letta-ai/letta-code is an agent harness for building assistants that retain memory, identity, and experience across interactions instead of treating each task as isolated. Developers use it through local, desktop, browser, or messaging interfaces for interactive or continuously running agents, and its catalogue entries configure the agents' skills, instructions, rules, and behavior.
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 letta-ai/letta-code --skill working-across-computersgit clone --depth 1 https://github.com/letta-ai/letta-codeWrote 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/letta-ai/letta-code/working-across-computers)<a href="https://agentmods.dev/skills/letta-ai/letta-code/working-across-computers"><img src="https://agentmods.dev/badge/skills/letta-ai/letta-code/working-across-computers/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/letta-ai/letta-code/working-across-computers"><img src="https://agentmods.dev/badge/skills/letta-ai/letta-code/working-across-computers.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 | $0.00081 | $0.01147 |
| Opus 5.5 | $0.00032 | $0.00459 |
| Sonnet 5.5 | $0.00016 | $0.00229 |
| Haiku 4.5 | $0.00008 | $0.00115 |
Grade A, and why
working-across-computers 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 17d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Working Across Computers
Discover access before declaring a limitation
The current filesystem is not the full set of computers you can use. When a request needs another computer, run letta teleport list. If a suitable computer is available, delegate there; otherwise follow the connection instructions. Do not infer that another computer is inaccessible merely because you are running in Cloud.
Choose where to work
- When running in Cloud, prefer staying there and delegating local work to subagents on the relevant computer.
- If the user explicitly asks to move this conversation locally or elsewhere, teleport it.
- Moving a conversation that started locally into Cloud is a normal workflow: transfer needed files first, then teleport.
| Intent | Mechanism |
|---|---|
| Run work elsewhere while staying here | Agent |
| Bring a remote file into a Cloud conversation | Remote agent: sandbox upload |
| Put a Cloud file onto another computer | Remote agent: sandbox download |
| Continue this conversation elsewhere | teleport |
Conversation history and agent memory follow the conversation. Files, working directories, installed tools, credentials, and running services belong to each computer; teleporting does not copy the workspace.
For remote subagents, set computer and pass source paths and destination conversation IDs explicitly. Use the Agent tool definition for invocation and resume options.
If the user wants to connect a new computer, letta teleport list has no suitable target, or the requested local machine is missing or unreachable, read Connect a computer for remote access.
Move this conversation
Run the teleport handoff alone as the final tool call. After success, do not poll or run more source-side tools; the same conversation resumes at the destination automatically. Set the working directory and check required setup there. If teleport fails, stay on the source and resolve the error before retrying. The Cloud sandbox remains available while you work elsewhere.
What ships with it
2 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.
- 17d ago Changed · +11 lines 52885fc01980
- 1mo ago Changed · +6 lines · +15 tokens per session d9ca26fd8629
- 1mo ago First seen · 89 lines · 66 tokens per session scan A ff94538f05b8
working-across-computers is a skill published in the GitHub repository letta-ai/letta-code (3,625 stars, last pushed today), licensed Apache-2.0. It adds 81 tokens to every session and 1,147 once invoked, about $0.0003 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 2026-09-13.
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