De la autor
Ranked content search over a text corpus you point it at, using BM25 (via xhluca/bm25s). Corpus-agnostic: cloned repos, project knowledge stores, uploaded files and archives, any local directory. In-memory BM25 index per invocation, with a session-local disk cache for repeat runs against the same corpus. Use for "rank these documents", "search this corpus", "which files are most about X", "find content about Y", or any multi-word concept query against a known body of text where grep would return everything or nothing. Needs a corpus on disk. Not for searching stored memories or prior-session decisions (remembering), not for a named symbol or a file's structure (tree-sitting), and not for a literal string you could grep.
Instalare
npx skills add oaustegard/claude-skills --skill bm25 -a claude-code
Se instalează în .claude/skills/bm25/ · 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
- Include scripturi pe care nu le-am verificatScăzut
De ce 78
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.
- wiki-retrieveAgriciDaniel/claude-obsidianBuild and query a vault-local contextual BM25 retrieval index with optional multilingual Nomic cosine reranking; use for retrieve, hybrid retrieval, BM25, rerank, contextual retrieval, chunk search, vault search, semantic search, find relevant passages, or retrieval diagnostics. Derived caches stay under .vault-meta, remote egress requires explicit consent, and unavailable reranking falls back deterministically.Altele★ 15.8K
- creating-kboaustegard/claude-skillsBuilds a portable, embedding-free knowledgebase from a set of files and delivers it as a self-contained `.skill` bundle (BM25 index + bundled searcher + query protocol). Use when a user wants to turn uploaded files, a folder, or a corpus into a searchable knowledgebase they can hand to any agent — phrased as "make a knowledgebase", "build a KB skill", "package these docs for retrieval", "create a searchable bundle", or references to a `.skill` KB. The output runs anywhere with Node or Python — no model, no install, no network. Distinct from `bm25` (ephemeral in-session search) and `building-github-index` (markdown project-knowledge index).Inginerie★ 154
- wiki-queryAr9av/obsidian-wikiSearch and synthesize answers from the compiled Obsidian wiki, including cited and multi-hop answers. Use for questions about existing wiki knowledge or fast index-only lookups, and for challenge requests ("challenge this", "argue against X", "poke holes in my plan") that look for the vault's own evidence against a plan. Supports named-vault routing such as wiki-query @work; not for ingesting new sources.Planificare★ 3.6K
- knowledge-base-managementchubbyguan/chubbyskills管理本地 Markdown/Obsidian 知识库：素材入库、健康检查、增量索引、关键词与 semantic-lite 检索、逐字原文资料包、归档和 MCP 连接。用于搜索知识库、整理资料及为 Agent 准备可定位的引用。Productivitate★ 1.3K
- embeddings-searchericrisco/rsc-harnessUse when choosing an embedding model, chunk size, or query form, when semantic search returns irrelevant results, when adding hybrid BM25+vector or a reranker, or when a retrieval change needs a number (recall@k, nDCG, MRR). NOT operating the store — index tuning, quantization (that is `vector-db`) — nor the retrieve-to-answer loop (that is `rag`).Altele★ 255
- context-retrievalseb1n/awesome-ai-agent-skillsRetrieve relevant information from a knowledge base using semantic, keyword, or hybrid search to ground a query. Use when the task starts with a corpus or index that must be searched; use context-ranking when candidate chunks already exist and only need ordering.Productivitate★ 228
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