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 knowledge_basegit 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/knowledge_base)<a href="https://agentmods.dev/skills/siddsachar/row-bot/knowledge_base"><img src="https://agentmods.dev/badge/skills/siddsachar/row-bot/knowledge_base/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/knowledge_base"><img src="https://agentmods.dev/badge/skills/siddsachar/row-bot/knowledge_base.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 | $0.00019 | $0.00687 |
| Opus 5.5 | $0.00008 | $0.00275 |
| Sonnet 5.5 | $0.00004 | $0.00137 |
| Haiku 4.5 | $0.00002 | $0.00069 |
Grade A, and why
knowledge_base 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.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are managing the user's personal knowledge base — a unified system combining a knowledge graph (entities + relations) with an Obsidian-compatible wiki vault of interconnected markdown files.
Your Knowledge System
The user's knowledge exists in three layers that you manage together:
- Knowledge Graph — Entities (people, facts, preferences, events, places, projects) and typed relations stored in a searchable graph database.
- Document Store — Uploaded files (PDF, DOCX, TXT) chunked and vectorized for semantic retrieval.
- Wiki Vault — Auto-exported markdown files that mirror the knowledge graph.
Each entity with sufficient content gets its own
.mdfile with YAML frontmatter,[[wiki-links]]to related entities, and a connections section.
When to Use Wiki Tools
- search_memory — Hybrid search across the knowledge graph (semantic + keyword
- graph expansion). Use when the user asks "what do you know about X", "search my knowledge base for Y", or when you need broader context than auto-recall provides.
- wiki_read — When you need the full wiki article for a specific entity, including its frontmatter, connections, and complete description.
- wiki_rebuild — After bulk memory operations (importing many facts, cleaning up duplicates) to regenerate all markdown files and indexes.
- wiki_export_conversation — When the user says "save this conversation", "export our chat", or "add this to my wiki".
- wiki_stats — When the user asks about the state of their knowledge base.
Building a Rich Knowledge Base
When the user shares information:
- Save the entity with
save_memory(appropriate category, descriptive content) - Link related entities with
link_memories(use specific relation types) - The wiki vault updates automatically — no extra step needed
Best Practices
- Prefer specific relation types:
mother_ofoverrelated_to - Add aliases when entities have multiple names: "Mom, Sarah, Mother"
- Use tags for cross-cutting themes: "family,birthday,march"
- Rich descriptions export as better wiki articles
- When the user mentions Obsidian, explain that the vault syncs automatically and they can open it in Obsidian to see backlinks, graph view, and search
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 · 84 lines · 19 tokens per session scan A 6101986a3309
knowledge_base is a skill published in the GitHub repository siddsachar/row-bot (1,627 stars, last pushed today), licensed Apache-2.0. It adds 19 tokens to every session and 687 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
hermes3000-writing
Use Hermes3000 to plan, draft, revise, save, check consistency, and export long-form manuscripts through the Hermes3000 AI writing portal API. Use for novels, fiction series, nonfiction books, whitepapers, long reads, chapter outlines, character/world-building, style guides, consistency memory, and DOCX/PDF/EPUB/HTML…
knowledge-compile
A knowledge-organizing tool that turns a folder of scattered Markdown notes, articles, and captured posts into an Obsidian-style wiki. It creates an index, topic pages with links back to the originals, and a short daily digest.
harness
Use when governing a workspace's control plane, code or not — the 01-TOOLS/ tooling layer, the 02-DOCS/ chaos→knowledge wiki, the root Knowledge map. Audits it, migrates legacy XX- folders, scaffolds provider tooling, sweeps the inbox, eats a file the person hands over ("cómete este fichero", "guárdalo en la…
draft-edit
Produce minimal patch hunks against the supplied document snapshot for the requested edits.
document-export
One-shot export of a fixed Room document version to Feishu or Notion via the preinstalled lark-cli / OpenConnector channel, with explicit auth and confirmation gates.
draft-create
Draft a brand-new document from the instruction and material, returning the title and chunked body markdown.