audio-mix-maker
Mix music/audio onto an existing video via ffmpeg. Modes: replace, overlay, duck (sidechain compressor lowers music under…
Brand mark / wordmark / logo generator. Default ideogram-3-quality for clean embedded text (gpt-image-2 fallback). Six presets: wordmark, minimal, illustrated, typographic, geometric, emblem. Optional palette hint. N variants per call. Use when: 'logo', 'brand mark', 'wordmark',
Claude Code
$ npx -y skills add Mikefluff/skills --skill logo-maker --agent claude-code
Codex
$ npx skills add Mikefluff/skills --skill logo-maker -a codex -y
Cursor
$ npx skills add Mikefluff/skills --skill logo-maker -a cursor -y
Gemini CLI
$ npx skills add Mikefluff/skills --skill logo-maker -a gemini-cli -y
GitHub Copilot
$ npx skills add Mikefluff/skills --skill logo-maker -a github-copilot -y
OpenCode
$ npx skills add Mikefluff/skills --skill logo-maker -a opencode -y
Windsurf
$ npx skills add Mikefluff/skills --skill logo-maker -a windsurf -y
name: logo-maker description: "Brand mark / wordmark / logo generator. Default ideogram-3-quality for clean embedded text (gpt-image-2 fallback). Six presets: wordmark, minimal, illustrated, typographic, geometric, emblem. Optional palette hint. N variants per call. Use when: 'logo', 'brand mark', 'wordmark', 'логотип', 'эмблема', 'фирменный знак'." license: MIT allowed-tools: - Read - Write - Edit - Bash - Grep - Glob
<objective> Logo generator. Input: brand name + optional tagline + style preset + palette hint. Output: N stochastic variants of the same brief.
Distinct from `cover-maker`:
Distinct from `flyer-maker`:
This skill does NOT:
</objective>
Read brand + style preset + palette → pick text-strong model → assemble variant prompts that strongly cue "logo isolated on white background, no shadows, vector aesthetic" → batch execute → save PNGs.
1. **Resolve brand**:
2. **Resolve style preset** — see `references/style-presets.md`:
3. **Palette hint** (optional but recommended):
4. **Pick model**:
5. **Compose ONE LLM call** — load [`common/visual-prompt-library/system-prompt.md`](../../common/visual-prompt-library/system-prompt.md) (shared SYSTEM_PROMPT) and `buildUserMessage(opts)` with `Mode=logo`, `N=<variants>`, brand + tagline + style preset + palette. Spawn ONE Agent. Receives JSON `{"slides":[{"number":1,"prompt":"..."}]}` — 1–3 sentence prompts cueing isolated-on-white, no background clutter, vector look. Brand name in double quotes. The N prompts share the same content brief but allow stochastic variation in execution (different geometric interpretations, different palette emphasis within the constraint).
6. **Estimate cost + confirm** — inherits `SKILLS_CAROUSEL_BUDGET=1.50`.
7. **Batch execute** — `common.runners.batch.run_batch()`.
8. **Output**:
./generated/logo/<slug>/
logo-v1.png
logo-v2.png
logo-v3.png (if --variants 3)
manifest.json
prompts.mdWhen `--model` is an `ideogram-4*` tier, emit the layout as structure instead of flattening it into a sentence: add `json_prompt` to each plan item's `kwargs`, following [`common/references/json-prompt.md`](../../common/references/json-prompt.md). This skill already knows where every element goes; sending that directly is what stops the arrangement drifting between variants.
On any v3 tier the provider refuses a `json_prompt` rather than ignoring it, so keep the prose prompt as written and send nothing extra.
| File | When to load | |---|---| | [references/style-presets.md](references/style-presets.md) | Step 2 — exact composition rules per preset, when to pick which, common mistakes | | [references/model-picker.md](references/model-picker.md) | Step 4 — which model handles which style best, text vs icon strengths | | [references/troubleshoot.md](references/troubleshoot.md) | When text gets garbled, icon looks generic, palette ignored |
See [examples/before-after.md](examples/before-after.md) — 3 calibration runs: SaaS wordmark, illustrated mascot, geometric emblem.
45 skills for Claude Code that make content — and refuse to let it read like a machine made it. Prose editing that strips the tells. Prompt engineering for 40+ image, video and music models, with optional one-command execution against the real APIs.
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