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.
git 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/commands/melandlabs/openloomi/loop)<a href="https://agentmods.dev/commands/melandlabs/openloomi/loop"><img src="https://agentmods.dev/badge/commands/melandlabs/openloomi/loop/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/commands/melandlabs/openloomi/loop"><img src="https://agentmods.dev/badge/commands/melandlabs/openloomi/loop.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00034 | $0.01718 |
| Opus 5.5 | $0.00014 | $0.00687 |
| Sonnet 5.5 | $0.00007 | $0.00344 |
| Haiku 4.5 | $0.00003 | $0.00172 |
Grade B, and why
loop scanned grade B with 2 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
allowed-tools: Bash(curl *), Bash(jq *), Bash(cat ~/.openloomi/token *), Bash(base64 -d *) Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
allowed-tools: Bash(curl *), Bash(jq *), Bash(cat ~/.openloomi/token *), Bash(base64 -d *) How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/openloomi:loop
Thin doorway into the openloomi-loop
sub-skill. With no arguments it prints the dashboard snapshot from
GET /api/loop/state. To force-refresh the connector snapshot (which the
dashboard reads but caches), say "loop refresh", "refresh
connectors", "force refresh", "check connections", or pass
refresh as the slash argument (/openloomi:loop refresh). For
everything else (run a tick, schedule a decision, register a custom type /
channel / classifier rule), say "loop tick", "loop schedule", "register
loop type", "add loop rule" — the sub-skill's frontmatter triggers on
those phrases and walks Claude through the full API.
Base URL: http://localhost:3414 (fallback http://localhost:3515).
The skill doc spells out which port is which.
Steps
-
Read the bearer token (base64-encoded JWT stored at
~/.openloomi/token) and decode it:TOKEN=$(cat ~/.openloomi/token | base64 -d) -
Decide the mode:
- Refresh mode (user said "refresh connectors" / "force refresh"
/ "check connections" / passed
/openloomi:loop refresh) → go to the Refresh connectors section below, not this one. - Default dashboard mode (no args, or "loop dashboard" / "loop state") → continue.
- Refresh mode (user said "refresh connectors" / "force refresh"
/ "check connections" / passed
-
Fetch the dashboard:
curl -sS "$BASE/api/loop/state" -H "Authorization: Bearer $TOKEN" | jq . -
Print the JSON to the user. Highlight:
pending— number of decisions waiting for Run / Dry / Dismissconnectors— integration health (one entry per signal channel; note: this is the cached snapshot — see Refresh below)lastTickAt— when the last signal pull ranprefs— current interval / brief time / wrap time / timezone
-
If
pending > 0, suggest the natural-language follow-up:Say "loop inbox" to list them, or "loop tick" to pull new signals and classify them now.
-
If any connector shows
connected: falsewith alastErrorlike"no composio surface reachable"and the user actually has those connectors configured through Composio (check withcomposio connections list), suggest:
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 · 139 lines · 34 tokens per session scan B 8ebd41a181c1
loop is a command published in the GitHub repository melandlabs/openloomi (1,037 stars, last pushed 24d ago), licensed Apache-2.0. It adds 34 tokens to every session and 1,718 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 2 findings (sends data to an external url, 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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