acquiring-skills
Discover and install skills from Hermes, ClawHub, GitHub, and other registries. Load this skill whenever a user asks for a…
Read the official Letta documentation (docs.letta.com) through its cached, ETag-checked fetch route. Load before ANY docs.letta.com retrieval — answering how Letta works, what Letta (or you) can do, and looking up Letta API, Agent SDK, or Letta Code reference.
Claude Code
$ npx -y skills add letta-ai/letta-code --skill letta-guide --agent claude-code
Codex
$ npx skills add letta-ai/letta-code --skill letta-guide -a codex -y
Cursor
$ npx skills add letta-ai/letta-code --skill letta-guide -a cursor -y
Gemini CLI
$ npx skills add letta-ai/letta-code --skill letta-guide -a gemini-cli -y
GitHub Copilot
$ npx skills add letta-ai/letta-code --skill letta-guide -a github-copilot -y
OpenCode
$ npx skills add letta-ai/letta-code --skill letta-guide -a opencode -y
Windsurf
$ npx skills add letta-ai/letta-code --skill letta-guide -a windsurf -y
name: letta-guide description: Read the official Letta documentation (docs.letta.com) through its cached, ETag-checked fetch route. Load before ANY docs.letta.com retrieval — answering how Letta works, what Letta (or you) can do, and looking up Letta API, Agent SDK, or Letta Code reference.
Do not use fetch_webpage or web_search on docs.letta.com; this skill's helper is the docs route.
You are running inside Letta, but your training data about Letta's commands, flags, settings, UI, pricing, and providers is out of date. Users lose trust fastest when an agent confidently invents product details. This skill defines how to read the Letta docs correctly — both when answering questions about Letta and when looking up API, Agent SDK, or Letta Code reference during development. Guessing a docs URL and fetching it with `fetch_webpage` misses pages that exist under a different path and can serve stale content; the helper below fetches the live index first, so you pick a URL that exists.
1. **Self-inspection first for questions about THIS agent.** "What model are you using?", "what tools do you have?", "what's in your memory?" are questions about the running session, not the docs. Load the `self-configuration` skill for model or settings questions and use its backend-aware active configuration report. Use the system prompt, agent info, tool schemas, and MemFS for the other live facts. Do not infer active state from recent/default preference lists, and do not fetch docs for these. 2. **Fetch the docs index directly.** For product questions, run:
node <SKILL_DIR>/scripts/fetch-letta-docs.mjs
The helper retrieves `https://docs.letta.com/llms.txt` from the docs host, verifies its ETag against the body, and prints the paths to a current local copy and heading outline. Read the outline, then read the relevant index lines and their applicability labels to pick a page matching the user's backend and interface (see below). 3. **Fetch the specific page directly.** Pass the exact canonical URL from the index back to the same helper, for example:
node <SKILL_DIR>/scripts/fetch-letta-docs.mjs \
--docs-url "https://docs.letta.com/configuration/models/index.md"Read the returned docs path, including its frontmatter, before applying its instructions or running the helper for another URL. The helper uses native HTTPS with a curl fallback; do not use `fetch_webpage` for the normal docs route because its upstream content cache may be stale. Cite the public doc URL so the user can go deeper. 4. **If direct retrieval fails**, use `fetch_webpage` only as a fallback with a fresh query parameter on the same official docs URL. Disclose that the fallback may be stale. If that also fails, say the docs are unreachable, give your best answer, and clearly mark it as possibly out of date with a link to https://docs.letta.com. Never silently fall back to memory.
Read each page's `applies_to` frontmatter before using its instructions:
applies_to: backends: [cloud, local] interfaces: [web, desktop, cli, sdk]
means Letta Cloud; `local` means a user-managed backend.
cloud-only), CLI, Desktop, or SDK.
historical context.
file shapes, or UI paths.** If something is not in the fetched docs and you cannot verify it locally (`letta --help`, `/help`, reading the actual config file), say you are not sure or that it does not exist — do not guess a plausible-sounding name.
(chat.letta.com), and the API/SDK have different affordances. Answer for the surface the user is actually on; say when a feature lives on a different surface.
limits, data policies, the provider/model catalog, channel setup steps, and integration instructions.
https://github.com/letta-ai/letta-code/issues to request it.
When the docs don't resolve the user's problem — setup issues you can't debug, account/billing questions, suspected bugs, or anything needing a human — point them to the right channel:
very active — best for setup help, troubleshooting, and quick questions. It's also where users can chat with **Ezra**, Letta's support agent.
reports and feature requests.
If the user reports errors, timeouts, or things suddenly not working, check **https://status.letta.com** for an active incident before debugging — and have the user check it too.
Offer these proactively when you've hit the end of what the docs cover, rather than leaving the user stuck.
The helper owns the cache. It uses the first writable temporary directory from `TMPDIR`, `TEMP`, `TMP`, `/private/tmp`, or `/tmp`, and accepts `--cache-dir` when an explicit location is needed. Every invocation checks the live ETag and reuses the lo
Letta Code is a stateful agent harness for creating agents that are more like people than tools. Letta Code agents have memory, identity, and a sense of experience over time.
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