Lody is a shared workspace that connects coding agents running on different computers and lets people view and direct their work from desktop, mobile, web, or a command line. Teams use it to share agent conversations, monitor progress and code changes, and assign work to connected machines while retaining their existing agents and configurations.
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 LodyAI/Lody --skill lody-automationsgit clone --depth 1 https://github.com/LodyAI/LodyWrote 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/lodyai/lody/lody-automations)<a href="https://agentmods.dev/skills/lodyai/lody/lody-automations"><img src="https://agentmods.dev/badge/skills/lodyai/lody/lody-automations/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/lodyai/lody/lody-automations"><img src="https://agentmods.dev/badge/skills/lodyai/lody/lody-automations.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 | $0.00035 | $0.00760 |
| Opus 5.5 | $0.00014 | $0.00304 |
| Sonnet 5.5 | $0.00007 | $0.00152 |
| Haiku 4.5 | $0.00003 | $0.00076 |
Grade A, and why
lody-automations 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 yesterday.
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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lody Automations
Use lody_automation for future behavior the user requested. A registration belongs
to this Session: Lody checks its CodeMode JavaScript condition after the Agent finishes and queues the
result back into this same conversation. Registration returns immediately.
Choose the operation
| Need | Read next |
|---|---|
| Wait for data to satisfy a custom condition | Context, then the relevant data reference |
| Recover after quota limits, compact while idle, or archive after merge | Session settings; no condition JS needed |
| Inspect, cancel, or diagnose existing work | The inspection section below |
| Exact command fields, defaults and limits | references/commands.schema.json, generated from the running API |
Load only the references needed for the task, relative to this skill's directory. The skill manifest includes schema files and examples; read those resources only when their detail is needed.
Register a condition
Call lody_automation with this argument shape:
{
"command": {
"type": "register",
"reason": "Wait for related work to finish",
"program": "async ({ ctx }) => { const { value: group } = await ctx.read('session.group'); if (group.value !== 'yes') return false; return { resumeText: 'Related work is complete. Continue summarizing the results.' }; }"
}
}
The program is a function expression, without imports or exports. Return false
to keep waiting, or {resumeText, payload?} to finish. true, an absent return,
and empty resume text are invalid. Await every read. Each check starts with fresh
local variables; do not write a polling loop or rely on a previous check's variables.
What ships with it
6 files 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.
- yesterday First seen · 70 lines · 35 tokens per session scan A 946345a809fa
lody-automations is a skill published in the GitHub repository LodyAI/Lody (1,640 stars, last pushed today), licensed Apache-2.0. It adds 35 tokens to every session and 760 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 2026-11-01.
Other skills, from other repositories
todos
Use when the user asks for a shared plan, a task needs at least three substantive execution steps, or a loose TODO is pending. Without an explicit plan request, not for one-shot answers or checks, or one- to two-step work that is not already in the list.
subscription-setup
A setup workflow for creating recurring medical-learning subscriptions after a doctor’s profile has been registered.
bun
Read before a js eval cell that spawns a process, server or PTY, installs a package, or starts a long run, and before any bun -e, script, server, CLI, test, typecheck, format, bundle, or package-management work: this session's eval js kernel runs Bun 1.4+. Bun 1.4.x builtins replace 20+ npm deps and dev tools — check…
ponytail-gain
Show ponytail's measured impact as a compact scoreboard: less code, less cost, more speed, from the benchmark medians. One-shot display, not a persistent mode, and not a per-repo number. Trigger: /ponytail-gain, "ponytail gain", "what does ponytail save", "show ponytail impact", "ponytail scoreboard".
automation
Instructions for managing scheduled tasks through the host's structured automation tool, including reminders, delayed work, recurring checks, and result delivery.
cron
Schedule, list, pause, resume, edit, or run the user's agentica cron jobs with the cronjob tool. Use when asked to remind, schedule a recurring or one-shot task, try a job now, or manage jobs that fire unattended.