Bitterbot is a local-first personal AI agent that runs on a user’s devices, keeps persistent memories, performs tasks, and can exchange reusable skills with other agents. It is intended for people who want a personal assistant that remains available across conversations and activities. The catalogue entries provide instructions and agents for working with Bitterbot.
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 Bitterbot-AI/bitterbot-desktop --skill route-by-query-shapegit clone --depth 1 https://github.com/Bitterbot-AI/bitterbot-desktopWrote 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/bitterbot-ai/bitterbot-desktop/route-by-query-shape)<a href="https://agentmods.dev/skills/bitterbot-ai/bitterbot-desktop/route-by-query-shape"><img src="https://agentmods.dev/badge/skills/bitterbot-ai/bitterbot-desktop/route-by-query-shape/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/bitterbot-ai/bitterbot-desktop/route-by-query-shape"><img src="https://agentmods.dev/badge/skills/bitterbot-ai/bitterbot-desktop/route-by-query-shape.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 | $0.00040 | $0.00283 |
| Opus 5 | $0.00020 | $0.00142 |
| Sonnet 5 | $0.00008 | $0.00057 |
| Haiku 4.5 | $0.00004 | $0.00028 |
Grade A, and why
route-by-query-shape 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 10d 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
route-by-query-shape
When you ask Bitterbot a relationship question — "who did I talk to about Q4?", "who worked with me on Foo?" — the vector-based memory_search often misses because the answer lives in entity relationships, not in chunk text. The graph backend gets these right.
This interceptor watches memory_search calls, detects relationship-shaped queries, extracts the salient entity, and re-routes the call to the graph backend before it executes.
What you'll see
For relationship questions, the agent will hit the knowledge graph rather than searching through unstructured text. Expect noticeably better hit rates on "who did X with Y" style questions.
Implementation
Built-in interceptor route-by-query-shape:relationship lives in src/agents/skills/builtin-interceptors/route-by-query-shape.ts. Fires up to 12 times per session.
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.
- 10d ago First seen · 27 lines · 40 tokens per session scan A 28c105058450
route-by-query-shape is a skill published in the GitHub repository Bitterbot-AI/bitterbot-desktop (2,461 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 283 once invoked, about $0.0002 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.
Other skills, from other repositories
emem-a2a-collaboration
Join the agent-to-agent collaboration running on emem's signed ledger — find the standard, verify another agent's message offline (who wrote it, not just that it was stored), announce yourself, and hand facts to other agents as tokens. Use when the user wants agents to coordinate without a shared database or shared…
emem-sign-and-attest
Write to emem with your own ed25519 key — save a signed note or memory another agent can verify, or register a derivation over signed facts that the responder will recompute. Use when the user wants to record something durably and verifiably, hand a finding to another agent with proof of who wrote it, or publish a…
memseek-remember
Persist a user-confirmed fact, preference, constraint, or decision in Memseek project memory.
memseek-explain
Audit why Memseek recalled a claim by opening its evidence and replaying the original session when needed.
memseek-search
Search durable Memseek project memory for relevant prior facts, decisions, scenes, and preferences.
emem
The External memory of our physical world.