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 event4u-app/agent-config --skill logo-generationgit clone --depth 1 https://github.com/event4u-app/agent-configWrote 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/event4u-app/agent-config/logo-generation)<a href="https://agentmods.dev/skills/event4u-app/agent-config/logo-generation"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/logo-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.
<a href="https://agentmods.dev/skills/event4u-app/agent-config/logo-generation"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/logo-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00040 | $0.01153 |
| Opus 5 | $0.00020 | $0.00576 |
| Sonnet 5 | $0.00008 | $0.00231 |
| Haiku 4.5 | $0.00004 | $0.00115 |
Grade A, and why
logo-generation scanned grade A with 0 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 8d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
logo-generation
Generate a logo or brand mark end-to-end: capture the brand brief, choose raster
vs. true-vector path, inject brand tokens when available, route to the right
provider, author a provider-specific prompt, dry-run the adapter, and apply rights
governance. All adapters are scaffold-tier (dry-run) until promoted to stable.
When to use
- User asks to generate, create, or design a logo or brand mark.
- End-to-end logo production (path selection + routing + prompting + governance).
- When a simple geometric mark can be authored directly as SVG without a raster model.
Procedure
- Capture the brand brief — extract: business name, style intent (wordmark / icon mark / combination), colour palette, do/don't constraints (e.g. "no gradients", "must be legible at 16 px").
- Choose the path — raster concept (text-in-mark → Ideogram for legible type)
vs. true vector (vector-native provider emitting
<path>SVG for editable marks, or LLM-authored SVG for simple geometric marks). Raster output is a concept only — not a shippable logo asset. - Inject brand tokens when a brand layer is present (
pack-brand) — pull the registered palette, typeface, and spacing tokens. When no brand layer exists, use the brief's palette and type choices directly. - Route + prompt via
image-provider-routingandprompt-engineering-image— apply provider-specific grammar (text-literal first for Ideogram,style: vectorparam for a vector-native provider, direct SVG authoring for simple geometric shapes). - Dry-run + validate — invoke the adapter (scaffold-tier; returns a dry-run
plan). If the vector path is taken, validate that the output contains
<path>elements before treating it as an editable mark. - Rights check — never reproduce a mark that resembles an existing trademarked
logo. Run
image-likeness-and-rightswhen the brief names a brand, references a known mark style, or targets a regulated sector.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 102 lines · 40 tokens per session scan A af09a41e0e2b
logo-generation is a skill published in the GitHub repository event4u-app/agent-config (10 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 1,153 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.
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