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 RiggdAI/uniqent --skill cost-optimizegit clone --depth 1 https://github.com/RiggdAI/uniqentWrote 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/riggdai/uniqent/cost-optimize)<a href="https://agentmods.dev/skills/riggdai/uniqent/cost-optimize"><img src="https://agentmods.dev/badge/skills/riggdai/uniqent/cost-optimize/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/riggdai/uniqent/cost-optimize"><img src="https://agentmods.dev/badge/skills/riggdai/uniqent/cost-optimize.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 | $0.00024 | $0.00274 |
| Opus 5.5 | $0.00010 | $0.00110 |
| Sonnet 5.5 | $0.00005 | $0.00055 |
| Haiku 4.5 | $0.00002 | $0.00027 |
Grade A, and why
cost-optimize 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.
What it actually says
Cost Optimize
When asked to optimize a menu for food cost:
- Identify over-budget dishes. List every dish whose ingredient cost exceeds the target % (default 30%). Sort by cost descending — tackle the worst offenders first.
- Propose concrete swaps. For each over-budget dish suggest one or two specific ingredient swaps with the expected cost saving (e.g. "replace salmon with ocean trout: saves ~22% on protein cost"). Preserve the dish's flavour profile and presentation quality.
- Check seasonal alternatives. Fetch current seasonal produce prices if available; seasonal substitutes are the first port of call before changing the dish concept.
- Re-run the numbers. After each proposed swap, recalculate the dish food-cost % and the blended menu food-cost % to confirm the target is met.
- Flag quality risks. If a swap materially changes texture, flavour, or presentation, note it explicitly so the operator can decide whether the trade-off is acceptable.
- Summarise changes in a before/after table: dish name | original cost % | new cost % | swap made.
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 · 22 lines · 24 tokens per session scan A 31701303f236
cost-optimize is a skill published in the GitHub repository RiggdAI/uniqent (15 stars, last pushed 8d ago), licensed Apache-2.0. It adds 24 tokens to every session and 274 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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