بنقرة واحدة
document-search
Hybrid vector + full-text search across the document store with hierarchical context.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Hybrid vector + full-text search across the document store with hierarchical context.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Generate a Word document from ingested source documents using the agnostic Document tree (CommonMark/Pandoc-aligned)
Generate a single Document (Word/PowerPoint) from all source documents in a collection, with attributions back to each source
Generate a PDF from ingested source documents using the agnostic Document tree
Generate a PowerPoint deck from ingested source documents using the agnostic Document tree (parametrised by slide_count, style, audience, tone)
Generate an Excel workbook (.xlsx) from ingested source documents — tabular with charts, formulas, KPI cells
Find PII (emails, phones, SSN, credit cards, IBANs, names, addresses, DOB) in an ingested document; return redaction plan
| name | document-search |
| description | Hybrid vector + full-text search across the document store with hierarchical context. |
| inputs | [{"name":"query","type":"string","required":true,"description":"Natural-language question or keywords to search for."},{"name":"top_k","type":"integer","required":false,"description":"Maximum number of chunks to return. Defaults to 8."},{"name":"collection_id","type":"string","required":false,"description":"Optional collection scope."}] |
| outputs | [{"name":"results","type":"array","description":"Ranked list of {chunk_id, document_id, document_title, chapter_title, section_title, score, snippet}."}] |
| tools | ["vector-search","db-query"] |
Pick this skill when the user asks a semantic question that may be answered by indexed
content. Prefer it over document-extract for retrieval; prefer it over document-summarize
when the user wants citations rather than a synthesis.
Document.summary and Document.topics to shortlist candidate documents.Chunk.embedding column via vector-search.Chapter.title and Section.title via db-query.collection_id scoping if provided.Emits no ExecutionHistory rows (read-only). Each call may still produce a structured log line for observability.