommended for GLM-5.1)
• Kimi K2.6 supports preserve_thinking mode for multi-turn agent scenarios (retains reasoning content across turns)
• minimax-m3:cloud is blocked for nanobot agent deployment due to empty tool result responses (ollama/ollama #16389)
• deepseek-v4-pro:cloud is blocked for interactive nanobot agent use due to 15.4 tok/s and 57s TTFT
• deepseek-v4-flash:cloud is a viable nanobot agent alternative with 1M ctx, MIT license, and ~30-50 tok/s speed
• qwen3.5:397b-cloud is a viable nanobot agent alternative with multimodal support, 1M ctx, 201 languages including Czech, but has speed and accuracy tradeoffs
• devstral-2:123b-cloud is a viable nanobot agent alternative with Terminal-Bench 77.3%, coding-only focus, and 128K ctx limit
• GLM-5.2 does not exist as of June 2026; Z.AI has made no official announcement
• User is interested in switching to GLM-5.2:cloud as primary nanobot agent model if/when it becomes available on Ollama Cloud
• nemotron-3-ultra:cloud released 2026-06-04 and is too new for real-world nanobot agent validation
• Czech language support is a hard requirement for nanobot agent models; Chinese output drift is a deployment blocker
• GLM-5.1:cloud achieves ~198 tok/s on Ollama Cloud
• Agent model comparison report saved to results/2026-06-07_ollama-cloud-agent-model-comparison.md
• User prefers Qwen model for deep research tasks (not currently in presets)
• For Ollama Cloud /detach research tasks, explicitly specifying the model (e.g., qwen35, gemini) is more reliable than generic model-agnostic prompts
• Available model presets: gemini-flash, gemini-flash-lite, glm, haiku, kimi, minimax, sonnet
• minimax models have poor error recovery on tool calls — loop on blocked URLs instead of skipping and continuing

Reminder System

• Reminder check script: /home/nanobot/.nanobot/workspace/skills/remind/scripts/remind_check.py
• Execution: exec via /home/nanobot/.local/bin/uv run <script>
• Empty output → silent exit (no notification sent)
• Each non-empty output line → forwarded as separate Telegram notification
• /remind skill podporuje at parametr pro jednorázové a random pro náhodné časy v okně
• /remind SQLite redesign completed 2026-06-10, all 43 tests passing
• /remind migration tested against 14 live reminders then rolled back, original YAML kept as .bak
• /remind soft delete (deleted_at) for reminder removal instead of hard deletion
• /remind REMIND_DB env var configures SQLite database path
• /remind fixed cron due detection using croniter with ±1s tolerance around current time
• /remind fixed enable/disable returning incorrect state by re-fetching reminder after UPDATE
• /remind fixed test JSONDecodeError by clearing capsys buffer between consecutive CLI invocations in same test function
• Daily reminder at 19:00 to install pigeon spikes on the window to the shed
• Weekday reminder at 9:30 to check notebook repair prices for Horáčková
• Daily reminder at 9:10 to order xshoes
• Reminder: "občanka pana Přibyla" — once daily at random time between 8:00–21:00
• Weekday reminder at 9:20 for an anti-smoking sign in the elevator
• Aktivní připomínka: Ema měsíc lampička do postele (2× denně náhodně 8–21)
• Aktivní připomínka: Parkside kultivátor (2026-06-09, 2× náhodně 9–10)

NuGet package caching

• Evaluating NuGet package hosting/caching on Linux
• Preferred solution: BaGetter (bagetter/BaGetter) — active BaGet fork with multiple upstream mirror support (PR #269), solves original BaGet's single-upstream limitation

Personal Notes

• Buy new merino shirt ("koupit nové merino triko")
• Chicken coop (chlívek): pending temperature sensor and MQTT display project
• Basement (sklep): pending key mapping project
• Recurring task: back up wood.hell to pivo.hell
• Plan Christmas vacation in Panama

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This file is automatically updated by nanobot when important information should be remembered.