{ "jsonrpc": "2.0", "id": 1, "result": { "content": [ { "type": "text", "text": "{\"skills\":[{\"key\":\"audience-comparison\",\"description\":\"Read this skill when the user asks to compare audiences or groups, contrast X vs Y, compare an attached audience, or explain similarities and differences.\"},{\"key\":\"audience-investigation\",\"description\":\"Read this skill when the user asks who to target, what audience to target, which audience is most likely to do or buy something, or how to target advertising, sponsorships, campaigns, or sales opportunities.\"},{\"key\":\"gwi-dictionary\",\"description\":\"Read this skill when the user asks what a GWI term or metric means, including responses, universe, audience percentage, data point percentage, or index.\"},{\"key\":\"segment-requests\",\"description\":\"Read this skill when the user asks for segments, segmentations, available segments, audience groups, market groups, or analysis of segment groups around a topic, location, or category.\"}]}" } ], "structuredContent": { "skills": [ { "key": "audience-comparison", "description": "Read this skill when the user asks to compare audiences or groups, contrast X vs Y, compare an attached audience, or explain similarities and differences." }, { "key": "audience-investigation", "description": "Read this skill when the user asks who to target, what audience to target, which audience is most likely to do or buy something, or how to target advertising, sponsorships, campaigns, or sales opportunities." }, { "key": "gwi-dictionary", "description": "Read this skill when the user asks what a GWI term or metric means, including responses, universe, audience percentage, data point percentage, or index." }, { "key": "segment-requests", "description": "Read this skill when the user asks for segments, segmentations, available segments, audience groups, market groups, or analysis of segment groups around a topic, location, or category." } ] } }}
MCP Tools
Execute GWI MCP v2beta tool calls
JSON-RPC endpoint for the v2beta MCP profile. Supported tools:
{ "jsonrpc": "2.0", "id": 1, "result": { "content": [ { "type": "text", "text": "{\"skills\":[{\"key\":\"audience-comparison\",\"description\":\"Read this skill when the user asks to compare audiences or groups, contrast X vs Y, compare an attached audience, or explain similarities and differences.\"},{\"key\":\"audience-investigation\",\"description\":\"Read this skill when the user asks who to target, what audience to target, which audience is most likely to do or buy something, or how to target advertising, sponsorships, campaigns, or sales opportunities.\"},{\"key\":\"gwi-dictionary\",\"description\":\"Read this skill when the user asks what a GWI term or metric means, including responses, universe, audience percentage, data point percentage, or index.\"},{\"key\":\"segment-requests\",\"description\":\"Read this skill when the user asks for segments, segmentations, available segments, audience groups, market groups, or analysis of segment groups around a topic, location, or category.\"}]}" } ], "structuredContent": { "skills": [ { "key": "audience-comparison", "description": "Read this skill when the user asks to compare audiences or groups, contrast X vs Y, compare an attached audience, or explain similarities and differences." }, { "key": "audience-investigation", "description": "Read this skill when the user asks who to target, what audience to target, which audience is most likely to do or buy something, or how to target advertising, sponsorships, campaigns, or sales opportunities." }, { "key": "gwi-dictionary", "description": "Read this skill when the user asks what a GWI term or metric means, including responses, universe, audience percentage, data point percentage, or index." }, { "key": "segment-requests", "description": "Read this skill when the user asks for segments, segmentations, available segments, audience groups, market groups, or analysis of segment groups around a topic, location, or category." } ] } }}
JSON-RPC request for any supported v2beta MCP tool
list_skills
get_skills
list_datasets
explore_datasets
global_filters
explore_taxonomy
search_audiences
audience_generation
generate_insights
explore_insight
Discover workflow skill keys and short descriptions. Call at the start of each new GWI analysis and when the user shifts to a different workflow type on a follow-up.
Match the user request to returned descriptions. Do not invent keys. Full skill bodies are not included — use get_skills for matching keys only.
Do not mention this tool or skill mechanics in user-facing replies.
JSON-RPC response. HTTP 200 means the JSON-RPC call was processed, not that the tool succeeded.
Inspect result.isError if present:
true — tool failed; the message is in result.content[0].text, and result._meta.isInternalError may be true for internal or timeout-style failures.
See Tool errors (result.isError) in the overview above for full behavior.
JSON-RPC 2.0 success envelope for MCP tools/call (no top-level error field).
When the tool fails, HTTP status is still typically 200 and this object is returned with result.isError: true. Use that flag rather than HTTP status alone.
MCP tool result. Inspect isError for tool-level success or failure.
isError: true — the tool failed; content usually has one text item with a human-readable explanation. Typical causes:
Invalid arguments (e.g. empty prompt, invalid UUID for insight_id where required).
Downstream errors (e.g. resource not found, timeout, cancelled request, or generic internal failure).
_meta.isInternalError — when present and true, the server classified the failure as internal or timeout-style. Omitted or false for most validation and not-found style errors.
This is not the same as a JSON-RPC protocol error: invalid method or malformed requests use the standard JSON-RPC error field instead of a tool result.
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Unknown keys and empty `skill_keys` return `result.isError`.\nDo not mention this tool or skill mechanics in user-facing replies.\n","required":["jsonrpc","id","method","params"],"example":{"jsonrpc":"2.0","id":2,"method":"tools/call","params":{"name":"get_skills","arguments":{"skill_keys":["audience-investigation"]}}},"properties":{"jsonrpc":{"type":"string","enum":["2.0"],"isRequired":true,"uniqueKey":"oneOf.1.jsonrpc","typeLabel":"enum\u003cstring>"},"id":{"oneOf":[{"type":"string","example":2,"isRequired":true,"uniqueKey":"oneOf.1.id.oneOf.0","typeLabel":"string"},{"type":"integer","example":2,"isRequired":true,"uniqueKey":"oneOf.1.id.oneOf.1","typeLabel":"integer"}],"isRequired":true,"uniqueKey":"oneOf.1.id","typeLabel":"string | integer"},"method":{"type":"string","enum":["tools/call"],"isRequired":true,"uniqueKey":"oneOf.1.method","typeLabel":"enum\u003cstring>"},"params":{"type":"object","required":["name","arguments"],"properties":{"name":{"type":"string","enum":["get_skills"],"isRequired":true,"uniqueKey":"oneOf.1.params.name","typeLabel":"enum\u003cstring>"},"arguments":{"type":"object","required":["skill_keys"],"properties":{"skill_keys":{"type":"array","description":"Non-empty catalogue keys returned by `list_skills`. Do not invent keys.","minItems":1,"items":{"type":"string","uniqueKey":"oneOf.1.params.arguments.skill_keys.items.[INDEX]","typeLabel":"string"},"example":["audience-investigation"],"isRequired":true,"uniqueKey":"oneOf.1.params.arguments.skill_keys","typeLabel":"string[]"}},"isRequired":true,"uniqueKey":"oneOf.1.params.arguments","typeLabel":"object"}},"isRequired":true,"uniqueKey":"oneOf.1.params","typeLabel":"object"}},"uniqueKey":"oneOf.1","typeLabel":"get_skills · object"},{"type":"object","title":"list_datasets","description":"List accessible GWI datasets and valid dataset codes for downstream tools.\nReturns a hierarchical tree: `type: dataset` and `type: folder` nodes, with nested `children` where present.\nThe live response can be large; examples below are truncated.\n","required":["jsonrpc","id","method","params"],"example":{"jsonrpc":"2.0","id":3,"method":"tools/call","params":{"name":"list_datasets","arguments":{}}},"properties":{"jsonrpc":{"type":"string","enum":["2.0"],"isRequired":true,"uniqueKey":"oneOf.2.jsonrpc","typeLabel":"enum\u003cstring>"},"id":{"oneOf":[{"type":"string","example":3,"isRequired":true,"uniqueKey":"oneOf.2.id.oneOf.0","typeLabel":"string"},{"type":"integer","example":3,"isRequired":true,"uniqueKey":"oneOf.2.id.oneOf.1","typeLabel":"integer"}],"isRequired":true,"uniqueKey":"oneOf.2.id","typeLabel":"string | integer"},"method":{"type":"string","enum":["tools/call"],"isRequired":true,"uniqueKey":"oneOf.2.method","typeLabel":"enum\u003cstring>"},"params":{"type":"object","required":["name"],"properties":{"name":{"type":"string","enum":["list_datasets"],"isRequired":true,"uniqueKey":"oneOf.2.params.name","typeLabel":"enum\u003cstring>"},"arguments":{"type":"object","description":"No arguments required.","uniqueKey":"oneOf.2.params.arguments","typeLabel":"object"}},"isRequired":true,"uniqueKey":"oneOf.2.params","typeLabel":"object"}},"uniqueKey":"oneOf.2","typeLabel":"list_datasets · object"},{"type":"object","title":"explore_datasets","description":"Retrieve short or verbose descriptions for 1–5 dataset codes returned by `list_datasets`.\nUse after `list_datasets` for dataset coverage, Pulse topics, module summaries, or help choosing between datasets. Pure dataset discovery does not require `global_filters`.\nA successful response can contain `summary_error` for individual datasets whose summary is unavailable; do not invent missing coverage.\n","required":["jsonrpc","id","method","params"],"example":{"jsonrpc":"2.0","id":10,"method":"tools/call","params":{"name":"explore_datasets","arguments":{"dataset_codes":["ds-core"],"length":"verbose"}}},"properties":{"jsonrpc":{"type":"string","enum":["2.0"],"isRequired":true,"uniqueKey":"oneOf.3.jsonrpc","typeLabel":"enum\u003cstring>"},"id":{"oneOf":[{"type":"string","example":10,"isRequired":true,"uniqueKey":"oneOf.3.id.oneOf.0","typeLabel":"string"},{"type":"integer","example":10,"isRequired":true,"uniqueKey":"oneOf.3.id.oneOf.1","typeLabel":"integer"}],"isRequired":true,"uniqueKey":"oneOf.3.id","typeLabel":"string | integer"},"method":{"type":"string","enum":["tools/call"],"isRequired":true,"uniqueKey":"oneOf.3.method","typeLabel":"enum\u003cstring>"},"params":{"type":"object","required":["name","arguments"],"properties":{"name":{"type":"string","enum":["explore_datasets"],"isRequired":true,"uniqueKey":"oneOf.3.params.name","typeLabel":"enum\u003cstring>"},"arguments":{"type":"object","required":["dataset_codes","length"],"properties":{"dataset_codes":{"type":"array","description":"Non-empty list of 1–5 dataset codes returned by `list_datasets`. Never invent codes.","minItems":1,"maxItems":5,"items":{"type":"string","uniqueKey":"oneOf.3.params.arguments.dataset_codes.items.[INDEX]","typeLabel":"string"},"isRequired":true,"uniqueKey":"oneOf.3.params.arguments.dataset_codes","typeLabel":"string[]"},"length":{"type":"string","description":"Use `short` for concise candidate context and `verbose` for detailed coverage or topic questions.","enum":["short","verbose"],"isRequired":true,"uniqueKey":"oneOf.3.params.arguments.length","typeLabel":"enum\u003cstring>"}},"isRequired":true,"uniqueKey":"oneOf.3.params.arguments","typeLabel":"object"}},"isRequired":true,"uniqueKey":"oneOf.3.params","typeLabel":"object"}},"uniqueKey":"oneOf.3","typeLabel":"explore_datasets · object"},{"type":"object","title":"global_filters","description":"Resolve location and wave filters. Required before audience_generation, search_audiences (when used in the same workflow), and generate_insights.\n","required":["jsonrpc","id","method","params"],"example":{"jsonrpc":"2.0","id":4,"method":"tools/call","params":{"name":"global_filters","arguments":{"prompt":"social media habits of Gen Z in the UK in Q1 2025"}}},"properties":{"jsonrpc":{"type":"string","enum":["2.0"],"isRequired":true,"uniqueKey":"oneOf.4.jsonrpc","typeLabel":"enum\u003cstring>"},"id":{"type":"string","example":4,"isRequired":true,"uniqueKey":"oneOf.4.id","typeLabel":"string"},"method":{"type":"string","enum":["tools/call"],"isRequired":true,"uniqueKey":"oneOf.4.method","typeLabel":"enum\u003cstring>"},"params":{"type":"object","required":["name","arguments"],"properties":{"name":{"type":"string","enum":["global_filters"],"isRequired":true,"uniqueKey":"oneOf.4.params.name","typeLabel":"enum\u003cstring>"},"arguments":{"type":"object","required":["prompt"],"properties":{"prompt":{"type":"string","description":"Non-empty. When the user named location and/or timeframe, include only terms needed to extract that scope.\nWhen `current_filters` is provided and new scope is requested, state whether to append or overwrite.\n","example":"social media habits of Gen Z in the UK in Q1 2025","isRequired":true,"uniqueKey":"oneOf.4.params.arguments.prompt","typeLabel":"string"},"dataset_codes":{"type":"array","description":"Optional dataset codes from list_datasets (same tree).","items":{"type":"string","uniqueKey":"oneOf.4.params.arguments.dataset_codes.items.[INDEX]","typeLabel":"string"},"example":["ds-core"],"uniqueKey":"oneOf.4.params.arguments.dataset_codes","typeLabel":"string[]"},"current_filters":{"type":"object","description":"Prior successful response only — carry forward resolved names, not codes.","properties":{"location_names":{"type":"array","items":{"type":"string","uniqueKey":"oneOf.4.params.arguments.current_filters.location_names.items.[INDEX]","typeLabel":"string"},"example":["UK"],"uniqueKey":"oneOf.4.params.arguments.current_filters.location_names","typeLabel":"string[]"},"wave_names":{"type":"array","items":{"type":"string","uniqueKey":"oneOf.4.params.arguments.current_filters.wave_names.items.[INDEX]","typeLabel":"string"},"example":["Q1 2025"],"uniqueKey":"oneOf.4.params.arguments.current_filters.wave_names","typeLabel":"string[]"}},"uniqueKey":"oneOf.4.params.arguments.current_filters","typeLabel":"object"}},"isRequired":true,"uniqueKey":"oneOf.4.params.arguments","typeLabel":"object"}},"isRequired":true,"uniqueKey":"oneOf.4.params","typeLabel":"object"}},"uniqueKey":"oneOf.4","typeLabel":"global_filters · object"},{"type":"object","title":"explore_taxonomy","description":"Discover GWI survey questions and attributes relevant to a topic. This is semantic data discovery, not computed insight generation.\nCall `global_filters` first on every new user message. Keep `prompt` topic-only; pass audience, location, timeframe, and dataset scope through their dedicated arguments.\nUse returned data points to explain available coverage or refine a later `generate_insights` prompt. Curate relevant results rather than presenting every match.\n","required":["jsonrpc","id","method","params"],"example":{"jsonrpc":"2.0","id":11,"method":"tools/call","params":{"name":"explore_taxonomy","arguments":{"prompt":"social media usage","dataset_codes":["ds-core"],"enforced_audiences":["550e8400-e29b-41d4-a716-446655440000"],"location_codes":["s2_1"],"wave_codes":["q1_2026"]}}},"properties":{"jsonrpc":{"type":"string","enum":["2.0"],"isRequired":true,"uniqueKey":"oneOf.5.jsonrpc","typeLabel":"enum\u003cstring>"},"id":{"oneOf":[{"type":"string","example":11,"isRequired":true,"uniqueKey":"oneOf.5.id.oneOf.0","typeLabel":"string"},{"type":"integer","example":11,"isRequired":true,"uniqueKey":"oneOf.5.id.oneOf.1","typeLabel":"integer"}],"isRequired":true,"uniqueKey":"oneOf.5.id","typeLabel":"string | integer"},"method":{"type":"string","enum":["tools/call"],"isRequired":true,"uniqueKey":"oneOf.5.method","typeLabel":"enum\u003cstring>"},"params":{"type":"object","required":["name","arguments"],"properties":{"name":{"type":"string","enum":["explore_taxonomy"],"isRequired":true,"uniqueKey":"oneOf.5.params.name","typeLabel":"enum\u003cstring>"},"arguments":{"type":"object","required":["prompt"],"properties":{"prompt":{"type":"string","minLength":1,"description":"Topic or subject to search for. Do not include audiences, locations, or timeframes.","isRequired":true,"uniqueKey":"oneOf.5.params.arguments.prompt","typeLabel":"string"},"dataset_codes":{"type":"array","description":"Optional compatible dataset codes returned by `list_datasets`.","items":{"type":"string","uniqueKey":"oneOf.5.params.arguments.dataset_codes.items.[INDEX]","typeLabel":"string"},"uniqueKey":"oneOf.5.params.arguments.dataset_codes","typeLabel":"string[]"},"enforced_audiences":{"type":"array","description":"Optional audience UUIDs returned by `audience_generation` or `search_audiences`.","maxItems":10,"items":{"type":"string","format":"uuid","uniqueKey":"oneOf.5.params.arguments.enforced_audiences.items.[INDEX]","typeLabel":"string\u003cuuid>"},"uniqueKey":"oneOf.5.params.arguments.enforced_audiences","typeLabel":"string\u003cuuid>[]"},"location_codes":{"type":"array","description":"Optional flat location codes already resolved by `global_filters`.","items":{"type":"string","uniqueKey":"oneOf.5.params.arguments.location_codes.items.[INDEX]","typeLabel":"string"},"uniqueKey":"oneOf.5.params.arguments.location_codes","typeLabel":"string[]"},"wave_codes":{"type":"array","description":"Optional flat wave codes already resolved by `global_filters`.","items":{"type":"string","uniqueKey":"oneOf.5.params.arguments.wave_codes.items.[INDEX]","typeLabel":"string"},"uniqueKey":"oneOf.5.params.arguments.wave_codes","typeLabel":"string[]"},"questions_k":{"type":"integer","description":"Optional number of survey questions to retrieve. Defaults to 5 when omitted or zero; intended range 3–30.","uniqueKey":"oneOf.5.params.arguments.questions_k","typeLabel":"integer"},"attributes_k":{"type":"integer","description":"Optional number of attributes to retrieve. Defaults to 10 when omitted or zero; intended range 5–50.","uniqueKey":"oneOf.5.params.arguments.attributes_k","typeLabel":"integer"}},"isRequired":true,"uniqueKey":"oneOf.5.params.arguments","typeLabel":"object"}},"isRequired":true,"uniqueKey":"oneOf.5.params","typeLabel":"object"}},"uniqueKey":"oneOf.5","typeLabel":"explore_taxonomy · object"},{"type":"object","title":"search_audiences","description":"Search saved platform audiences. Pass audiences[].id to generate_insights.enforced_audiences.\nResponse items use `title` (not `name`) for the audience label.\n","required":["jsonrpc","id","method","params"],"example":{"jsonrpc":"2.0","id":6,"method":"tools/call","params":{"name":"search_audiences","arguments":{"query":"Gen Z","limit":5}}},"properties":{"jsonrpc":{"type":"string","enum":["2.0"],"isRequired":true,"uniqueKey":"oneOf.6.jsonrpc","typeLabel":"enum\u003cstring>"},"id":{"type":"string","example":6,"isRequired":true,"uniqueKey":"oneOf.6.id","typeLabel":"string"},"method":{"type":"string","enum":["tools/call"],"isRequired":true,"uniqueKey":"oneOf.6.method","typeLabel":"enum\u003cstring>"},"params":{"type":"object","required":["name","arguments"],"properties":{"name":{"type":"string","enum":["search_audiences"],"isRequired":true,"uniqueKey":"oneOf.6.params.name","typeLabel":"enum\u003cstring>"},"arguments":{"type":"object","required":["query"],"properties":{"query":{"type":"string","description":"Required free-text audience search query.","example":"Gen Z","isRequired":true,"uniqueKey":"oneOf.6.params.arguments.query","typeLabel":"string"},"dataset_codes":{"type":"array","items":{"type":"string","uniqueKey":"oneOf.6.params.arguments.dataset_codes.items.[INDEX]","typeLabel":"string"},"example":["ds-core"],"uniqueKey":"oneOf.6.params.arguments.dataset_codes","typeLabel":"string[]"},"exclude_audience_ids":{"type":"array","items":{"type":"string","pattern":"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$","uniqueKey":"oneOf.6.params.arguments.exclude_audience_ids.items.[INDEX]","typeLabel":"string"},"uniqueKey":"oneOf.6.params.arguments.exclude_audience_ids","typeLabel":"string[]"},"limit":{"type":"integer","minimum":1,"maximum":100,"example":5,"uniqueKey":"oneOf.6.params.arguments.limit","typeLabel":"integer"}},"isRequired":true,"uniqueKey":"oneOf.6.params.arguments","typeLabel":"object"}},"isRequired":true,"uniqueKey":"oneOf.6.params","typeLabel":"object"}},"uniqueKey":"oneOf.6","typeLabel":"search_audiences · object"},{"type":"object","title":"audience_generation","description":"Create platform audiences from natural-language descriptions.\nCall only after global_filters on the same user message.\n","required":["jsonrpc","id","method","params"],"example":{"jsonrpc":"2.0","id":5,"method":"tools/call","params":{"name":"audience_generation","arguments":{"audiences":["Gen Z"],"location_codes":["s2_44"],"wave_codes":["q1_2025"]}}},"properties":{"jsonrpc":{"type":"string","enum":["2.0"],"isRequired":true,"uniqueKey":"oneOf.7.jsonrpc","typeLabel":"enum\u003cstring>"},"id":{"type":"string","example":5,"isRequired":true,"uniqueKey":"oneOf.7.id","typeLabel":"string"},"method":{"type":"string","enum":["tools/call"],"isRequired":true,"uniqueKey":"oneOf.7.method","typeLabel":"enum\u003cstring>"},"params":{"type":"object","required":["name","arguments"],"properties":{"name":{"type":"string","enum":["audience_generation"],"isRequired":true,"uniqueKey":"oneOf.7.params.name","typeLabel":"enum\u003cstring>"},"arguments":{"type":"object","required":["audiences"],"properties":{"audiences":{"type":"array","description":"Required natural-language audience descriptions.","minItems":1,"items":{"type":"string","uniqueKey":"oneOf.7.params.arguments.audiences.items.[INDEX]","typeLabel":"string"},"example":["Gen Z"],"isRequired":true,"uniqueKey":"oneOf.7.params.arguments.audiences","typeLabel":"string[]"},"dataset_codes":{"type":"array","items":{"type":"string","uniqueKey":"oneOf.7.params.arguments.dataset_codes.items.[INDEX]","typeLabel":"string"},"example":["ds-core"],"uniqueKey":"oneOf.7.params.arguments.dataset_codes","typeLabel":"string[]"},"location_codes":{"type":"array","description":"Forward non-empty values from global_filters.global_filters.location_codes.","items":{"type":"string","uniqueKey":"oneOf.7.params.arguments.location_codes.items.[INDEX]","typeLabel":"string"},"example":["s2_44"],"uniqueKey":"oneOf.7.params.arguments.location_codes","typeLabel":"string[]"},"wave_codes":{"type":"array","description":"Forward non-empty values from global_filters.global_filters.wave_codes.","items":{"type":"string","uniqueKey":"oneOf.7.params.arguments.wave_codes.items.[INDEX]","typeLabel":"string"},"example":["q1_2025"],"uniqueKey":"oneOf.7.params.arguments.wave_codes","typeLabel":"string[]"}},"isRequired":true,"uniqueKey":"oneOf.7.params.arguments","typeLabel":"object"}},"isRequired":true,"uniqueKey":"oneOf.7.params","typeLabel":"object"}},"uniqueKey":"oneOf.7","typeLabel":"audience_generation · object"},{"type":"object","title":"generate_insights","description":"Generate structured audience insights. Primary discovery tool on v2beta.\nPass `enforced_audiences` with UUIDs from audience_generation or search_audiences.\n","required":["jsonrpc","id","method","params"],"example":{"jsonrpc":"2.0","id":7,"method":"tools/call","params":{"name":"generate_insights","arguments":{"prompts":["social media habits"],"enforced_audiences":["259f6394-436c-4801-b83b-bbc926e8b4b9"],"location_codes":["s2_44"],"wave_codes":["q1_2025"],"limit":5}}},"properties":{"jsonrpc":{"type":"string","enum":["2.0"],"isRequired":true,"uniqueKey":"oneOf.8.jsonrpc","typeLabel":"enum\u003cstring>"},"id":{"type":"string","example":7,"isRequired":true,"uniqueKey":"oneOf.8.id","typeLabel":"string"},"method":{"type":"string","enum":["tools/call"],"isRequired":true,"uniqueKey":"oneOf.8.method","typeLabel":"enum\u003cstring>"},"params":{"type":"object","required":["name","arguments"],"properties":{"name":{"type":"string","enum":["generate_insights"],"isRequired":true,"uniqueKey":"oneOf.8.params.name","typeLabel":"enum\u003cstring>"},"arguments":{"type":"object","required":["prompts"],"properties":{"prompts":{"type":"array","description":"Required array of strings. 1–10 short research questions per call. Each element is one topic.","minItems":1,"maxItems":10,"items":{"type":"string","uniqueKey":"oneOf.8.params.arguments.prompts.items.[INDEX]","typeLabel":"string"},"example":["social media habits","streaming preferences"],"isRequired":true,"uniqueKey":"oneOf.8.params.arguments.prompts","typeLabel":"string[]"},"dataset_codes":{"type":"array","description":"Optional. Only when dataset scope was established earlier in the workflow.","items":{"type":"string","uniqueKey":"oneOf.8.params.arguments.dataset_codes.items.[INDEX]","typeLabel":"string"},"example":["ds-core"],"uniqueKey":"oneOf.8.params.arguments.dataset_codes","typeLabel":"string[]"},"enforced_audiences":{"type":"array","description":"Optional platform audience UUIDs (max 10).\nUse IDs from audience_generation or search_audiences only.\n","maxItems":10,"items":{"type":"string","format":"uuid","uniqueKey":"oneOf.8.params.arguments.enforced_audiences.items.[INDEX]","typeLabel":"string\u003cuuid>"},"example":["259f6394-436c-4801-b83b-bbc926e8b4b9"],"uniqueKey":"oneOf.8.params.arguments.enforced_audiences","typeLabel":"string\u003cuuid>[]"},"location_codes":{"type":"array","description":"Forward from global_filters when non-empty.","items":{"type":"string","uniqueKey":"oneOf.8.params.arguments.location_codes.items.[INDEX]","typeLabel":"string"},"example":["s2_44"],"uniqueKey":"oneOf.8.params.arguments.location_codes","typeLabel":"string[]"},"wave_codes":{"type":"array","description":"Forward from global_filters when non-empty.","items":{"type":"string","uniqueKey":"oneOf.8.params.arguments.wave_codes.items.[INDEX]","typeLabel":"string"},"example":["q1_2025"],"uniqueKey":"oneOf.8.params.arguments.wave_codes","typeLabel":"string[]"},"limit":{"type":"integer","description":"Optional maximum insights to return (1-20). Default 10 when omitted.","minimum":1,"maximum":20,"example":5,"uniqueKey":"oneOf.8.params.arguments.limit","typeLabel":"integer"}},"isRequired":true,"uniqueKey":"oneOf.8.params.arguments","typeLabel":"object"}},"isRequired":true,"uniqueKey":"oneOf.8.params","typeLabel":"object"}},"uniqueKey":"oneOf.8","typeLabel":"generate_insights · object"},{"type":"object","title":"explore_insight","description":"Deep dive into a specific insight from generate_insights. Returns structured JSON with narrative text,\nper-answer statistics in `metadata.attributes[]`, and provenance (audiences, datasets, locations, timeframes).\n\nReactive-only on v2beta — call only when the user explicitly requests more detail on a specific `insights[].id`.\nDo not call automatically after `generate_insights`.\n","required":["jsonrpc","id","method","params"],"example":{"jsonrpc":"2.0","id":8,"method":"tools/call","params":{"name":"explore_insight","arguments":{"insight_id":"95c35f2c-9235-4536-ad46-44867a3a5996"}}},"properties":{"jsonrpc":{"type":"string","enum":["2.0"],"isRequired":true,"uniqueKey":"oneOf.9.jsonrpc","typeLabel":"enum\u003cstring>"},"id":{"type":"string","example":8,"isRequired":true,"uniqueKey":"oneOf.9.id","typeLabel":"string"},"method":{"type":"string","enum":["tools/call"],"isRequired":true,"uniqueKey":"oneOf.9.method","typeLabel":"enum\u003cstring>"},"params":{"type":"object","required":["name","arguments"],"properties":{"name":{"type":"string","enum":["explore_insight"],"isRequired":true,"uniqueKey":"oneOf.9.params.name","typeLabel":"enum\u003cstring>"},"arguments":{"type":"object","required":["insight_id"],"properties":{"insight_id":{"type":"string","description":"Exact UUID from a prior generate_insights response (insights[].id).","pattern":"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$","example":"95c35f2c-9235-4536-ad46-44867a3a5996","isRequired":true,"uniqueKey":"oneOf.9.params.arguments.insight_id","typeLabel":"string"}},"isRequired":true,"uniqueKey":"oneOf.9.params.arguments","typeLabel":"object"}},"isRequired":true,"uniqueKey":"oneOf.9.params","typeLabel":"object"}},"uniqueKey":"oneOf.9","typeLabel":"explore_insight · object"}],"uniqueKey":"","typeLabel":"list_skills · object | get_skills · object | list_datasets · object | explore_datasets · object | global_filters · object | explore_taxonomy · object | search_audiences · object | audience_generation · object | generate_insights · object | explore_insight · object"},"examples":{"Example":{"title":"Example","value":{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"list_skills","arguments":{}}}}},"exampleType":"generated"}},"exampleType":"generated"},"responses":{"6dfd4ef5-c3bb-42d8-820b-5ba14a34dffc":{"description":"JSON-RPC response. HTTP 200 means the JSON-RPC call was processed, not that the tool succeeded.\n\nInspect `result.isError` if present:\n\n- `true` — tool failed; the message is in `result.content[0].text`, and `result._meta.isInternalError` may be `true` for internal or timeout-style failures.\n\nSee **Tool errors (`result.isError`)** in the overview above for full behavior.\n","content":{"application/json":{"schema":{"type":"object","description":"JSON-RPC 2.0 success envelope for MCP `tools/call` (no top-level `error` field).\n\nWhen the tool fails, HTTP status is still typically **200** and this object is returned with `result.isError: true`. Use that flag rather than HTTP status alone.\n","required":["jsonrpc","id","result"],"properties":{"jsonrpc":{"type":"string","enum":["2.0"],"isRequired":true,"uniqueKey":"jsonrpc","typeLabel":"enum\u003cstring>"},"id":{"type":"string","description":"Request identifier echoed back","isRequired":true,"uniqueKey":"id","typeLabel":"string"},"result":{"type":"object","description":"MCP tool result. Inspect `isError` for tool-level success or failure.\n\n**`isError: true`** — the tool failed; `content` usually has one `text` item with a human-readable explanation. Typical causes:\n\n- **Invalid arguments** (e.g. empty `prompt`, invalid UUID for `insight_id` where required).\n- **Downstream errors** (e.g. resource not found, timeout, cancelled request, or generic internal failure).\n\n**`_meta.isInternalError`** — when present and `true`, the server classified the failure as internal or timeout-style. Omitted or `false` for most validation and not-found style errors.\n\nThis is **not** the same as a JSON-RPC protocol error: invalid `method` or malformed requests use the standard JSON-RPC `error` field instead of a tool `result`.\n","required":["content"],"properties":{"content":{"type":"array","items":{"type":"object","required":["type","text"],"properties":{"type":{"type":"string","enum":["text"],"isRequired":true,"uniqueKey":"result.content.items.[INDEX].type","typeLabel":"enum\u003cstring>"},"text":{"type":"string","description":"Tool response if successful. When `result.isError` is `true`, it is the error message (exact wording may vary; do not rely on it for branching except for documented validation cases). On success, this is typically a JSON-encoded mirror of `structuredContent`.","isRequired":true,"uniqueKey":"result.content.items.[INDEX].text","typeLabel":"string"}},"uniqueKey":"result.content.items.[INDEX]","typeLabel":"object"},"isRequired":true,"uniqueKey":"result.content","typeLabel":"object[]"},"structuredContent":{"type":"object","description":"Typed tool output when the call succeeds. Prefer this over parsing `content[0].text`. The object shape depends on the tool that was called — see the response examples below and the Tools overview.","uniqueKey":"result.structuredContent","typeLabel":"object"},"isError":{"type":"boolean","description":"Tool-level failure indicator. `true` means the tool did not return a successful result; read `content[0].text` (when present) for details. Optional `_meta.isInternalError` refines internal failures.","uniqueKey":"result.isError","typeLabel":"boolean"},"_meta":{"type":"object","description":"Optional MCP result metadata.","properties":{"isInternalError":{"type":"boolean","description":"When `true`, indicates an internal or timeout-style failure path at the server. May be omitted for other error types.","uniqueKey":"result._meta.isInternalError","typeLabel":"boolean"}},"uniqueKey":"result._meta","typeLabel":"object"}},"isRequired":true,"uniqueKey":"result","typeLabel":"object"}},"uniqueKey":"","typeLabel":"object"},"examples":{"list_skills_response":{"title":"list_skills_response","value":{"jsonrpc":"2.0","id":1,"result":{"content":[{"type":"text","text":"{\"skills\":[{\"key\":\"audience-comparison\",\"description\":\"Read this skill when the user asks to compare audiences or groups, contrast X vs Y, compare an attached audience, or explain similarities and differences.\"},{\"key\":\"audience-investigation\",\"description\":\"Read this skill when the user asks who to target, what audience to target, which audience is most likely to do or buy something, or how to target advertising, sponsorships, campaigns, or sales opportunities.\"},{\"key\":\"gwi-dictionary\",\"description\":\"Read this skill when the user asks what a GWI term or metric means, including responses, universe, audience percentage, data point percentage, or index.\"},{\"key\":\"segment-requests\",\"description\":\"Read this skill when the user asks for segments, segmentations, available segments, audience groups, market groups, or analysis of segment groups around a topic, location, or category.\"}]}"}],"structuredContent":{"skills":[{"key":"audience-comparison","description":"Read this skill when the user asks to compare audiences or groups, contrast X vs Y, compare an attached audience, or explain similarities and differences."},{"key":"audience-investigation","description":"Read this skill when the user asks who to target, what audience to target, which audience is most likely to do or buy something, or how to target advertising, sponsorships, campaigns, or sales opportunities."},{"key":"gwi-dictionary","description":"Read this skill when the user asks what a GWI term or metric means, including responses, universe, audience percentage, data point percentage, or index."},{"key":"segment-requests","description":"Read this skill when the user asks for segments, segmentations, available segments, audience groups, market groups, or analysis of segment groups around a topic, location, or category."}]}}}},"get_skills_response":{"title":"get_skills_response","value":{"jsonrpc":"2.0","id":2,"result":{"content":[{"type":"text","text":"{\"skills\":[{\"key\":\"audience-investigation\",\"content\":\"# Audience Investigation\\n\\n## Prerequisites\\n\\n- Call `list_datasets` when the dataset is unclear.\\n- Call `global_filters` before audience or insight tools on a new analysis.\\n- Create or resolve the audience with `audience_generation` when the user describes a cohort, or `search_audiences` when they name a saved audience.\\n- Use one `generate_insights` call with multiple focused prompts in `prompts` when the investigation spans several dimensions. Pass the same `enforced_audiences` from the generated or matched audience on that call.\\n- Use `explore_insight` only when the user explicitly asks for more detail on a returned `insights[].id`.\\n\\n## Instructions\\n\\nUse this skill when the user asks who they should target, what audience they should target to sell or promote something, or which audience is more likely to do a specific behavior.\\n\\n1. Always create the target audience first with `audience_generation` (or resolve it with `search_audiences` when the user names a saved audience). The audience should represent the behavior or target group being investigated, such as \\\"luxury watch buyers\\\", \\\"eco-friendly apparel shoppers\\\", or \\\"people who buy premium skincare\\\".\\n2. Reuse that audience in `enforced_audiences` for every prompt in the `generate_insights` call. Do not investigate the general population when the user asked for a target audience.\\n3. Prefer one `generate_insights` call with multiple focused prompts in `prompts` rather than one broad prompt or several sequential `generate_insights` tool calls. Each prompt should cover one investigation dimension. Use additional `generate_insights` tool calls only when scope differs per call (for example different `wave_codes` for period comparison or different `location_codes` for market comparison).\\n4. Useful investigation dimensions include demographics and overindex patterns, behaviors and interests, lifestyle indicators, media consumption, social media usage, purchase drivers, and decision factors.\\n5. Focus on what differentiates the audience. Prefer overindex relationships and clear contrasts against the general population when useful.\\n\\n## Examples\\n\\n- User asks: \\\"What audience should I target to sell luxury watches?\\\"\\n- Create audience: \\\"luxury watch buyers\\\".\\n- Run one `generate_insights` call with separate prompts such as \\\"demographics and overindex patterns\\\", \\\"behaviors and interests\\\", \\\"social media usage\\\", and \\\"purchase drivers\\\", all with the same `enforced_audiences`.\\n\\n- User asks in one turn: \\\"Do Facebook users use Instagram Reels? What are they buying? Which media do they watch?\\\"\\n- After audience resolution, run one `generate_insights` call with three prompts in `prompts` (one per question) and the same `enforced_audiences`, `location_codes`, and `wave_codes`.\\n\\n## Rules\\n\\n- Never collapse an entire multi-dimension investigation into a single prompt when the user asked about distinct topics.\\n- Always pass the generated or matched audience in `enforced_audiences` for every prompt in the call.\\n- Do not chain several single-prompt `generate_insights` tool calls when one call with multiple prompts shares the same audience, location, and timeframe scope.\\n- Keep each prompt narrow and purposeful.\\n- If an audience is only a proxy, evaluate whether it captures the same core intent before proceeding.\"}]}"}],"structuredContent":{"skills":[{"key":"audience-investigation","content":"# Audience Investigation\n\n## Prerequisites\n\n- Call `list_datasets` when the dataset is unclear.\n- Call `global_filters` before audience or insight tools on a new analysis.\n- Create or resolve the audience with `audience_generation` when the user describes a cohort, or `search_audiences` when they name a saved audience.\n- Use one `generate_insights` call with multiple focused prompts in `prompts` when the investigation spans several dimensions. Pass the same `enforced_audiences` from the generated or matched audience on that call.\n- Use `explore_insight` only when the user explicitly asks for more detail on a returned `insights[].id`.\n\n## Instructions\n\nUse this skill when the user asks who they should target, what audience they should target to sell or promote something, or which audience is more likely to do a specific behavior.\n\n1. Always create the target audience first with `audience_generation` (or resolve it with `search_audiences` when the user names a saved audience). The audience should represent the behavior or target group being investigated, such as \"luxury watch buyers\", \"eco-friendly apparel shoppers\", or \"people who buy premium skincare\".\n2. Reuse that audience in `enforced_audiences` for every prompt in the `generate_insights` call. Do not investigate the general population when the user asked for a target audience.\n3. Prefer one `generate_insights` call with multiple focused prompts in `prompts` rather than one broad prompt or several sequential `generate_insights` tool calls. Each prompt should cover one investigation dimension. Use additional `generate_insights` tool calls only when scope differs per call (for example different `wave_codes` for period comparison or different `location_codes` for market comparison).\n4. Useful investigation dimensions include demographics and overindex patterns, behaviors and interests, lifestyle indicators, media consumption, social media usage, purchase drivers, and decision factors.\n5. Focus on what differentiates the audience. Prefer overindex relationships and clear contrasts against the general population when useful.\n\n## Examples\n\n- User asks: \"What audience should I target to sell luxury watches?\"\n- Create audience: \"luxury watch buyers\".\n- Run one `generate_insights` call with separate prompts such as \"demographics and overindex patterns\", \"behaviors and interests\", \"social media usage\", and \"purchase drivers\", all with the same `enforced_audiences`.\n\n- User asks in one turn: \"Do Facebook users use Instagram Reels? What are they buying? Which media do they watch?\"\n- After audience resolution, run one `generate_insights` call with three prompts in `prompts` (one per question) and the same `enforced_audiences`, `location_codes`, and `wave_codes`.\n\n## Rules\n\n- Never collapse an entire multi-dimension investigation into a single prompt when the user asked about distinct topics.\n- Always pass the generated or matched audience in `enforced_audiences` for every prompt in the call.\n- Do not chain several single-prompt `generate_insights` tool calls when one call with multiple prompts shares the same audience, location, and timeframe scope.\n- Keep each prompt narrow and purposeful.\n- If an audience is only a proxy, evaluate whether it captures the same core intent before proceeding.\n"}]}}}},"get_skills_unknown_key":{"title":"get_skills_unknown_key","value":{"jsonrpc":"2.0","id":2,"result":{"isError":true,"content":[{"type":"text","text":"unknown skill \"missing-skill\""}]}}},"explore_datasets_response":{"title":"explore_datasets_response","value":{"jsonrpc":"2.0","id":10,"result":{"content":[{"type":"text","text":"{\"datasets\":[{\"code\":\"ds-core\",\"name\":\"GWI Core\",\"summary\":\"Our primary data set on the attitudes and behaviors of digital consumers\",\"url\":\"https://help.globalwebindex.com/en/collections/11937099-gwi-core\"},{\"code\":\"ds-usa\",\"name\":\"GWI USA\",\"summary_error\":\"summary unavailable\"}]}"}],"structuredContent":{"datasets":[{"code":"ds-core","name":"GWI Core","summary":"Our primary data set on the attitudes and behaviors of digital consumers","url":"https://help.globalwebindex.com/en/collections/11937099-gwi-core"},{"code":"ds-usa","name":"GWI USA","summary_error":"summary unavailable"}]}}}},"explore_taxonomy_response":{"title":"explore_taxonomy_response","value":{"jsonrpc":"2.0","id":11,"result":{"content":[{"type":"text","text":"{\"dataset\":{\"code\":\"ds-core\",\"name\":\"GWI Core\"},\"audiences\":[],\"questions\":[{\"label\":\"Social media behaviors\",\"description\":\"Which social media behaviors apply to you?\"}],\"attributes\":[{\"text\":\"Uses TikTok daily\"}],\"message\":\"\"}"}],"structuredContent":{"dataset":{"code":"ds-core","name":"GWI Core"},"audiences":[],"questions":[{"label":"Social media behaviors","description":"Which social media behaviors apply to you?"}],"attributes":[{"text":"Uses TikTok daily"}],"message":""}}}},"global_filters_response":{"title":"global_filters_response","value":{"jsonrpc":"2.0","id":4,"result":{"content":[{"type":"text","text":"{\"global_filters\":{\"location_codes\":[\"s2_44\"],\"location_names\":[\"UK\"],\"wave_codes\":[\"q1_2025\"],\"wave_names\":[\"Q1 2025\"]}}"}],"structuredContent":{"global_filters":{"location_codes":["s2_44"],"location_names":["UK"],"wave_codes":["q1_2025"],"wave_names":["Q1 2025"]}}}}},"global_filters_partial_access":{"title":"global_filters_partial_access","value":{"jsonrpc":"2.0","id":4,"result":{"content":[{"type":"text","text":"{\"global_filters\":{\"inaccessible_location_names\":[\"Albania\"],\"location_codes\":[\"s2_30\"],\"location_names\":[\"Greece\"],\"wave_codes\":[\"q3_2025\",\"q4_2025\",\"q1_2026\",\"q2_2026\"],\"wave_names\":[]}}"}],"structuredContent":{"global_filters":{"inaccessible_location_names":["Albania"],"location_codes":["s2_30"],"location_names":["Greece"],"wave_codes":["q3_2025","q4_2025","q1_2026","q2_2026"],"wave_names":[]}}}}},"audience_generation_response":{"title":"audience_generation_response","value":{"jsonrpc":"2.0","id":5,"result":{"content":[{"type":"text","text":"{\"audiences\":[{\"datasets\":[\"ds-core\"],\"description\":\"This audience consists of individuals who are part of Gen Z.\",\"id\":\"259f6394-436c-4801-b83b-bbc926e8b4b9\",\"name\":\"Generation: Gen Z\"}]}"}],"structuredContent":{"audiences":[{"datasets":["ds-core"],"description":"This audience consists of individuals who are part of Gen Z.","id":"259f6394-436c-4801-b83b-bbc926e8b4b9","name":"Generation: Gen Z"}]}}}},"audience_generation_all_failed":{"title":"audience_generation_all_failed","value":{"jsonrpc":"2.0","id":5,"result":{"content":[{"type":"text","text":"{\"audiences\":[],\"failed_audiences\":{\"mars explorers\":\"no relevant attributes found for the terms: mars explorers: audience not found\"}}"}],"structuredContent":{"audiences":[],"failed_audiences":{"mars explorers":"no relevant attributes found for the terms: mars explorers: audience not found"}}}}},"generate_insights_response":{"title":"generate_insights_response","value":{"jsonrpc":"2.0","id":7,"result":{"content":[{"type":"text","text":"{\"results\":[{\"prompt\":\"social media habits\",\"has_more_insights\":true,\"inaccessible_locations\":[],\"insights\":[{\"id\":\"95c35f2c-9235-4536-ad46-44867a3a5996\",\"text\":\"9.5% of Gen Z are social media scrollers, making them 100% more likely to do so than the average person.\",\"url\":\"https://platform.globalwebindex.com/chart-builder/insights-v2/95c35f2c-9235-4536-ad46-44867a3a5996\"}],\"message\":\"Based on the prompt social media habits, the Insights tool generated the following insights:\",\"sources\":{\"audiences\":[{\"description\":\"This audience consists of individuals who are part of Gen Z.\",\"id\":\"259f6394-436c-4801-b83b-bbc926e8b4b9\",\"name\":\"Generation: Gen Z\"}],\"datasets\":[{\"code\":\"ds-core\",\"name\":\"GWI Core\"}],\"locations\":[{\"code\":\"s2_44\",\"name\":\"UK\"}],\"topics\":[\"social media habits\"],\"waves\":[{\"code\":\"q1_2025\",\"name\":\"Q1 2025\"}]},\"state_id\":\"f08cef8d-1995-4097-9d6e-0d1a5ccddd40\"}]}"}],"structuredContent":{"results":[{"prompt":"social media 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of questions from GWI Core\",\"sample\":248,\"universe_size\":1330784},{\"answer\":\"I am a social media scroller.\",\"index\":200.39999389648438,\"percentage\":9.5,\"question\":\"This data is auto-generated based on responses to a variety of questions from GWI Core\",\"sample\":185,\"universe_size\":978191}],\"audiences\":[{\"description\":\"This audience consists of individuals who are part of Gen Z.\",\"id\":\"259f6394-436c-4801-b83b-bbc926e8b4b9\",\"title\":\"Generation: Gen Z\"}],\"datasets\":[{\"description\":\"Our primary data set on the attitudes and behaviors of digital consumers\",\"id\":\"ds-core\",\"title\":\"GWI Core\",\"url\":\"https://help.globalwebindex.com/en/collections/11937099-gwi-core\"}],\"location_groups\":[{\"details\":{\"description\":\"Europe\",\"locations\":[{\"id\":\"s2_44\",\"name\":\"UK\"}]},\"group\":\"Europe\"}],\"timeframe_groups\":[{\"details\":{\"description\":\"2025 (Q1)\",\"timeframes\":[{\"id\":\"q1_2025\",\"name\":\"Q1 2025\"}]},\"group\":\"2025 (Q1)\"}]},\"text\":\"9.5% of Gen Z are social media scrollers, making them 100% more likely to do so than the average person.\",\"title\":\"GWI Insight\"}"}],"structuredContent":{"id":"95c35f2c-9235-4536-ad46-44867a3a5996","title":"GWI Insight","text":"9.5% of Gen Z are social media scrollers, making them 100% more likely to do so than the average person.","metadata":{"attributes":[{"answer":"I am a social learner.","index":177.89999389648438,"percentage":16.899999618530273,"question":"This data is auto-generated based on responses to a variety of questions from GWI Core","sample":327,"universe_size":1737501},{"answer":"I am a Social TV Viewer.","index":130.5,"percentage":14.600000381469727,"question":"This data is auto-generated based on responses to a variety of questions from GWI Core","sample":287,"universe_size":1504625},{"answer":"I am interested in the data generated from responses to questions about memers in GWI 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America\",\"type\":\"dataset\"},{\"code\":\"ds-zqy-gyv\",\"name\":\"GWI Kids\",\"description\":\"Our data set on the attitudes and behaviors of kids aged 8-15.\",\"type\":\"dataset\"}]}"}],"structuredContent":{"datasets":[{"code":"ds-core","name":"GWI Core","description":"Our primary data set on the attitudes and behaviors of digital consumers","type":"dataset","children":[{"id":446,"name":"GWI Syndicated","type":"folder","children":[{"code":"ds-work","name":"GWI Work","description":"Attitudes and behaviors of business professionals in the workplace","type":"dataset"},{"id":435,"name":"GWI Pulse","type":"folder","children":[{"code":"ds-gwi-gwi-jos","name":"July 2026 Pulse Week 1 (USA)","description":"FIFA World Cup 2026, AI Saturation, NBA Finals, AI","type":"dataset"}]}]}]},{"code":"ds-usa","name":"GWI USA","description":"A 360-degree view of today's America","type":"dataset"},{"code":"ds-zqy-gyv","name":"GWI Kids","description":"Our data set on the attitudes and behaviors of kids 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