Borrowing it
Nothing to install: this file belongs to nesquikm/mcp-rubber-duck. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/nesquikm/mcp-rubber-duck/master/.claude/skills/update-pricing/SKILL.mdgit clone --depth 1 https://github.com/nesquikm/mcp-rubber-duckWrote 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/nesquikm/mcp-rubber-duck/update-pricing)<a href="https://agentmods.dev/skills/nesquikm/mcp-rubber-duck/update-pricing"><img src="https://agentmods.dev/badge/skills/nesquikm/mcp-rubber-duck/update-pricing/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/nesquikm/mcp-rubber-duck/update-pricing"><img src="https://agentmods.dev/badge/skills/nesquikm/mcp-rubber-duck/update-pricing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00012 | $0.00247 |
| Opus 5 | $0.00006 | $0.00123 |
| Sonnet 5 | $0.00002 | $0.00049 |
| Haiku 4.5 | $0.00001 | $0.00025 |
Grade A, and why
update-pricing 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 12d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- update-pricing — 94% identical, 1 lines differ
What it actually says
Update Pricing
Use the pricing-updater subagent to update the LLM pricing data in src/data/default-pricing.ts.
The agent should:
- Research current pricing from all provider websites (OpenAI, Anthropic, Google, Groq, Mistral, DeepSeek, Together AI)
- Discover and add models that are actually listed on pricing pages - do NOT add speculative/future models
- Update any prices that have changed
- Remove models that are no longer available or deprecated
- Update the
DEFAULT_PRICING_LAST_UPDATEDtimestamp to today's date - Run
npm run typecheckandnpm test -- tests/pricing.test.tsto verify changes
Important guidelines:
- Only add models with explicit pricing on official provider pages
- Do not invent or extrapolate pricing for unannounced models
- When uncertain about a price, skip the model rather than guess
- Cross-reference model names exactly as they appear in API documentation
$ARGUMENTS
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.
- 12d ago First seen · 26 lines · 12 tokens per session scan A 9afcd7c9c546
update-pricing is a skill published in the GitHub repository nesquikm/mcp-rubber-duck (176 stars, last pushed 2d ago), licensed MIT. It adds 12 tokens to every session and 247 once invoked, about $0.0001 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.
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