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 agentmods add skills/mcpware/logoloom/design-logonpx skills add mcpware/logoloom --skill design-logogit clone --depth 1 https://github.com/mcpware/logoloomWrote 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/mcpware/logoloom/design-logo)<a href="https://agentmods.dev/skills/mcpware/logoloom/design-logo"><img src="https://agentmods.dev/badge/skills/mcpware/logoloom/design-logo.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.02017 |
| Opus 5 | $0.00000 | $0.01009 |
| Sonnet 5 | $0.00000 | $0.00403 |
| Haiku 4.5 | $0.00000 | $0.00202 |
Grade A, and why
design-logo 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 5d 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 — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Logo
Generate a commercial-grade SVG logo for a project by reading its codebase and iterating with the user.
When to use
When the user says "design logo", "整 logo", "make a logo", "brand design", or wants a visual identity for a project/org.
Workflow
Phase 1: Understand the Brand
-
Read the project's codebase to understand identity:
# If it's a GitHub org ~/.local/bin/gh api orgs/{org} --jq '{name, description}' ~/.local/bin/gh repo list {org} --json name,description --limit 20 # If it's a single repo cat README.md | head -50 cat package.json | grep -E '"name"|"description"|"keywords"' -
Ask the user 3 questions (keep it fast, don't overthink):
- Who is your target user? (developers only? general public? both?)
- What feeling? (sharp/bold? soft/friendly? minimal/clean? premium/luxury?)
- Any color preference? (warm? cool? specific color? no preference?)
Phase 2: Generate Concepts
-
Generate 6-8 SVG logo concepts with different approaches:
- Vary: icon style, color palette, typography weight, corner radius
- Always include: at least 1 geometric, 1 abstract, 1 text-heavy
- Each concept should have a different personality
-
Package ALL concepts into a single HTML preview file:
/tmp/{project}-logo-preview.htmlHTML requirements:
- Grid layout (2 columns)
- Each concept shows BOTH light and dark background preview side by side
- Concept name + 1-line description
- User opens
file:///tmp/{project}-logo-preview.htmlto compare all at once
Phase 3: Iterate
-
User picks a direction → generate 4 variations of that direction:
- Vary: stroke weight, dot size, color saturation, corner sharpness, tagline
- Show icon-only variants at different sizes (64px, 32px, 16px)
- Still package in single HTML preview (replace same file)
-
Repeat until user says "this one" or "OK"
Phase 4: Final Package
- DO NOT run text_to_path on the final SVG. Keep original
<text>elements — they render perfectly in browsers (GitHub, npm, websites). text_to_path degrades quality (wrong kerning, loses gradient fills on tspan, font mismatch). Only use text_to_path if user specifically needs print/offline use.
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.
- 5d ago First seen · 189 lines · 0 tokens per session scan A 586a118c303c
design-logo is a skill published in the GitHub repository mcpware/logoloom (35 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,017 tokens. 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 2026-08-30.
Other skills, from other repositories
chatcrystal-debug-recall
Recall ChatCrystal memories for debugging tasks involving failing tests, compiler errors, runtime exceptions, dependency issues, environment breakage, or performance regressions. Use when historical root causes, fixes, or pitfalls may accelerate diagnosis before proposing a fix.
verify
Fact-check claims encountered during reading — dates, names, events, citations. Use when encountering historical facts or disputed claims.
expert
Base expert skill.
collection
Choose which SkillNote skill collection is active for this Codex project. Use when the user says "change collection", "switch skills", "use frontend skills", or "show collections".
alpha
Alpha skill.
assistant
Assistant — on any repo, scan README→docs→AGENTS→CONTRIBUTING→PR templates→task runners→devcontainer→CI→configs before code; cite sources; prefer AGENTS.md for agent behavior; portable across Cursor/Copilot/Claude; use agent-toolkit CLI when needed.