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internal-knowledge
Discover and retrieve from knowledge bases the current AIChat user can access.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Discover and retrieve from knowledge bases the current AIChat user can access.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Extract structured contract fields from existing contract text or already parsed contract content according to a configured field list. Use when the user asks for 合同字段抽取, 合同信息抽取, 合同关键信息提取, 合同台账, contract field extraction, contract metadata extraction, contract ledger data, or extracting parties, amount, dates, term, payment terms, renewal terms, breach clauses, or other configured contract fields. This skill does not parse uploaded files directly; it works only after contract text is available from another system or parser.
Design structured user clarification flows with the existing request_user_input capability so the assistant asks stable, focused questions with usable quick options instead of plain natural-language follow-up. Use when the user or another skill needs 问答交互, 表单交互, 结构化质询, 弹出输入框, 选项框, 单选, 多选, 补充信息, 确认参数, 文件上传提示, 表单填写, questionnaire, form interaction, structured clarification, user input, quick replies, or parameter confirmation.
Plan precise slide-by-slide PPT structures from a topic, text content, requirements, or uploaded-material summaries, and prepare a file-generator-ready PPTX payload for downstream generation. Use when the user asks for PPT planning, PowerPoint outline, slide planning, page-by-page PPT requirements, presentation storyboard, report deck structure, pitch deck outline, training deck plan, proposal slides, project report slides, business review slides, or when the user asks to first create a precise outline before generating a PPT file. This skill is the planning and layout layer, not the PPTX file generator.
Rewrite existing assistant replies, service replies, workplace messages, or explanatory answers to sound more natural, human, warm, polite, concise, professional, empathetic, and easy to understand while preserving the original facts and boundaries. Use when the user asks for 回复口吻优化, 语气优化, 改得自然一点, 去 AI 味, 减少机械感, 像正常人说话, 温和一点, 亲切一点, 礼貌一点, 客服话术优化, 办公回复优化, 心理关怀回复, 面向普通用户, polish response, rewrite tone, make it natural, make it warmer, make it less robotic, or humanize this reply.
Generate downloadable SVG and HTML technical diagrams from natural language or structured data, including system architecture, AI Agent architecture, data flow, flowchart, comparison matrix, sequence, state, and ER diagrams.
Generate downloadable SVG charts from structured data, including radar, bar, line, pie, doughnut, scatter, and score distribution charts.
| name | internal-knowledge |
| description | Discover and retrieve from knowledge bases the current AIChat user can access. |
| when_to_use | Use this skill when an internal AIChat answer needs factual context from workspace knowledge bases. |
| provider_type | builtin |
| provider_id | knowledge |
| runtime_type | tool |
| tools | ["list_accessible_knowledge_bases","retrieve_knowledge"] |
| max_calls_per_turn | 20 |
| timeout_seconds | 30 |
| display | {"icon":"library","category":"knowledge","label":{"en_US":"Internal Knowledge","zh_Hans":"内部知识库"},"description":{"en_US":"Finds knowledge bases accessible to the current AIChat user and retrieves relevant context.","zh_Hans":"查找当前 AIChat 用户可访问的知识库,并检索相关上下文。"},"when_to_use":{"en_US":"Use when an AIChat answer needs facts or source context from accessible knowledge bases.","zh_Hans":"当 AIChat 回复需要引用可访问知识库中的事实或来源上下文时使用。"},"tags":{"en_US":["Knowledge","Retrieval"],"zh_Hans":["知识库","检索"]}} |
Use this skill to answer internal AIChat questions with context from knowledge bases the current user can access.
list_accessible_knowledge_bases with a short query derived from the user's topic, business domain, or explicitly named knowledge base.status, fallback_used, and returned knowledge base names/descriptions before selecting datasets:
status is success, select only the most relevant returned dataset_id values.status is fallback, treat the candidates as weak matches. Select a dataset only when its name or description is clearly related; otherwise refine the list query once or ask the user which knowledge base/domain to use.status is no_results, answer from conversation context if possible and say no relevant accessible knowledge base was found.retrieve_knowledge with the selected dataset_ids and a concise query. Do not use dataset IDs that were not returned by the list tool.status, source_summary, context_blocks, and scores before answering:
source_summary or retriever_resources when useful.list_accessible_knowledge_bases accepts:
query: optional search text for narrowing candidate knowledge bases.limit: optional maximum number of candidates. Defaults to 20 and is capped at 100.retrieve_knowledge accepts:
query: the user question or refined search query.dataset_ids: required selected knowledge base IDs returned by the list tool.top_k: optional maximum retrieved chunks. Defaults to 5 and is capped at 20.retrieval_mode: optional hybrid, vector, or graph. Omit it for the default hybrid mode; use graph only for relationship or entity questions.