Fodda Knowledge Graphs

Use when seeking candidate AI-powered Human Agent (Digital Twin) expert models or Synthetic Analysts across specialized domains or research questions (e.g. 'Who has expertise in luxury retail?' or 'What would consumer culture analysts say about this?'). Searches Fodda's catalog of 4,000+ domain specialists to return 2–3 ranked expert models with their analytical focus, methodology, credibility anchors, and expert ID for consultation via consult_human_agent or consult_analyst.

Translate cultural trends, brand challenges, and consumer insights into a 2026 Strategy-to-Activation Comms & Retail Media Plan. Generates an agency-grade media deliverable with T1-T5 tasks, 3-layer shopper audience cards (with mandatory exclusions), Amazon/Walmart digital shelf intelligence, tactical placement tables with [LIVE] provenance tags, and a machine-readable activation manifest.

Create a presentation-ready data visualization from research findings. Available chart types: "cultural_shifts" (From→To transitions), "competitive_compass" (brands on 2 axes), "trend_constellation" (network of related trends), "implication_ladder" (Signal→Trend→So What→Do What), "innovation_pathway" (Now→Near-Term→Future), "opportunity_map" (2×2 white space analysis). Returns a branded SVG that renders directly in the chat. (Data payload transformation + SVG chart rendering.)

Returns Fodda's capabilities, semantic research workflows, Human Agents (Human Agents), and pricing. Call this for any question about what Fodda can do, how experts work, available research recipes, or pricing. Sibling routing: Use get_capabilities to discover platform features and workflow recipes; use list_graphs to list specific data graphs; use list_analysts to discover expert personas. Returns platform overview, active specialist counts, workflow descriptions, and published offerings.

The canonical per-ticker earnings source for 517 covered companies. - view='snapshot' (default): Full quarterly record including headline, financial metrics, analyst sentiment, strategic activity, CEO quotes, and top Q&A entries. - view='qa': Itemized analyst Q&A session with verbatim analyst questions, analyst names, analyst firms, executive responses, and response directness. USE THIS VIEW whenever the user asks who asked a question, for analyst names/firms, or for verbatim call quotes. - view='history': Narrative quarterly timeline. - view='compare': Side-by-side comparison of 2-5 tickers.

Step 4a in standard Human Agent onboarding: retrieves detected expertise themes and verified public findings for expert review before locking. Use after submit_expertise_analysis to present themes and cited public articles to the expert for approval. Prerequisite: submit_expertise_analysis must be completed first. Workflow sequence: Present the findings to the expert to flag inaccurate items, select 2-3 core themes, and then proceed to confirm_themes. Returns an array of detected theme objects and verified research findings with citation URLs.

Search PSFK-curated domain graphs (travel & hospitality, retail, tech, beauty, fashion, sports, food & beverage) for trend intelligence with bundled evidence. No graph ID needed — searches all 7 live domain graphs in parallel. Returns expert-curated trends with bundled evidence including brand case studies, statistics, executive quotes and analysis with source attribution. Sibling routing: Use get_domain_intelligence when exploring broad consumer culture across the primary retail/consumer domains without needing a graphId; use search_graph to query the broader catalog of 100+ specialist partne…

Surfaces strategic deflection and narrative tension by comparing Wall Street analyst questions against executive responses across quarterly earnings calls. Use when investigating corporate transparency, executive dodge/deflection patterns, or uncovering unaddressed operational risks (e.g., 'Where are retail CEOs deflecting analyst questions on margin pressure?', 'Show analyst-management divergence for hospitality brands'). Sibling routing: Use get_company_earnings for standard single-ticker quarterly records and get_earnings_intelligence for multi-company strategic initiatives; use get_earning…

Cross-company thematic earnings intelligence from the knowledge graph and web sources. Use for multi-company comparisons ("what are hotel companies saying about labor costs?"), industry-level queries, sector filters, or strategic corporate activity categories (activity: "sustainability" | "marketing" | "retail" | "technology"). For corporate ESG, circular economy, and climate initiatives (e.g. "What sustainability commitments did apparel companies make this quarter?"), pass activity="sustainability" or rely on server-side intent routing to avoid conflation with analyst margin sustainability qu…

Evidence citation lookup: retrieves primary evidence articles, publisher case studies, data points, and source URLs that validate a specific trend node. Prerequisite: Requires a valid for_node_id and graphId obtained from a prior search_graph or get_neighbors call. Use when backing a specific trend with original reporting, verifying publisher citations, or extracting concrete brand examples. Sibling routing: Use search_graph first to discover trends and retrieve their node_id; use get_evidence to inspect the underlying source citations for that node; use get_node for high-level metadata; use s…

[Deprecated: Legacy alias of get_specialist_intelligence. Prefer search_graph for topic-routed multi-graph searches, or consult_human_agent / consult_analyst for direct strategist consultation.] Parallel search across specialist strategist knowledge graphs curated by domain strategists and boutique studios (culture, youth trends, commerce, media). Sibling routing: For consumer domain trends use get_domain_intelligence; for standalone statistics use search_statistics; for direct 1-on-1 expert advisory use consult_human_agent. Returns structured specialist frameworks, strategic commentary, and c…

Certified multi-source evidence dossier generator: synthesizes domain knowledge graph case studies, consulting report findings (PwC, McKinsey, DHL), expert quotes, and live macroeconomic data (FRED, BLS, Census) into a comprehensive intelligence dossier in a single synchronous call. Use when preparing client pitch decks, executive briefings, or comprehensive topic overviews (e.g., 'Build an evidence dossier on sustainable luxury packaging'). Optionally generates an executive 4-beat journalistic briefing (include_editorial: true). Sibling routing: Use get_intelligence_dossier for instant, singl…

List unique taxonomy entity values (brands, locations, technologies, audiences) or retrieve the complete table of contents for small, discrete report graphs (<40 trends, e.g. DHL, PwC, or Mintel radars) where search may return partial results. Returns up to 100 unique values ordered alphabetically. Sibling routing: DO NOT use this tool for thematic or topic research (e.g. 'find AI trends' or 'what trends are in tech?') on large domain graphs (tech, retail, cpg), because it caps at 100 items alphabetically without evidence or signals; use search_graph or get_domain_intelligence instead for sema…

Check the current user's account status: API call balance, plan, enabled/disabled graphs, and profile info. Use when the user asks "how many API calls do I have?", "what plan am I on?", "what graphs can I access?", or similar account questions. Returns live data — not cached from session start. (User account status & credit balance lookup.)

Check creator revenue share and consultation earnings balance for an authenticated Human Agent on Fodda. Use when an expert creator asks about their earnings, consultation fees, or royalty payouts (e.g., 'How much have I earned on Fodda?', 'Check my expert payout balance'). Requires an authenticated expert account. Sibling routing: This tool is strictly for human creator monetization—do NOT use for public company SEC filings or corporate earnings (use get_company_earnings for per-ticker records or get_earnings_intelligence for multi-company comparisons). Returns creator financial status includ…

Discover what's connected to a specific trend — related brands, technologies, locations, and cross-domain links. Returns curated editorial connections between trends. Use after search_graph to map the territory around a trend, find which brands are connected, or understand cross-domain relationships. Requires node_id from a prior search_graph result. (1-hop graph relationship traversal from seed node in Neo4j.)

Get the full profile of a specific trend — detailed description, lifecycle stage (emerging/building/mature), signal strength, geographic scope, and all properties. Use when you need deeper detail on a single trend after search_graph returned a summary. Requires node_id from a prior search_graph result. (Direct Neo4j node metadata lookup by ID.)

Status and progress checker for Human Agent onboarding sessions: retrieves current milestone, active stage, and pending tasks. Supports holding connection (waitForResearch: true) for up to 25 seconds while background research completes. Use when monitoring onboarding progress or checking whether asynchronous background research has finished. Sibling routing: Use get_onboarding_status for expert onboarding tracking; use check_research_status for topic deep research; use check_deliverable_status for commissioned documents. Returns session status, completed steps, research_state, next_tool, and p…

Published corporate research and market forecast layer: searches industry report knowledge graphs (DHL, PwC, Unilever, Jack Morton, and specialist research firms) for published forecasts, projections, and whitepaper findings. Returns an executive 5-pillar analyst briefing by default with cross-graph validation. Does NOT return living consumer domain trends (use get_domain_intelligence) or standalone data points (use search_statistics). When the query names a specific company or brand, brand_tracker is the entry point. No graph ID needed.

[Deprecated: Prefer search_graph for topic-routed multi-graph searches, or consult_human_agent / consult_analyst for direct strategist and thinker consultation.] Proprietary strategist frameworks and niche domain intelligence layer: searches specialist knowledge graphs curated by domain strategists, newsletters, and boutique studios (culture, youth trends, commerce, media). Returns specialist frameworks and analysis; does not return broad consumer domain trends (use get_domain_intelligence) or standalone statistics (use search_statistics). When the query names a specific company or brand, bran…

Federated empirical data layer: queries 110+ live institutional and government feeds (FRED, BLS, US Census, World Bank, OECD, WTO, IMF PortWatch, etc.) for real-time macroeconomic indicators, demographic shifts, global trade flows, container shipping & port throughput, maritime chokepoints (Suez, Panama), and retail spending. When citing US retail sales, cite official Headline Retail & Food Services (NAICS 44X72 / FRED RSAFS, ~\$738B) as the primary retail figure; clearly distinguish from Retail Trade Excl. Food Services (NAICS 44000 / FRED RSXFS, ~\$646B). When citing consumer spending, repor…

Discovers consumer trends that have been empirically corroborated by corporate earnings reports in Fodda's cross-validation pipeline. Connects high-level cultural trend signals with corroborating executive statements and analyst Q&A from quarterly 10-Q/10-K earnings calls. Use when you need proof that an emerging consumer trend is impacting corporate P&L and executive strategy (e.g., 'Show consumer trends validated in recent beauty earnings calls'). Sibling routing: Use search_graph for pure cultural/consumer trend discovery; use get_company_earnings for full single-ticker filings; use get_val…

Catalog and discover all expert personas available on Fodda across 4 categories: living Human Agents (practitioners with Human Agent models), C-Suite Agents (corporate executive lenses grounded in earnings), Classic Agents (historical thinkers), and Synthetic Analysts (domain specialists). Use when exploring available experts, finding who to consult for a specific topic, or inspecting available specialist deliverables. Sibling routing: This tool lists and filters agents; to initiate an interactive conversation with a chosen specialist, call consult_human_agent (for living experts) or consult_a…

Catalog and discovery layer for Fodda knowledge graphs: lists all accessible knowledge graph IDs, topic vertical tags, author credentials, node counts, and signal metrics. Use first when discovering available domain libraries or when you need a valid graphId parameter for graph-scoped queries (e.g. "What knowledge graphs do you have on retail or sustainability?"). Sibling routing: Use list_graphs to inspect graph metadata and available sources; use search_graph to query trend content across graphs; use list_analysts to discover specialist Human Agents. Returns an array of graph profiles with g…

Use when a user asks to track a topic, monitor a competitor, or set up, list, update, pause, resume, or cancel recurring weekly/daily intelligence briefings delivered via email (e.g., 'Track sustainability shifts in luxury fashion every Monday', 'Pause my weekly retail digest'). Actions: 'create' registers a new schedule (requires query, email, cadence); 'list' returns all active schedules for the user; 'update' modifies query/cadence for schedule_id; 'pause' and 'resume' temporarily halt or restart delivery; 'cancel' permanently removes the schedule. Returns confirmation status, schedule_id, …

Test tool

Extract clean text content from any URL. Use this when a user shares a link (competitor site, news article, client brief, trend report) and wants to cross-reference it against Fodda knowledge graphs. Returns structured text ready for analysis.

Use when commissioning an executive document from an analyst or Human Agent—such as a strategic briefing, market memo, competitive assessment, or publication-ready article—rather than conversational chat (e.g., 'Have Ben Dietz write a strategic memo on retail media networks'). Workflow routing: Discover available analysts and their specific commissionable offerings first via list_analysts or consult them interactively via consult_human_agent / consult_analyst. Execution & follow-up: Requests may process asynchronously; returns a job_id that can be polled to completion using check_deliverable_s…

Use when a user wants to request a facilitated advisory introduction or 1-on-1 consultation with an On-Request Human Agent or active specialist across 4,150+ indexed topics, or when an expert does not maintain a direct public calendar link (e.g., 'I want to speak with Peter Abraham about bicycle retail strategy'). Sibling routing: Use consult_human_agent for immediate AI-driven consultation with active Human Agents; use find_expert to discover specialists; use request_expert_intro when the user seeks a human-to-human advisory introduction. Returns immediate request confirmation, concierge trac…

Returns a greeting.

Step 5 (final stage) in standard Human Agent onboarding: schedules or immediately dispatches a 5–10 minute voice interview with the Fodda AI interviewer on Google Meet to capture conversational tone, voice cadence, and contrarian perspectives. Prerequisite: confirm_themes must be completed first to generate the interview questionnaire. Sibling routing: This tool finalizes standard graph-backed expert onboarding; for Bring-Your-Own-MCP onboarding, use finalize_byo_mcp_onboarding instead (which does not require a voice interview). Returns meeting link, calendar confirmation, and next steps for g…

Search a specific Fodda knowledge graph to understand its contents and trends.

Narrative and qualitative evidence layer only: returns expert quotes, editorial analysis, and strategic perspectives from named strategists and industry leaders across all graphs, with source attribution and parent trend context. Sibling routing: Use search_insights when you need authoritative quotes and qualitative commentary; use search_statistics for numerical data points and market sizing; use consult_human_agent to speak interactively with an expert. Does NOT return raw statistics or market sizing.

Search for specific quantitative data points, numbers, and stats in a graph.

Forward user feedback, feature requests, complaints, or exit reasons to the Fodda team via email and Slack. Call this whenever a user shares feedback — including when they want to leave, report a problem, or suggest an improvement. (User feedback logging.)

Create a free Fodda Base account (100 API calls/month across ALL knowledge graphs) and send a confirmation email. GUARDRAIL: only call this AFTER the user has explicitly provided their email and asked to create an account — never sign someone up proactively or with an email inferred from earlier context. Can also pass profile fields (name, job_title, company). (User registration and free tier provision.)

Step 1b in Human Agent onboarding: registers expert profile details (name, role, knowledge area, consultation call rate, optional bio/headshot) and records explicit acceptance of Terms of Service and Privacy Policy. Prerequisite: The expert must review and explicitly accept Fodda Terms (https://www.fodda.ai/terms) and Privacy Policy (https://www.fodda.ai/privacy) with termsAccepted: true before progress can be saved. Workflow sequence: Advances to expert_onboarding_research for standard onboarding or submit_mcp_source for BYO-MCP. Returns basic_info_saved status and next step instructions.

Step 3 in standard Human Agent onboarding: submits the expert's structured voice study and domain expertise map derived from conversational analysis and public writing. Prerequisite: Must follow submit_basic_info and expert_onboarding_research. Workflow sequence: Submitting this analysis prepares the thematic taxonomy; immediately follow this call with get_detected_themes to review extracted themes. Sibling routing: This is for standard onboarding—BYO-MCP onboarding skips this step and uses submit_mcp_source instead. Returns submission confirmation and advances onboarding status to theme revie…

Step 2 in the Bring-Your-Own-MCP (BYO-MCP) expert onboarding flow: connects to and probes an external public HTTPS MCP endpoint to evaluate live tools and infer domain expertise for a Human Agent digital twin. Prerequisite: submit_basic_info must be called first. Alternative: If the expert does not have an external MCP endpoint, use the standard knowledge-graph path via expert_onboarding_research instead. Side effects: Sends an external live probe to the target MCP server to discover tools and capabilities; does not finalize onboarding until finalize_byo_mcp_onboarding is invoked. Returns disc…

User search scope preference manager: toggles inclusion or exclusion preferences for specific knowledge graphs (e.g., 'Don't include the sports graph in my searches', 'Re-enable the beauty graph'). Preferences persist across sessions in the user profile. Sibling routing: Use toggle_graph_preference to set permanent search filtering; use update_user_profile for general account context; pass explicit graphs or graphId directly on search_graph for one-off query overrides. Returns updated user graph preference state and confirmation status.

Save the user's research profile to improve the relevance of future responses. Call this after you understand the user's role, industry, and research needs. The profile persists across sessions — you only need to set it once, then update if their focus changes. Write BEHAVIORAL INSTRUCTIONS, not a bio. Format: one sentence of identity (who they are and how they use Fodda), then numbered directives that change how you synthesize and frame responses. Include: what evidence to prioritize, how to frame conclusions, geographic needs, and output structure preferences. Max 2000 chars per field. (User…

Use when verifying a factual claim, hypothesis, or strategic assertion against a named practitioner's curated knowledge graph via their AI-powered Human Agent (Digital Twin) model. Evaluates whether the practitioner's documented research and domain evidence supports or refutes the claim. If analyst_id is omitted, automatically routes to the most relevant active Human Agent covering the domain. Sibling routing: Use verify_claim to evaluate a claim against a specific practitioner's knowledge graph and receive a structured verdict; use verify_market_claim for multi-graph algorithmic 5-gate verifi…

Use when verifying a factual market claim against 100+ knowledge graphs, primary research citations, and corporate earnings divergence through 5 sequential kill-gates (grounding, contradiction, freshness, corroboration, divergence). Sibling routing: Use verify_market_claim for objective, multi-source empirical data verification and contradiction scoring; use verify_claim to evaluate a claim against a specific practitioner's curated knowledge graph via their AI-powered Human Agent model. Returns structured verdict ([VERIFIED], [REFUTED_BY_EVIDENCE], [INSUFFICIENT_EVIDENCE], [UNGROUNDED_SPECULAT…