Borrowing it
Nothing to install: this file belongs to Piebald-AI/splitrail. 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/Piebald-AI/splitrail/main/.claude/skills/pricing/SKILL.mdgit clone --depth 1 https://github.com/Piebald-AI/splitrailWrote 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/piebald-ai/splitrail/pricing)<a href="https://agentmods.dev/skills/piebald-ai/splitrail/pricing"><img src="https://agentmods.dev/badge/skills/piebald-ai/splitrail/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/piebald-ai/splitrail/pricing"><img src="https://agentmods.dev/badge/skills/piebald-ai/splitrail/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 | $0.00024 | $0.00715 |
| Opus 5.5 | $0.00010 | $0.00286 |
| Sonnet 5.5 | $0.00005 | $0.00143 |
| Haiku 4.5 | $0.00002 | $0.00072 |
Grade A, and why
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 1mo 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pricing Model Updates
Token pricing is defined in src/models.rs. Built-in models are populated by populate_defaults() into the runtime model registry, and user/config models can be merged with init_external_models().
Adding a New Model
- Add a
ModelInfoentry inpopulate_defaults()with:pricing: UsePricingStructure::Flat { input_per_1m, output_per_1m }for flat-rate models, orPricingStructure::Tieredfor threshold-based pricing.caching: Use the appropriateCachingSupportvariant (None,OpenAI,Anthropic,OpenAIWithWrites, orTiered).service_tiers: Leave empty unless the provider has distinct priority/flex/batch rates.dated_pricing: Leave empty unless pricing changes by usage date.is_estimated: Set totrueonly when pricing is not confirmed by a provider/tool source.input_token_semantics: Auto-derived for built-in models (defaults toExcludesCache); only GPT/o-series models typically needIncludesCacheRead. External model configs should set this explicitly if it affects cache-read counting.
- If the model has aliases (date suffixes, provider-prefixed names, regional names, etc.), add entries to the alias section mapping each observed name to the canonical model name.
- Add or update tests in
src/models.rsfor canonical pricing, aliases, caching, and estimated/non-estimated status.
Dated Pricing Overrides
Use dated_pricing when a model has temporary promotional pricing, launch pricing, or another time-bounded rate that should apply based on the original usage timestamp.
The default pricing and caching fields should represent the durable/current sticker price. Each DatedPricing override has a valid_until: NaiveDate exclusive end date and applies when usage_date < valid_until. For example, an introductory rate that applies through 2026-08-31 should use valid_until = NaiveDate::from_ymd_opt(2026, 9, 1).expect("valid date").
When adding a dated override:
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.
- 1mo ago First seen · 46 lines · 24 tokens per session scan A d058d17660ee
pricing is a skill published in the GitHub repository Piebald-AI/splitrail (227 stars, last pushed today), licensed MIT. It adds 24 tokens to every session and 715 once invoked, about $0.0001 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 2026-08-30.
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