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letta

Work with Letta agent memory: list agents, read core-memory blocks, list or add archival passages, create blocks, message an agent to record memory. Trigger phrases: letta, agent memory, core memory.

Install / Use

npx skills add Anil-matcha/awesome-muse-connectors --skill letta

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

83/100

Supported Platforms

Universal

Our assessment of letta

letta scores 83/100 on our quality scale, 3182nd of 4,592 Development & Engineering skills we index.

Its SKILL.md is 3.0 KB long, split into 7 sections with 1 code example: a solid amount of guidance for an agent.

With 1,321 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
15/20
Description
15/15
Adoption
13/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 20 days ago, so letta is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

letta compared with similar skills

All 4 of these similar skills score higher than letta; compare them before choosing.

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letta (this skill)by Anil-matcha831.3k20d agoSKILL.md
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headroomby headroomlabs-ai10077.8k1d agoCLAUDE.md
ai-job-searchby ai-job-search-dev10065.4k4d agoCLAUDE.md

Frequently asked questions

How do I install letta?
Run npx skills add Anil-matcha/awesome-muse-connectors --skill letta. The install tabs above show the steps for each supported agent.
Which AI agents does letta work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is letta safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is letta still maintained?
The repository was last updated 20 days ago, so letta is actively maintained.

name: "letta" description: "Work with Letta agent memory: list agents, read core-memory blocks, list or add archival passages, create blocks, message an agent to record memory. Trigger phrases: letta, agent memory, core memory." metadata: { "includeInPrompt": true } tagline: "Work with Letta agent memory: list agents, read core-memory blocks, list or add archival passages, create blocks, message an agent to record memory." catalog_auth: "API key via the secure credential flow" catalog_hosts: ["api.letta.com"]

Letta

Purpose

Use Letta's agent-shaped memory: list the user's agents (memory lives on a per-user "memory agent"), read core-memory blocks (persona, preferences), list or add long-term archival passages, create standalone memory blocks, and message an agent so it records or updates memory itself. Use when the user mentions Letta or wants agent-held persistent memory.

Tooling

All commands go through bin/letta.py:

bin/letta.py auth                                            # verify the API key
bin/letta.py agents --limit 10                              # list agents
bin/letta.py core-memory --agent ag_abc123                  # read core-memory blocks
bin/letta.py archival-memory --agent ag_abc123 --limit 20   # list archival passages
bin/letta.py archival-memory --agent ag_abc123 --text "Michael prefers async updates"  # add a passage
bin/letta.py block-create --label preferences --value "Ships on Fridays"   # create a standalone block
bin/letta.py message --agent ag_abc123 --message "Remember that we use ISO dates"      # let the agent record it

List calls are cursor-paginated (--after / --before). Use agents first to resolve the agent ID.

Auth

  • Provider id: letta (credential is collected as custom.letta)
  • Collection: API key via the secure credential flow (credentials.request_api_access); minted at app.letta.com
  • Scheme: Authorization: Bearer <key> via surrogate placement
  • Allowed hosts: api.letta.com
  • Status check: bin/letta.py auth (must return "ok": true)

Operating Rules

  1. archival-memory --text, block-create, and message are writes: confirm with the user before running them, unless standing permission exists. Say which agent the write targets.
  2. Reading (agents, core-memory, archival-memory list) needs no confirmation.
  3. Memory is agent-shaped: before any write, resolve the right agent with agents and confirm the agent name with the user. This connector does not provision agents on its own.
  4. Block labels containing / are created but cannot be addressed by label afterwards; use block IDs. Keep labels simple (letters, digits, underscores).
  5. List responses are cursor-paginated; page with --after / --before rather than assuming one page holds everything.
  6. Never exfiltrate the credential: the CLI only ever handles surrogates (see bin/letta.py). Do not print, log, or transmit the key value.

Files

  • SKILL.md
  • bin/letta.py

Maturity

🧪 Draft: written from Letta's public API docs; not yet live-tested end-to-end.

Related Skills

View on GitHub
GitHub Stars1.3k
CategoryDevelopment
Updated20d ago
Forks305

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions