arena
De la autor
Spawn N parallel candidates at the same task, pick a base, graft the strongest parts of the losers into it. Use for /arena, 'arena this', 'throw it in the arena', or when one attempt at a non-trivial artifact would lock in the wrong shape.
Instalare
npx skills add backnotprop/pstack --skill arena -a claude-code
Se instalează în .claude/skills/arena/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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Verificări de siguranță pe SKILL.md
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De ce 90
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- swarmbacknotprop/pstackFan out N parallel workers, drain them, and return one report. Use for /swarm, 'swarm this', or parallel coverage, races, gauntlets, and exploration.Altele★ 3K
- spawnalirezarezvani/claude-skillsLaunch N parallel subagents in isolated git worktrees to compete on the session task. Use when the user runs /hub:spawn or asks to start the competing agents for an initialized AgentHub session.Inginerie★ 28.9K
- agni-kaitmcfarlane/team-avatarZuko's Agni Kai for bakeoffs. The formal firebending duel, where competing implementations fight under the same rules and a judge declares the winner. Use for arena, /arena, "arena this", "throw it in the arena", "bakeoff", or when one attempt at a nontrivial design or artifact would lock in the wrong shape. Spawns N parallel candidates at the same task, picks a base with a cross-judge, and grafts the strongest parts of the losers into it.Design★ 111
- 01-auto-arenaagentscope-ai/OpenJudgeAutomatically evaluate and compare multiple AI models or agents without pre-existing test data. Generates test queries from a task description, collects responses from all target endpoints, auto-generates evaluation rubrics, runs pairwise comparisons via a judge model, and produces win-rate rankings with reports and charts. Supports checkpoint resume, incremental endpoint addition, and judge model hot-swap. Use when the user asks to compare, benchmark, or rank multiple models or agents on a custom task, or run an arena-style evaluation.Testare★ 938
- parallelhashgraph-online/awesome-codex-pluginsBuild a planned game with several agents at once — game logic and netcode, levels, art, sound, the landing page — each in its own folders, then one merge, a two-browser check, a playtest and a blind review. Use only when parallel work is requested and the host supports it. Use after the plan step, or when someone asks to "build it in parallel", "use more agents", "split the work" or "go faster".Design★ 1.4K
- 00-arena-routeragentscope-ai/OpenJudgeUse when the user wants to compare or benchmark multiple LLMs/agents arena-style but it's unclear which specific workflow fits — a general-purpose win-rate comparison on a custom task, or a benchmark specifically about reference/citation hallucination rate. Also use when the user mentions model arena, agent arena, pairwise model comparison, win-rate ranking, or comparing models on a task and hasn't specified whether that task is generic or about citation accuracy. This skill is the entry router for the arena-eval suite: it asks one diagnostic question when needed, then recommends the workflow or workflows needed to cover the request.Planificare★ 938
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