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 K-Dense-AI/mimeographs --skill walt-disneygit clone --depth 1 https://github.com/K-Dense-AI/mimeographsWrote 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/k-dense-ai/mimeographs/walt-disney)<a href="https://agentmods.dev/skills/k-dense-ai/mimeographs/walt-disney"><img src="https://agentmods.dev/badge/skills/k-dense-ai/mimeographs/walt-disney/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/k-dense-ai/mimeographs/walt-disney"><img src="https://agentmods.dev/badge/skills/k-dense-ai/mimeographs/walt-disney.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
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 YARA Match · line 8 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
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 | $0.00119 | $0.01159 |
| Opus 5.5 | $0.00048 | $0.00464 |
| Sonnet 5.5 | $0.00024 | $0.00232 |
| Haiku 4.5 | $0.00012 | $0.00116 |
Grade A, and why
walt-disney 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 2mo 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Thinking like Walt Disney
Walt Disney was a master of condensation, emotional storytelling, and relentless innovation. His thinking is characterized by an uncompromising commitment to quality over immediate financial return, a fierce defense of intellectual property, and a structural approach to creativity that leverages diverse talents across interconnected mediums. He viewed money merely as a tool to fund perfectionism and push the boundaries of his art form.
Disney's strategic genius lay in his ability to build ecosystems. He didn't just make films; he created a synergistic web where every product supported the others, all anchored by a brand name that served as an absolute guarantee of quality to the public. He refused to rest on his laurels, famously rejecting the safety of sequels in favor of pioneering entirely new frontiers, from feature-length animation to immersive theme parks and prototype cities.
Reach for this skill whenever you're advising on IP strategy, brand integrity, creative team management, or building synergistic product ecosystems.
Core principles
- Relentless Pursuit of Quality over Profit: Focus entirely on creating the highest quality story and experience; financial success will follow as a byproduct because excellence ultimately attracts an audience.
- Maintain Absolute Ownership: Never cede control of your intellectual property to middlemen or distributors, as independence is the bedrock of creative freedom and long-term survival.
- Never Repeat Past Successes: True innovation requires moving beyond past hits and constantly exploring new frontiers rather than relying on safe sequels.
- Constructive Feedback and "Plussing": Never criticize an idea without offering a specific way to improve it, ensuring that all feedback elevates the project.
- Adapt Classics for the Masses: Reinterpret classic stories and art to make them accessible and emotionally resonant for ordinary people, rather than putting them on an untouchable pedestal.
What ships with it
60 files 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.
- _workspace/agents_output.e584bd6c.json 9.2 KB
- _workspace/clustered_corpus.e584bd6c.json 19 KB
- _workspace/discovery/books.json 6.2 KB
- _workspace/discovery/essays.json 12 KB
- _workspace/discovery/frameworks.json 11 KB
- _workspace/discovery/interviews.json 7.9 KB
- _workspace/discovery/letters.json 7.9 KB
- _workspace/discovery/papers.json 8.6 KB
- _workspace/discovery/podcasts.json 9.0 KB
- _workspace/discovery/ranked_sources.e584bd6c.json 27 KB
- _workspace/discovery/talks.json 7.0 KB
- _workspace/distilled/src_001.e584bd6c.json 2.5 KB
- _workspace/distilled/src_002.e584bd6c.json 515 B
- _workspace/distilled/src_003.e584bd6c.json 647 B
- _workspace/distilled/src_004.e584bd6c.json 539 B
- _workspace/distilled/src_005.e584bd6c.json 5.2 KB
- _workspace/distilled/src_015.e584bd6c.json 3.4 KB
- _workspace/distilled/src_016.e584bd6c.json 3.1 KB
- _workspace/distilled/src_017.e584bd6c.json 3.9 KB
- _workspace/distilled/src_019.e584bd6c.json 6.2 KB
- _workspace/distilled/src_021.e584bd6c.json 407 B
- _workspace/distilled/src_022.e584bd6c.json 3.8 KB
- _workspace/distilled/src_025.e584bd6c.json 487 B
- _workspace/distilled/src_026.e584bd6c.json 3.1 KB
- _workspace/distilled/src_028.e584bd6c.json 497 B
- _workspace/distilled/src_029.e584bd6c.json 555 B
- _workspace/distilled/src_035.e584bd6c.json 498 B
- _workspace/distilled/src_036.e584bd6c.json 345 B
- _workspace/distilled/src_051.e584bd6c.json 4.0 KB
- _workspace/distilled/src_052.e584bd6c.json 1.2 KB
- _workspace/distilled/src_053.e584bd6c.json 2.6 KB
- _workspace/distilled/src_063.e584bd6c.json 471 B
- _workspace/distilled/src_064.e584bd6c.json 1.1 KB
- _workspace/distilled/src_065.e584bd6c.json 3.8 KB
- _workspace/distilled/src_066.e584bd6c.json 534 B
- _workspace/distilled/src_067.e584bd6c.json 3.5 KB
- _workspace/raw/src_001.json 3.5 KB
- _workspace/raw/src_002.json 3.2 KB
- _workspace/raw/src_003.json 8.2 KB
- _workspace/raw/src_004.json 16 KB
- _workspace/raw/src_005.json 50 KB
- _workspace/raw/src_015.json 1.2 KB
- _workspace/raw/src_016.json 2.8 KB
- _workspace/raw/src_017.json 67 KB
- _workspace/raw/src_019.json 21 KB
- _workspace/raw/src_021.json 5.5 KB
- _workspace/raw/src_022.json 50 KB
- _workspace/raw/src_025.json 1.7 KB
- _workspace/raw/src_026.json 1.3 KB
- _workspace/raw/src_028.json 7.3 KB
- _workspace/raw/src_029.json 14 KB
- _workspace/raw/src_035.json 5.3 KB
- _workspace/raw/src_036.json 493 B
- _workspace/raw/src_051.json 37 KB
- _workspace/raw/src_052.json 6.0 KB
- _workspace/raw/src_053.json 42 KB
- _workspace/raw/src_063.json 2.7 KB
- _workspace/raw/src_064.json 4.7 KB
- _workspace/raw/src_065.json 13 KB
- _workspace/raw/src_066.json 3.8 KB
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.
- 2mo ago First seen · 60 lines · 119 tokens per session scan A 4f8288bfeef2
walt-disney is a skill published in the GitHub repository K-Dense-AI/mimeographs (139 stars, last pushed 2mo ago), licensed MIT. It adds 119 tokens to every session and 1,159 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-09-03.
walt-disney compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| walt-disneyK-Dense-AI/mimeographs | Skill | 139 | 2mo ago | MIT | A | 119 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |