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 AuraVixStudio/caelo --skill best-of-ngit clone --depth 1 https://github.com/AuraVixStudio/caeloWrote 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/auravixstudio/caelo/best-of-n)<a href="https://agentmods.dev/skills/auravixstudio/caelo/best-of-n"><img src="https://agentmods.dev/badge/skills/auravixstudio/caelo/best-of-n/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/auravixstudio/caelo/best-of-n"><img src="https://agentmods.dev/badge/skills/auravixstudio/caelo/best-of-n.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 | $0.00023 | $0.00340 |
| Opus 5 | $0.00012 | $0.00170 |
| Sonnet 5 | $0.00005 | $0.00068 |
| Haiku 4.5 | $0.00002 | $0.00034 |
Grade A, and why
Best of N (parallel attempts) 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
Best of N (parallel attempts)
Use this when a task has a wide solution space and you want the strongest result: run N independent attempts in parallel and choose the best. Each attempt is isolated, so they cannot interfere with each other.
Steps
- Pick N. Default N = 3 (cap to the parallelism limit). For a code task use the
implementerrole; for analysis/design useresearcherordesign-doc-writer. - Fan out.
delegateN subagents with the same task in a singledelegatecall so they run in parallel. Give each identical, complete instructions. - Compare. When the summaries return, evaluate each against the goal and the acceptance criteria (correctness, simplicity, completeness, risk).
- Choose. Pick the best attempt. The others' isolated copies are simply rejected at merge time (not applied).
- Summarize. State which attempt you chose and why, and what is staged for merge.
Notes
- The attempts are blind to each other — that is the point (diversity).
- Vary the instruction slightly per attempt only if you want different angles; otherwise keep them identical for a fair comparison.
- Only the chosen attempt's changes should be merged; explicitly discard the rest.
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 · 31 lines · 23 tokens per session scan A d199e56c3cd8
Best of N (parallel attempts) is a skill published in the GitHub repository AuraVixStudio/caelo (25 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 23 tokens to every session and 340 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.
Other skills, from other repositories
skill-creator
A guide for creating and maintaining skills for Lfcode, including where to store them and which files each skill needs.
tavern-management
Use when the user asks to import or translate an Lfcode Tavern or SillyTavern character card or worldbook, including PNG image cards, or manage the Tavern plugin lifecycle.
error-collection
A structured record of confirmed engineering mistakes, their root causes, and checks that prevent them from returning. It uses evidence from real application behavior, not just successful builds.
playwright-browser
Use when controlling browser pages with Playwright MCP in Lfcode; guides navigation, screenshots, interaction, and reuse of hidden or collapsed embedded side browser targets instead of the Electron app shell.
e2e-test-engineer
Use when the user asks to create, improve, review, or repair end-to-end tests for a meaningful user workflow across the UI, runtime, backend, or installed application. Validate the real workflow at the highest useful boundary while keeping environments, accounts, and test data controlled.
flaky-test-triage
Use when a test passes and fails intermittently, behaves differently by order, machine, runtime, timing, or retry, or when the user asks to reduce test flakiness. Gather repeatable evidence, isolate nondeterminism, and repair the causal dependency without weakening test intent.