image-generation

An image-making tool that creates pictures from written prompts and can optionally edit or remix an input image. It saves the resulting image locally for use in a project.

In plain words
What is it for?
Use it to create illustrations, logos, icons, diagrams, photos, and other raster image assets.
Why use it?
It removes the need to draw or source every visual by hand when a prompt can describe the desired result.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/letta-ai/letta-code/image-generation
Any agent
npx skills add letta-ai/letta-code --skill image-generation
Clone the repo
git clone --depth 1 https://github.com/letta-ai/letta-code

Made for: Claude Code, Codex.

Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,347 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00047 $0.01347
Opus 5 $0.00023 $0.00674
Sonnet 5 $0.00009 $0.00269
Haiku 4.5 $0.00005 $0.00135

Measured yesterday against content hash 76e394e5f1b2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

image-generation scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -sS -X POST "$base_url/v1/images/generations" \
src/skills/builtin/image-generation/SKILL.md · 125 lines

How it starts

The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Image Generation

Generate images via Letta's hosted endpoint POST /v1/images/generations. The API usually returns base64 image bytes, but some providers return signed image URLs; save either form to a local image file before replying.

Example

Generate the image, save it locally, then show it inline:

base_url="${LETTA_BASE_URL%/}"

curl -sS -X POST "$base_url/v1/images/generations" \
  -H "Authorization: Bearer $LETTA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"provider":"gemini","prompt":"a friendly robot mascot waving, flat vector logo, mint green background","n":1}' \
  > image-response.json

python3 - <<'PY'
import base64, json, urllib.request

with open("image-response.json") as f:
    response = json.load(f)

image = response["images"][0]
if image.get("b64_json"):
    data = base64.b64decode(image["b64_json"])
else:
    data = urllib.request.urlopen(image["url"]).read()

with open("robot-mascot.png", "wb") as f:
    f.write(data)

print("saved robot-mascot.png; credits:", response["billing"]["credits_charged"])
PY

In Bash tools launched by Letta Code, use the runtime-provided LETTA_BASE_URL and LETTA_API_KEY together for Letta API calls. Build URLs relative to ${LETTA_BASE_URL%/} and send Authorization: Bearer $LETTA_API_KEY. Do not hardcode https://api.letta.com: Desktop and remote runtimes may provide a proxy base URL, and the credential may only be valid through that URL. If either variable is missing, the user needs to authenticate with Letta Cloud (or provide a Letta API key); do not ask for an OpenAI/Gemini provider key. This endpoint also does not use /connect BYOK providers — the only provider values supported here are flux, gemini, and openai.

Then show the image to the user by embedding the saved file in your reply:

Here's the mascot:

![a friendly robot mascot waving, flat vector logo](./robot-mascot.png)

The Letta Code UI renders local file paths in markdown image tags, so the image appears inline. Always display generated images this way — don't just report the path, and never paste the raw base64 / a data: URI. The markdown path must match where you saved the file. For n > 1, save each image to its own file and embed each on its own line. Also tell the user the credits_charged.

Read the full file on GitHub · 125 lines

Changes

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.

  1. yesterday First seen · 125 lines · 47 tokens per session scan A 76e394e5f1b2

Subscribe to this mod's changes

image-generation is a skill published in the GitHub repository letta-ai/letta-code (3,156 stars, last pushed 2d ago), licensed Apache-2.0. It adds 47 tokens to every session and 1,347 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.