Fodda Synthetic Expert Consult

Previous value: -"Optional user identifier."New value: +"Optional expert user identifier or email. Automatically resolved from authenticated API key for expert accounts."

Previous value: -"The internal expert ID of the Synthetic Analyst (e.g., 'brand-cmo' or from list_analysts). Never display raw IDs or slugs, internal field names, or tool names to the user — refer to the expert by display name."New value: +"The internal ID of the agent (from list_analysts or find_expert, e.g. 'brand-cmo', 'john-ruskin', or 'retail-synthetic'). This is an internal identifier; the agent's display name is in the response."

Added value: +{
+  "description": "Set true to have the agent conduct deep background research across specialist graphs and market data before answering (or detects 'do your homework' / 'deep breakdown' in multi-turn queries).",
+  "type": "boolean"
+}

Previous value: -"The question or topic to discuss with the synthetic analyst"New value: +"The question or topic to discuss with the analyst"

Previous value: -"Pass the session_id from a previous consult response to continue that engagement — the analyst keeps context and follow-ups cost less. Omit for a one-off question."New value: +"Pass the session_id from a previous consult response to continue that engagement — the analyst keeps context across the session. Omit for a one-off question."

Previous value: -"Optional user identifier."New value: +"Optional expert user identifier or email. Automatically resolved from authenticated API key for expert accounts."

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": {},
+  "properties": {
+    "coverage": {
+      "description": "Coverage tier: FULL, PARTIAL, or PENDING",
+      "type": "string"
+    },
+    "credibility_anchor": {
+      "anyOf": [
+        {
+          "type": "string"
+        },
+        {
+          "type": "null"
+        }
+      ],
+      "description": "Pedigree or executive role framing"
+    },
+    "expert": {
+      "additionalProperties": {},
+      "description": "Analyst information",
+      "properties": {
+        "analyst_id": {
+          "description": "Identifier of the analyst or persona",
+          "type": "string"
+        },
+        "name": {
+          "description": "Display name of the analyst or persona",
+          "type": "string"
+        }
+      },
+      "type": "object"
+    },
+    "job_id": {
+      "description": "Job identifier if running asynchronous deep research",
+      "type": "string"
+    },
+    "next_moves": {
+      "description": "Recommended next research or application actions"
+    },
+    "sources_used": {
+      "description": "Sources, citations, and graph evidence cited in the analysis",
+      "items": {},
+      "type": "array"
+    },
+    "status": {
+      "description": "Status if running asynchronous deep research",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

Previous value: -"The internal expert ID of the Human Agent (from list_analysts). Never display raw IDs or slugs, internal field names, or tool names to the user — refer to the expert by display name."New value: +"The expert ID of the Human Agent (from list_analysts or find_expert, e.g. 'ben-dietz-sic'). Refer to the expert by their display name and credentials in user-facing responses."

Added value: +{
+  "description": "Set true to have the human agent conduct deep background research across specialist graphs and market data before answering (or detects 'do your homework' / 'deep breakdown' in multi-turn queries).",
+  "type": "boolean"
+}

Previous value: -"Pass the session_id from a previous consult response to continue that engagement — the human agent keeps context and follow-ups cost less. Omit for a one-off question."New value: +"Pass the session_id from a previous consult response to continue that engagement — the human agent keeps context across the session. Omit for a one-off question."

Previous value: -"Optional user identifier."New value: +"Optional expert user identifier or email. Automatically resolved from authenticated API key for expert accounts."

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": {},
+  "properties": {
+    "coverage": {
+      "description": "Coverage tier: FULL, PARTIAL, or PENDING",
+      "type": "string"
+    },
+    "credibility_anchor": {
+      "anyOf": [
+        {
+          "type": "string"
+        },
+        {
+          "type": "null"
+        }
+      ],
+      "description": "Official background credibility anchor of the Human Agent"
+    },
+    "expert": {
+      "additionalProperties": {},
+      "description": "Expert information",
+      "properties": {
+        "analyst_id": {
+          "description": "Identifier of the expert",
+          "type": "string"
+        },
+        "name": {
+          "description": "Display name of the expert",
+          "type": "string"
+        }
+      },
+      "type": "object"
+    },
+    "job_id": {
+      "description": "Job identifier if running asynchronous deep research",
+      "type": "string"
+    },
+    "next_moves": {
+      "description": "Recommended next research or application actions"
+    },
+    "sources_used": {
+      "description": "Sources, citations, and graph evidence cited in the analysis",
+      "items": {},
+      "type": "array"
+    },
+    "status": {
+      "description": "Status if running asynchronous deep research",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

Added value: +{
+  "description": "Optional subject, brand, category, or problem statement to assess topic reconnaissance ('What does Fodda know about [topic]?'). If omitted, returns platform capability overview, workflow recipes, and specialist breakdown.",
+  "type": "string"
+}

Previous value: -"Optional user identifier."New value: +"Optional expert user identifier or email. Automatically resolved from authenticated API key for expert accounts."

Previous value: -"The label to fetch values for (e.g., 'Brand', 'Location', 'Technology', 'Audience', 'RetailerType', 'Trend')"New value: +"The label to fetch values for (e.g., 'Brand', 'Location', 'Technology', 'Audience', 'RetailerType', 'Trend'). Note: caps at 100 values alphabetically."

Added value: +{
+  "description": "Filter by agent category: 'human_agent' (Human Agent), 'classic_agent' (Classic Agent), 'c_suite_agent' (C-Suite Agent), 'synthetic_agent' (Synthetic Agent), or 'all' (default).",
+  "enum": [
+    "all",
+    "human_agent",
+    "classic_agent",
+    "c_suite_agent",
+    "synthetic_agent"
+  ],
+  "type": "string"
+}

Added value: +{
+  "description": "Optional natural language search query to filter analysts by lane, domain, expertise, or topics (e.g. 'streetwear', 'earnings', 'marketing').",
+  "type": "string"
+}

Previous value: -"Optional user identifier."New value: +"Optional expert user identifier or email. Automatically resolved from authenticated API key for expert accounts."

Previous value: -"The internal analyst ID producing the deliverable (from list_analysts). Never display raw IDs or slugs, internal field names, or tool names to the user — refer to the expert by display name."New value: +"The internal analyst ID producing the deliverable (from list_analysts). This is an internal identifier; the expert's display name is in the response."

Previous value: -"Optional user identifier."New value: +"Optional expert user identifier or email. Automatically resolved from authenticated API key for expert accounts."

Added value: +{
+  "description": "Alias for graphId.",
+  "type": "string"
+}

Added value: +{
+  "description": "Alias for graphId.",
+  "type": "string"
+}

Added value: +{
+  "description": "Optional sector focus (e.g. 'Alcoholic Drinks', 'Non-Alcoholic Drinks', 'Food & Beverage', 'Retail', 'Beauty', 'Sports', 'Technology', 'Luxury Goods'). When provided, scopes trend discovery to this sector.",
+  "type": "string"
+}

Previous value: -"JSON string containing the chart data. Structure depends on chart_type. cultural_shifts: {shifts:[{from,to}]}. competitive_compass: {brands:[{name,x,y,focus?:boolean}], axes:{left,right,top,bottom}}. trend_constellation: {trends:[{name,x,y,focus?:boolean}], connections:[{from,to,strength}]}. implication_ladder: {signal,trend,so_what,do_what}. innovation_pathway: {now,near_term,future}. opportunity_map: {items:[{name,consumer_desire,market_activity,focus?:boolean}], x_label?:string, y_label?:string}"New value: +"JSON string containing chart data. Optional top-level \"focus\":\"Name\" or per-item \"focus\":true highlights key entity in brand accent. cultural_shifts: {shifts:[{from,to}]}. competitive_compass: {brands:[{name,x,y,focus?:boolean}], axes:{left,right,top,bottom}, focus?:string}. trend_constellation: {trends:[{name,x,y,focus?:boolean}], connections:[{from,to,strength}], focus?:string}. implication_ladder: {signal,trend,so_what,do_what}. innovation_pathway: {now,near_term,future}. opportunity_map: {items:[{name,consumer_desire,market_activity,focus?:boolean}], x_label?:string, y_label?:string, focus?:string}"

Previous value: -"JSON string containing the chart data. Structure depends on chart_type. cultural_shifts: {shifts:[{from,to}]}. competitive_compass: {brands:[{name,x,y}], axes:{left,right,top,bottom}}. trend_constellation: {trends:[{name,x,y}], connections:[{from,to,strength}]}. implication_ladder: {signal,trend,so_what,do_what}. innovation_pathway: {now,near_term,future}. opportunity_map: {items:[{name,consumer_desire,market_activity}]}"New value: +"JSON string containing the chart data. Structure depends on chart_type. cultural_shifts: {shifts:[{from,to}]}. competitive_compass: {brands:[{name,x,y,focus?:boolean}], axes:{left,right,top,bottom}}. trend_constellation: {trends:[{name,x,y,focus?:boolean}], connections:[{from,to,strength}]}. implication_ladder: {signal,trend,so_what,do_what}. innovation_pathway: {now,near_term,future}. opportunity_map: {items:[{name,consumer_desire,market_activity,focus?:boolean}], x_label?:string, y_label?:string}"