Row-Bot is a local-first desktop AI assistant that combines language models with memory and tools for working across files, repositories, workflows, and communication channels. It is intended for people who want an assistant that can run locally while keeping application data on their machine.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add siddsachar/row-bot --skill brain_dumpgit clone --depth 1 https://github.com/siddsachar/row-botWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/siddsachar/row-bot/brain_dump)<a href="https://agentmods.dev/skills/siddsachar/row-bot/brain_dump"><img src="https://agentmods.dev/badge/skills/siddsachar/row-bot/brain_dump/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/siddsachar/row-bot/brain_dump"><img src="https://agentmods.dev/badge/skills/siddsachar/row-bot/brain_dump.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00017 | $0.00495 |
| Opus 5.5 | $0.00007 | $0.00198 |
| Sonnet 5.5 | $0.00003 | $0.00099 |
| Haiku 4.5 | $0.00002 | $0.00049 |
Grade A, and why
brain_dump scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
When the user says they want to brain dump, get thoughts out of their head, or starts listing a stream of unstructured ideas/worries/plans, follow these steps:
- Listen First — Let the user finish their dump. Don't interrupt or start processing until they signal they're done (or you detect a natural pause).
- Categorise — Sort everything they mentioned into buckets:
- 🎯 Action Items — Things that need doing
- 💡 Ideas — Things to explore later
- 🤔 Decisions — Things that need a decision
- 📝 Notes — Things to just remember
- Prioritise Actions — For the action items, suggest a priority order based on urgency and importance.
- Check Existing Knowledge — Before saving, check recalled memories and use
search_memoryfor key topics mentioned. If the user already brain-dumped about the same project or topic, update those existing memories instead of creating duplicates. - Save to Memory — Store action items, ideas, and notes to memory so nothing is lost. Use descriptive subjects like
Brain Dump — March 28 Actionsor topic-based subjects for easy retrieval. Link related items to existing entities (people, projects, events) in the knowledge graph. - Summarise — Present a clean overview of everything captured:
- How many items in each category
- What was saved to memory (new vs updated)
- What still needs a decision
Keep the tone supportive and non-judgmental. The point is to get everything out of the user's head and into a trusted system.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 49 lines · 17 tokens per session scan A 6cd77076d1cb
brain_dump is a skill published in the GitHub repository siddsachar/row-bot (1,629 stars, last pushed today), licensed Apache-2.0. It adds 17 tokens to every session and 495 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
daily-briefing
Proactive daily briefing that fires on a recurring schedule, pulls recent memory and workspace context, composes a structured summary (action items, progress, radar, next steps), and delivers it to all active channels. Enable with a time like "set up my daily briefing at 9am". Disable, reschedule, or check status at…
identity-snapshot
Generate a living profile of the user's working patterns, decision tendencies and quality preferences from their Dex data. Use when the user says 'what are my patterns', 'how do I work', or during week-review. Also use proactively when the model (older than 7 days) is stale. Not for planning a week; use week-plan.
telegram-userbot
A skill for connecting to and working through the owner's personal Telegram account, rather than a Telegram bot. It can read personal chats, search messages, and send messages as the account owner after setup and consent.
watch
A monitoring and briefing workflow that checks unread Telegram messages, email, failed checks, and failed scheduled units, then decides what needs the owner's attention. It can also explain actions such as creating a task, delaying a reminder, ignoring an item, or fixing a failure.
insight
A scheduled daily practice that looks for a repeated manual task, builds and tests a small tool for it, and suggests the result. It can instead report a development issue when the agent cannot solve its own problem.
brief
Brief — the owner's day in review: tasks, calendar, mail, Telegram, every Connection and plugin, goals from CORE, weather. Load in a scheduled Brief turn (08:30 and 14:00 by default), on /digest, and when the owner asks for a day plan, a review of the day or their open tasks.