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 SpartanLabsXyz/simmer-sdk --skill backtest-demo-favoritesgit clone --depth 1 https://github.com/SpartanLabsXyz/simmer-sdkWrote 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/spartanlabsxyz/simmer-sdk/backtest-demo-favorites)<a href="https://agentmods.dev/skills/spartanlabsxyz/simmer-sdk/backtest-demo-favorites"><img src="https://agentmods.dev/badge/skills/spartanlabsxyz/simmer-sdk/backtest-demo-favorites/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/spartanlabsxyz/simmer-sdk/backtest-demo-favorites"><img src="https://agentmods.dev/badge/skills/spartanlabsxyz/simmer-sdk/backtest-demo-favorites.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 | $0.00034 | $0.00239 |
| Opus 5 | $0.00017 | $0.00120 |
| Sonnet 5 | $0.00007 | $0.00048 |
| Haiku 4.5 | $0.00003 | $0.00024 |
Grade A, and why
backtest-demo-favorites 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.
What it actually says
Backtest demo — favorites buyer
This is not a real trading strategy. It exists so simmer backtest --demo
produces a meaningful report (decisions, trades, settlements, hit_rate, pnl,
baselines) with no network access and no tape download.
Each tick it buys a small fixed amount of YES on the most liquid markets trading as favorites (YES price in a mid-to-high band), skipping anything it already holds. Run against the bundled 10-market demo slice, a handful of those favorites resolve YES (wins) and a handful resolve NO (losses), so the demo shows a realistic mixed outcome rather than "0 trades, stayed flat".
Entrypoint: favorites_demo.py (reads SIMMER_API_URL / SIMMER_API_KEY from
the replay harness; accepts and ignores --live / --quiet).
What ships with it
1 file 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.
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 · 22 lines · 34 tokens per session scan A 29760c0bf7fc
backtest-demo-favorites is a skill published in the GitHub repository SpartanLabsXyz/simmer-sdk (48 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 239 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
moonpay-scout
Prediction market arbitrage & alpha scout. Searches Polymarket and Kalshi for the same event, runs cross-platform arb math (including fees), and ranks opportunities by profitability. Use when asked to "find arb", "scout markets", "find edge", or scan a specific topic across prediction markets.
find-fade-setup
Find and evaluate a fade (mean-reversion) setup on prediction markets with oddsrail: candidates, overshoot signal, book, walked cost, resolution criteria, Kelly size, dry-run order.
check-cross-venue-edge
Decide whether a Polymarket vs Kalshi price difference is a real edge or a settlement mismatch: comparevenues, settlementaudit, quotecost on both legs, resolution criteria.
daily-review
Daily review of open prediction-market exposure with oddsrail: positions, resting orders, fills, markets closing soon, builder attribution.
settle-resolved
Turn resolved and hedged Polymarket positions back into USDC, gasless, through the operator's relayer key, with a dry-run read-back first.
polymarket
Query Polymarket: markets, prices, orderbooks, history.