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    "title": "Wikipedia Research Intelligence — Topic Maps & Research Briefs",
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            "type": "string",
            "description": "Search query for Wikipedia articles",
            "default": "artificial intelligence"
          },
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            "enum": [
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              "de",
              "fr",
              "es",
              "ja",
              "zh",
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              "pt",
              "it",
              "ar",
              "nl",
              "ko",
              "pl",
              "sv",
              "vi"
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            "description": "Wikipedia language code (e.g., en, de, fr, es, ja, zh, ru, pt, it, ar)",
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          },
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            "title": "Include Article Summary",
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          },
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            "default": 20
          },
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            "title": "Output Profile",
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              "standard",
              "full"
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          },
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          },
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            "maxItems": 20,
            "type": "array",
            "description": "Optional list of additional Wikipedia language codes (e.g. de, fr, ja) to compare how broadly this topic is covered. When set, the run summary record includes a per-language hit count and a coverage score. Does not change the main results, which still come from the primary Language above.",
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              "type": "string"
            }
          },
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            "title": "Build Topic Map (research surface)",
            "type": "boolean",
            "description": "Generate a research-surface topic map for the query: core concepts plus the people, organizations, related fields, and related concepts around it (classified deterministically from Wikidata entity types and the related-article graph). Emits one extra 'topic-map' record. Adds a few requests; useful for research and knowledge-graph workflows.",
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          },
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            "title": "Emit Research Brief",
            "type": "boolean",
            "description": "Emit a single 'research-brief' record that synthesises the run into a 5-minute understanding of the topic: primary concept, executive summary, what matters, reading order, key people/organizations, and gaps. Built deterministically from the run's own data (no LLM, no extra calls). On by default; turn off if you only want raw result rows.",
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          }
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