「llm」の検索結果

Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).

日本語の概要は準備中です。原文の説明を表示しています。

Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.

日本語の概要は準備中です。原文の説明を表示しています。

Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration

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Design production-grade multi-agent workflows with clear pattern choice (sequential, parallel, hierarchical), handoff contracts, failure handling, and cost/context controls. Use when architecting a multi-step agent pipeline, choosing between single-agent vs multi-agent approaches, or refactoring an LLM workflow that suffers from context bloat or unreliable handoffs.

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Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.

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6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

日本語の概要は準備中です。原文の説明を表示しています。

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

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Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

日本語の概要は準備中です。原文の説明を表示しています。

Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.

日本語の概要は準備中です。原文の説明を表示しています。

Fetch any X/Twitter post as clean LLM-friendly JSON. Converts x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics. No scraping or browser required.

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This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

日本語の概要は準備中です。原文の説明を表示しています。

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks

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Adds Wasp knowledge, LLM-friendly documentation fetching instructions, and best practices to your project's CLAUDE.md or AGENTS.md file

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上线前 PR 审查。分析当前分支与基础分支的 diff，检查 SQL 安全、竞态条件、 LLM 信任边界、枚举完整性等测试捕获不到的结构性问题。发现问题直接修复。 触发方式：用户说"review"、"审查代码"、"上线前检查"、"forge-review"，或 forge-dev --full 调度。 与内置 code-review/verify 的分工：forge 工作流内的上线前结构性审查用本 skill；用户点名 /code-review 或 /verify 时用对应内置 skill。

日本語の概要は準備中です。原文の説明を表示しています。

How to test the peoplereadme CLI end-to-end, including the fidelity harness (eval/calibrate) with a synthetic persona fixture and live LLM calls.

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Post-train LLMs with PrimeIntellect's prime-rl (async RL, SFT, distillation, evals). Use this skill whenever the user mentions prime-rl, wants to write an rl.toml or sft.toml, run `uv run rl` / `uv run sft` / `uv run eval` / `uv run inference`, pick GRPO, MaxRL, OPD or ECHO, tune IPO loss, or monitor and resume a run. Also trigger for verifiers environments, Prime Intellect post-training, reverse-text, and pydantic-config TOML overrides.

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Build GenAI and agentic apps with genai-tk (tclatos/genai-tk), a YAML-driven IoC toolkit over LangChain, DeepAgents, DeerFlow, and Prefect. Use this skill whenever the user mentions genai-tk, genai_tk, `cli init`, `cli agents run`, `LangchainAgent`, `create_harness`, `get_llm`, `global_config()`, `model_id@provider`, `agents:`/`agent_defaults:` profiles, `RetrieverFactory`, `cli workflow`, or BAML extraction. Also trigger for app_conf.yaml, GENAITK_PROFILE, CodeAct, OpenSandbox, decision models, or "the toolkit".

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Expert-level optimization knowledge. Use when working with linear programming, convex optimization, nonlinear programming, integer programming, dynamic programming, gradient methods, duality theory, or optimization algorithms. Also use when the user mentions 'linear programming', 'simplex method', 'convex optimization', 'Lagrangian', 'KKT conditions', 'gradient descent', 'Newton method', 'integer programming', 'dynamic programming', 'duality', 'Bellman equation', or 'branch and bound'.

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Use when writing, debugging, or configuring an omp hook or extension — blocking or rewriting tool calls, redacting tool output, reshaping LLM context, registering tools/commands, or wiring modules through config.yml. Covers ExtensionAPI (current) vs HookAPI (legacy), the event catalog, discovery and load order, and disable controls. Not for Claude Code hooks (~/.claude/settings.json) or the shared harness safety guard (~/.agents/harness/hooks/).

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Build AI-powered software with TypeSafe: small units of AI intelligence you can use like programming primitives. Its System One models, including Jev, turn natural language and application state into typed judgments and probabilities that code can combine. Use when a feature needs programmable common sense, when brainstorming what AI could make possible in an app, or when an LLM prompt-and-parse step could become a structured decision. Applications include routing, ranking, extraction, verification, and interactive experiences; these are starting points, not the limits. Read live docs and cookbooks to find useful patterns and discover new combinations.

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Run an infrastructure-first security audit of a repository - secrets archaeology, dependency supply chain, CI/CD pipeline, LLM/AI attack surface, agent skill supply chain, OWASP Top 10, STRIDE threat model, and data classification - with a confidence gate and a pre-emit verification gate that suppress speculative findings. Use when asked for a security audit, threat model, pentest-style review, OWASP pass, or a pre-release security check. Not for reviewing a single diff - use requesting-code-review for that.

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Calcule la vélocité des sprints terminés (Σ points des tickets feuilles livrés) et recommande la capacité du prochain sprint. À lancer en fin de sprint. Thin wrapper bash sur sprint_velocity.sh, zéro LLM lourd. Usage: /velocity [<titre-sprint>]

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Dashboard d'avancement des epics en cours. Thin wrapper sur les scripts bash qui agrègent les logs per-agent (.claude/state/epic_run/) et le state GitHub. Pas de LLM lourd. Usage: /report [<epic_N> ...]

日本語の概要は準備中です。原文の説明を表示しています。