OpenLoomi is an open-source desktop AI coworker that connects work tools, gathers context, and highlights decisions or actions needing attention. It is for people managing work across multiple apps, and its catalogue add-ons extend the resident desktop for agent frameworks such as Claude Code, Codex, OpenCode, Hermes, and OpenClaw.
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 melandlabs/openloomi --skill openloomi-memorygit clone --depth 1 https://github.com/melandlabs/openloomiWrote 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/melandlabs/openloomi/openloomi-memory)<a href="https://agentmods.dev/skills/melandlabs/openloomi/openloomi-memory"><img src="https://agentmods.dev/badge/skills/melandlabs/openloomi/openloomi-memory/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/melandlabs/openloomi/openloomi-memory"><img src="https://agentmods.dev/badge/skills/melandlabs/openloomi/openloomi-memory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 64 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Data Exfiltration · line 118 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 258 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Excessive Agency · line 409 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Data Exfiltration · line 423 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00074 | $0.06178 |
| Opus 5 | $0.00037 | $0.03089 |
| Sonnet 5 | $0.00015 | $0.01236 |
| Haiku 4.5 | $0.00007 | $0.00618 |
Grade A, and why
openloomi-memory scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST http://localhost:3414/api/rag/search \ How it starts
The opening of the file, as written. The whole thing — 735 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Note: If you haven't downloaded or installed openloomi yet, please refer to Getting Started for installation instructions.
OpenLoomi Memory Skill
OpenLoomi Memory is the long-lived context layer of OpenLoomi — a tiered, locally-stored knowledge graph that grows on its own from your Connectors, chats, and Screen Capture. Memory is what makes Chat grounded and what Loop reads before it produces a Decision. It is always on your machine (local-first), always visible, and always auditable — see Memory for the full model.
This skill exposes three searchable surfaces over that context:
| Surface | What it is | Where it lives |
|---|---|---|
| Memory files | People, projects, notes, strategy — your hand-edited knowledge graph | ~/.openloomi/data/memory/ |
| Knowledge Base | Documents you uploaded (PDF, DOCX, TXT, MD, slides, sheets, images) chunked + embedded via RAG | openloomi server |
| Insights | AI-extracted records (decisions, action items, preferences, relationships, events) derived from chats and source messages, with usage analytics + automatic maintenance | openloomi server |
Use search-all whenever the user asks a general memory question — it covers all three surfaces in one call.
Overview
Tiered model. OpenLoomi Memory spans four tiers that OpenLoomi reasons across simultaneously:
- Raw information — original messages, files, transcripts synced from your Connectors and Screen Capture.
- Insights — extracted entities, decisions, key events from chats and source messages. Each insight carries usage analytics (view frequency, sources, value score) and a maintenance cycle (daily analytics refresh, weekly compaction) that surfaces the most relevant records and prevents context decay.
- Contextual memory — recent conversation state, screen captures, and short-term references for the current task.
- Knowledge-base memory — the long-term people / projects / decisions / preferences graph that survives months of activity.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 735 lines · 74 tokens per session scan A cfc4401484d9
openloomi-memory is a skill published in the GitHub repository melandlabs/openloomi (1,023 stars, last pushed 9d ago), licensed Apache-2.0. It adds 74 tokens to every session and 6,178 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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