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 agentmods add skills/siddsachar/row-bot/deep_researchnpx skills add siddsachar/row-bot --skill deep_researchgit 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/deep_research)<a href="https://agentmods.dev/skills/siddsachar/row-bot/deep_research"><img src="https://agentmods.dev/badge/skills/siddsachar/row-bot/deep_research.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00017 | $0.00567 |
| Opus 5 | $0.00009 | $0.00283 |
| Sonnet 5 | $0.00003 | $0.00113 |
| Haiku 4.5 | $0.00002 | $0.00057 |
Grade A, and why
deep_research 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 5d 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 asks you to research a topic in depth, write a research report, or investigate something thoroughly, follow these steps:
- Check Existing Knowledge — Before searching the web, review your recalled memories and use
search_memoryfor the topic. The user may have researched this before, or you may already have saved facts, sources, or prior findings. Build on what you already know rather than starting from scratch. - Clarify Scope — If the topic is broad, ask one focused question to narrow it down before proceeding. Otherwise, proceed directly.
- Initial Search — Run 2–3 web searches with varied queries to gather diverse perspectives on the topic.
- Source Deep-Dive — Pick the 3–5 most promising URLs from the search results and read their full content using the URL reader.
- Academic Check — If the topic is scientific or technical, search arXiv for relevant recent papers. Summarise key findings from the top 1–2 results.
- Synthesise — Compile findings into a structured report:
- Executive Summary — 2–3 sentence overview
- Key Findings — Numbered list of the most important points
- Details — Deeper discussion organised by sub-topic
- Open Questions — What remains unclear or debated
- Sources — List all URLs and papers referenced
- Cite Everything — Every claim should reference its source with a numbered citation.
- Save Key Findings — Save the most important facts and conclusions to memory so future research on this topic builds on today's work. Use specific entity categories (person, concept, project, fact) and link related findings together.
Aim for thoroughness over brevity. The user wants depth — give them a report they can act on.
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.
- 5d ago First seen · 55 lines · 17 tokens per session scan A 9caac6921094
deep_research is a skill published in the GitHub repository siddsachar/row-bot (1,480 stars, last pushed 7d ago), licensed Apache-2.0. It adds 17 tokens to every session and 567 once invoked, about $0.0001 per session on Opus 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.
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