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 acquiring-skillsgit 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/acquiring-skills)<a href="https://agentmods.dev/skills/letta-ai/letta-code/acquiring-skills"><img src="https://agentmods.dev/badge/skills/letta-ai/letta-code/acquiring-skills/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/acquiring-skills"><img src="https://agentmods.dev/badge/skills/letta-ai/letta-code/acquiring-skills.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 114 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- high Tool Misuse · line 240 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- high Tool Misuse · line 114 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- high Tool Misuse · line 240 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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 | $0.00061 | $0.03144 |
| Opus 5 | $0.00030 | $0.01572 |
| Sonnet 5 | $0.00012 | $0.00629 |
| Haiku 4.5 | $0.00006 | $0.00314 |
Grade C, and why
acquiring-skills scanned grade C 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 10d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf /tmp/hermes-browse Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "https://clawhub.ai/api/v1/skills?q=calendar" | jq '.items[].slug' How it starts
The opening of the file, as written. The whole thing — 280 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Acquiring New Skills
This skill teaches you how to safely discover and install skills from external sources, including the Hermes Skills Hub, ClawHub (OpenClaw), GitHub repositories, and Letta community repos.
SAFETY - READ THIS FIRST
Skills can contain:
- Markdown files (.md) - Risk: prompt injection, misleading instructions
- Scripts (Python, TypeScript, Bash) - Risk: malicious code execution
Trusted Sources (no user approval needed for download)
https://github.com/letta-ai/skills- Letta's community skillshttps://github.com/anthropics/skills- Anthropic's official skillsofficial/*- Hermes official optional skills (fromNousResearch/hermes-agent)
Untrusted Sources (ALWAYS verify with user)
For ANY source other than the above:
- Ask the user before downloading
- Explain where the skill comes from
- Get explicit approval
This includes ClawHub community skills and arbitrary GitHub repos.
Script Safety
Even for skills from trusted sources, ALWAYS:
- Read and inspect any scripts before executing them
- Understand what the script does
- Be wary of network calls, file operations, or system commands
Cross-Harness Compatibility
Skills from Hermes, OpenClaw, and other ecosystems were written for their own harnesses. After installing, read the full SKILL.md before using it and watch for:
- Harness-specific commands — e.g.
hermes skills config,openclaw plugins install,/curator,/kanban. These won't exist in Letta. Determine whether the underlying capability can be achieved with Letta tools (Bash, the Skill tool, etc.) or if the skill simply doesn't apply. - Harness-specific paths and state — e.g.
~/.hermes/skills/,~/.openclaw/skills/,~/.hermes/config.yaml. Letta stores skills in the agent's memfs (<memory-dir>/skills/). Adapt any path references. - Toolset assumptions — some skills assume specific tool names or APIs (e.g. Hermes
webtoolset, OpenClawbrowsertool). Map these to the equivalent Letta tools or note when no equivalent exists. - Platform gating — skills may declare
platforms: [cli, discord, telegram]in frontmatter. Ignore platform restrictions that don't apply to Letta. - Environment variables — skills may require API keys or credentials. Check
requires.envin frontmatter and note any setup the user needs to do.
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.
- 10d ago First seen · 280 lines · 61 tokens per session scan C 717f2d432914
acquiring-skills is a skill published in the GitHub repository letta-ai/letta-code (3,241 stars, last pushed today), licensed Apache-2.0. It adds 61 tokens to every session and 3,144 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 2 findings (recursive force delete, 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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