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 UCSC-VLAA/VisualClaw --skill option-elimination-by-accuracygit clone --depth 1 https://github.com/UCSC-VLAA/VisualClawWrote 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/ucsc-vlaa/visualclaw/option-elimination-by-accuracy)<a href="https://agentmods.dev/skills/ucsc-vlaa/visualclaw/option-elimination-by-accuracy"><img src="https://agentmods.dev/badge/skills/ucsc-vlaa/visualclaw/option-elimination-by-accuracy/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/ucsc-vlaa/visualclaw/option-elimination-by-accuracy"><img src="https://agentmods.dev/badge/skills/ucsc-vlaa/visualclaw/option-elimination-by-accuracy.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 | $0.00033 | $0.00253 |
| Opus 5 | $0.00016 | $0.00127 |
| Sonnet 5 | $0.00007 | $0.00051 |
| Haiku 4.5 | $0.00003 | $0.00025 |
Grade A, and why
option-elimination-by-accuracy 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 10d 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.
What it actually says
Eliminate Factually Incorrect Options
- For each option, identify any claims about video content (actions, objects, relationships).
- Verify each claim against what you observe in the video:
- Is this action actually shown? (e.g., "consuming flowers" vs. "stringing flowers")
- Is this object actually present? (e.g., "vase" vs. "bag")
- Is this relationship accurate? (e.g., "conversation" vs. "playing cards")
- Eliminate any option with even one factually incorrect element.
- Among remaining options, select the most precise match.
Example: Option B says "puts them in a vase" but video shows flowers being strung. Eliminate B. Option E says "puts them on a string" — this is factually correct, so select E.
Anti-pattern: Selecting an option that sounds reasonable or well-written without verifying its factual accuracy against the actual video content. Always prioritize correctness over plausibility.
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.
- 10d ago First seen · 20 lines · 33 tokens per session scan A 1c7f35dfd2d1
option-elimination-by-accuracy is a skill published in the GitHub repository UCSC-VLAA/VisualClaw (55 stars, last pushed 2mo ago), licensed MIT. It adds 33 tokens to every session and 253 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 2026-08-30.
Other skills, from other repositories
ppt-generation
Use this skill when the user requests to generate, create, or make presentations (PPT/PPTX). Creates visually rich slides by generating images for each slide and composing them into a PowerPoint file.
image-generation
Use this skill when the user requests to generate, create, imagine, or visualize images including characters, scenes, products, or any visual content. Supports structured prompts and reference images for guided generation.
podcast-generation
Use this skill when the user requests to generate, create, or produce podcasts from text content. Converts written content into a two-host conversational podcast audio format with natural dialogue.
video-generation
Use this skill when the user requests to generate, create, or imagine videos. Supports structured prompts and reference image for guided generation.
ideation
Generate project ideas through creative constraints. Use when the user says 'I want to build something', 'give me a project idea', 'I'm bored', 'what should I make', 'inspire me', or any variant of 'I have tools but no direction'. Works for code, art, hardware, writing, tools, and anything that can be made.
youtube-full
Use when YouTube is or could be relevant — even if not mentioned: pasted video/channel/playlist links, video IDs, @handles, creator lookups, video summaries, quotes, translations, topic research, tutorials, talks, lectures, expert discussions, product reviews, how-to guides, new product announcements, first looks, or…