callDataAnalyst
ChatGPTDelegate cross-source data analysis to a specialized Data Analyst sub-agent. The sub-agent runs internal tools in parallel (experiments, campaigns, research, personas, optional web search), evaluates findings through the Magnitude / Confidence / Consistency framework, and returns an answer-first synthesis. Heavy path (~20-60s); suited to questions that require connecting dots across sources rather than a direct single-source lookup. Suited for: - Cross-experiment / cross-campaign synthesis ("what works across all our tests?", "what drives our audience?") - "Which variant won?" / "How did experiment X perform?" / "What was the uplift?" - Cross-source correlation (performance + research + persona) - Strategic / "so what" questions, root-cause analysis, conflict resolution Returned fields: - core_finding: one-sentence lead fact with an inline citation ref. - performance_evidence: prose summary of experiment + campaign findings, with inline citation refs and scope qualifiers. - contextual_evidence: prose summary of research + persona findings, with inline refs and segment qualifiers. - synthesis_status: "Alignment" / "Conflict" / "Gap" between sources. - synthesis_analysis: strategic "so what" synthesis with inline refs. - sources: structured citation entries for the refs ([E1] experiments, [C2] campaigns, [R3] research, [I4] interviews) actually cited in the prose fields. Each entry carries title and objectId; experiments may additionally include a deep-link URL when available, and research/interview entries may include sourceSummary, researchData, and sourceReference.
callDataAnalyst
ChatGPTDelegate cross-source data analysis to a specialized Data Analyst sub-agent. The sub-agent runs internal tools in parallel (experiments, campaigns, research, personas, optional web search), evaluates findings through the Magnitude / Confidence / Consistency framework, and returns an answer-first synthesis. Heavy path (~20-60s); suited to questions that require connecting dots across sources rather than a direct single-source lookup. Suited for: - Cross-experiment / cross-campaign synthesis ("what works across all our tests?", "what drives our audience?") - "Which variant won?" / "How did experiment X perform?" / "What was the uplift?" - Cross-source correlation (performance + research + persona) - Strategic / "so what" questions, root-cause analysis, conflict resolution Returned fields: - core_finding: one-sentence lead fact with an inline citation ref. - performance_evidence: prose summary of experiment + campaign findings, with inline citation refs and scope qualifiers. - contextual_evidence: prose summary of research + persona findings, with inline refs and segment qualifiers. - synthesis_status: "Alignment" / "Conflict" / "Gap" between sources. - synthesis_analysis: strategic "so what" synthesis with inline refs. - sources: structured citation entries for the refs ([E1] experiments, [C2] campaigns, [R3] research, [I4] interviews) actually cited in the prose fields. Each entry carries title and objectId; experiments may additionally include a deep-link URL when available, and research/interview entries may include sourceSummary, researchData, and sourceReference.
callDataAnalyst
ChatGPTDelegate cross-source data analysis to a specialized Data Analyst sub-agent. The sub-agent runs internal tools in parallel (experiments, campaigns, research, personas, optional web search), evaluates findings through the Magnitude / Confidence / Consistency framework, and returns an answer-first synthesis. Heavy path (~20-60s); suited to questions that require connecting dots across sources rather than a direct single-source lookup. Suited for: - Cross-experiment / cross-campaign synthesis ("what works across all our tests?", "what drives our audience?") - "Which variant won?" / "How did experiment X perform?" / "What was the uplift?" - Cross-source correlation (performance + research + persona) - Strategic / "so what" questions, root-cause analysis, conflict resolution Returned fields: - core_finding: one-sentence lead fact with an inline citation ref. - performance_evidence: prose summary of experiment + campaign findings, with inline citation refs and scope qualifiers. - contextual_evidence: prose summary of research + persona findings, with inline refs and segment qualifiers. - synthesis_status: "Alignment" / "Conflict" / "Gap" between sources. - synthesis_analysis: strategic "so what" synthesis with inline refs. - sources: structured citation entries for the refs ([E1] experiments, [C2] campaigns, [R3] research, [I4] interviews) actually cited in the prose fields. Each entry carries title and objectId; experiments may additionally include a deep-link URL when available, and research/interview entries may include sourceSummary, researchData, and sourceReference.
callHeatseekerAIAgent
ChatGPTHeatseeker's marketing-consultant sub-agent. Has scoped access to the workspace's experiments, campaigns, research, personas, brand voice, inline image attachments, and competitive landscape — plans and runs internal read-only tools to answer. Suited for: - Strategic recommendations or persona-aware interpretation grounded in the workspace's data - Cross-source synthesis across experiments, campaigns, research, and personas - Creative deliverables in the workspace's brand voice (ad copy, briefs, landing pages, positioning) - Multi-turn conversations with carried context (up to 20 messages) Higher latency and cost than direct data-retrieval tools. Attachments: inline base64, max 5 per call, 5 MB each, 20 MB total.
callHeatseekerAIAgent
ChatGPTHeatseeker's marketing-consultant sub-agent. Has scoped access to the workspace's experiments, campaigns, research, personas, brand voice, inline image attachments, and competitive landscape — plans and runs internal read-only tools to answer. Suited for: - Strategic recommendations or persona-aware interpretation grounded in the workspace's data - Cross-source synthesis across experiments, campaigns, research, and personas - Creative deliverables in the workspace's brand voice (ad copy, briefs, landing pages, positioning) - Multi-turn conversations with carried context (up to 20 messages) Higher latency and cost than direct data-retrieval tools. Attachments: inline base64, max 5 per call, 5 MB each, 20 MB total.
callHeatseekerAIAgent
ChatGPTHeatseeker's marketing-consultant sub-agent. Has scoped access to the workspace's experiments, campaigns, research, personas, brand voice, inline image attachments, and competitive landscape — plans and runs internal read-only tools to answer. Suited for: - Strategic recommendations or persona-aware interpretation grounded in the workspace's data - Cross-source synthesis across experiments, campaigns, research, and personas - Creative deliverables in the workspace's brand voice (ad copy, briefs, landing pages, positioning) - Multi-turn conversations with carried context (up to 20 messages) Higher latency and cost than direct data-retrieval tools. Attachments: inline base64, max 5 per call, 5 MB each, 20 MB total.
chatWithPersonaAgent
ChatGPTChat with a specific persona in a workspace. The persona agent has knowledge from experiments, campaigns, research, and persona brain modules, and answers questions from the persona's perspective with insights grounded in their background and learnings. Suited for: - Direct conversation with a specific persona - Persona-perspective interpretation of marketing data - Insights grounded in the persona's background, interests, and learned behaviors Requires a personaId, which is surfaced by the listPersonas tool. Messages are text-only (no attachments). Up to 20 messages for multi-turn context.
chatWithPersonaAgent
ChatGPTChat with a specific persona in a workspace. The persona agent has knowledge from experiments, campaigns, research, and persona brain modules, and answers questions from the persona's perspective with insights grounded in their background and learnings. Suited for: - Direct conversation with a specific persona - Persona-perspective interpretation of marketing data - Insights grounded in the persona's background, interests, and learned behaviors Requires a personaId, which is surfaced by the listPersonas tool. Messages are text-only (no attachments). Up to 20 messages for multi-turn context.
chatWithPersonaAgent
ChatGPTChat with a specific persona in a workspace. The persona agent has knowledge from experiments, campaigns, research, and persona brain modules, and answers questions from the persona's perspective with insights grounded in their background and learnings. Suited for: - Direct conversation with a specific persona - Persona-perspective interpretation of marketing data - Insights grounded in the persona's background, interests, and learned behaviors Requires a personaId, which is surfaced by the listPersonas tool. Messages are text-only (no attachments). Up to 20 messages for multi-turn context.
getAllExperiments
ChatGPTLists completed and published experiments in the workspace, sorted with the newest first. Can filter by title (case-insensitive substring match) or experimentId (exact match). By default returns only live experiments. Use experimentType to include synthetic or all. Returns a summary including ID, title, variant performance data, and isSimulation flag. Supports pagination via 'limit' and 'skip'.
getAllExperiments
ChatGPTLists completed and published experiments in the workspace, sorted with the newest first. Can filter by title (case-insensitive substring match) or experimentId (exact match). By default returns only live experiments. Use experimentType to include synthetic or all. Returns a summary including ID, title, variant performance data, and isSimulation flag. Supports pagination via 'limit' and 'skip'.
getAllExperiments
ChatGPTLists completed and published experiments in the workspace, sorted with the newest first. Can filter by title (case-insensitive substring match) or experimentId (exact match). By default returns only live experiments. Use experimentType to include synthetic or all. Returns a summary including ID, title, variant performance data, and isSimulation flag. Supports pagination via 'limit' and 'skip'.
getTopAds
ChatGPTReturns a flat, pre-sorted list of imported campaign ads (META / LINKEDIN) ranked by any metric, with full creative info. Does NOT include Heatseeker experiment variants. Suited for top/bottom N ads by metric, best/worst performing ads, image vs video comparison (filter via isVideo), or ads in a specific time window (with dateRange).
getTopAds
ChatGPTReturns a flat, pre-sorted list of imported campaign ads (META / LINKEDIN) ranked by any metric, with full creative info. Does NOT include Heatseeker experiment variants. Suited for top/bottom N ads by metric, best/worst performing ads, image vs video comparison (filter via isVideo), or ads in a specific time window (with dateRange).
getTopAds
ChatGPTReturns a flat, pre-sorted list of imported campaign ads (META / LINKEDIN) ranked by any metric, with full creative info. Does NOT include Heatseeker experiment variants. Suited for top/bottom N ads by metric, best/worst performing ads, image vs video comparison (filter via isVideo), or ads in a specific time window (with dateRange).
listPersonas
ChatGPTList all personas in a workspace. Returns each persona's ID, name, title, summary, location, age, and interest. The persona ID is the input that chatWithPersonaAgent expects.
listPersonas
ChatGPTList all personas in a workspace. Returns each persona's ID, name, title, summary, location, age, and interest. The persona ID is the input that chatWithPersonaAgent expects.
listPersonas
ChatGPTList all personas in a workspace. Returns each persona's ID, name, title, summary, location, age, and interest. The persona ID is the input that chatWithPersonaAgent expects.
searchCampaignHistory
ChatGPTSearch the workspace's imported campaign history (META / LINKEDIN) and return campaigns with nested ad variants, metrics, creative info, and aggregate totals. Uses semantic search when variant is provided. Suited for: - "show me my campaigns", "spend this month", "compare campaigns / which underperforming" - "active last week" or other time-windowed queries (with dateRange) - "campaigns about X" / theme-based queries (with variant for semantic match)
searchCampaignHistory
ChatGPTSearch the workspace's imported campaign history (META / LINKEDIN) and return campaigns with nested ad variants, metrics, creative info, and aggregate totals. Uses semantic search when variant is provided. Suited for: - "show me my campaigns", "spend this month", "compare campaigns / which underperforming" - "active last week" or other time-windowed queries (with dateRange) - "campaigns about X" / theme-based queries (with variant for semantic match)
searchCampaignHistory
ChatGPTSearch the workspace's imported campaign history (META / LINKEDIN) and return campaigns with nested ad variants, metrics, creative info, and aggregate totals. Uses semantic search when variant is provided. Suited for: - "show me my campaigns", "spend this month", "compare campaigns / which underperforming" - "active last week" or other time-windowed queries (with dateRange) - "campaigns about X" / theme-based queries (with variant for semantic match)
searchWorkspaces
ChatGPTSearch workspaces by name or list workspaces the caller belongs to. When query is empty, returns the caller's workspaces. When query is provided, searches by name. Each result includes the workspaceId required by other tools in this server.
searchWorkspaces
ChatGPTSearch workspaces by name or list workspaces the caller belongs to. When query is empty, returns the caller's workspaces. When query is provided, searches by name. Each result includes the workspaceId required by other tools in this server.
searchWorkspaces
ChatGPTSearch workspaces by name or list workspaces the caller belongs to. When query is empty, returns the caller's workspaces. When query is provided, searches by name. Each result includes the workspaceId required by other tools in this server.
