image-generation

image-generation is a skill for Claude Code, Codex from letta-ai/letta-code. It costs 47 tokens per session (1,353 once invoked), scanned A, original, Apache-2.0.

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

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create illustrations, logos, icons, diagrams, photos, and other raster image assets.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/letta-ai/letta-code/image-generation
About the project

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.

letta-ai/letta-code · 3,625 stars · on GitHub · letta.com

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.

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.

Wrote 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.

agentmods badge for image-generation

README.md
[![agentmods](https://agentmods.dev/badge/skills/letta-ai/letta-code/image-generation/github.svg)](https://agentmods.dev/skills/letta-ai/letta-code/image-generation)
Your own site
<a href="https://agentmods.dev/skills/letta-ai/letta-code/image-generation"><img src="https://agentmods.dev/badge/skills/letta-ai/letta-code/image-generation/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.

agentmods 80×15 button for image-generation

Your own site · 80×15
<a href="https://agentmods.dev/skills/letta-ai/letta-code/image-generation"><img src="https://agentmods.dev/badge/skills/letta-ai/letta-code/image-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,353 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

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 →

  • medium Data Exfiltration · line 19
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
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 5.1 $0.00047 $0.01353
Opus 5.5 $0.00019 $0.00541
Sonnet 5.5 $0.00009 $0.00271
Haiku 4.5 $0.00005 $0.00135

Measured 1mo ago against content hash a4f201d9a874, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, 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 1mo 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.

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 · 126 lines

How it starts

The opening of the file, as written. The whole thing — 126 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")
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. Keep credit amounts and billing metadata out of user-facing replies and captions unless the user asks about cost. When asked, read billing.credits_charged from the saved response.

Read the full file on GitHub · 126 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. 1mo ago Changed · +1 lines a4f201d9a874
  2. 1mo ago 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 (3,625 stars, last pushed today), licensed Apache-2.0. It adds 47 tokens to every session and 1,353 once invoked, about $0.0002 per session on Opus 5.5. 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.

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