io.github.MCFLAMINGO/local-intel

START HERE. Natural language entry point — send any plain-English question about any Florida market and get a structured answer. Auto-detects ZIP, industry vertical, and routes to the right tool. No tool knowledge required. Examples: "Is 32082 oversaturated with dentists?", "Where should I open a clinic in Northeast Florida?", "What food gaps exist in Nocatee?" Trained on 500+ real market queries across restaurant, healthcare, retail, construction, and real estate verticals.

Full spatial context block for a zip or lat/lon. Returns anchor business, nearby businesses in distance rings, zone intelligence, and category breakdown. Best first call for any location query.

Search businesses by name, category, or semantic group (food, retail, health, finance, civic, services).

Find businesses within a radius of any lat/lon point, sorted by distance with compass bearing.

Spending zone and demographic data for a ZIP code: population, income, home value, rent, ownership rate, zone score.

Businesses along a named street corridor. Use for queries like "what is on A1A" or "businesses on Palm Valley Road".

Recently added or owner-verified business listings. Use to detect new openings or data updates.

Dataset coverage stats: total businesses, confidence scores, query volume, revenue earned.

Tidal reading for a ZIP — temperature (0-100), direction (surging/heating/stable/cooling/receding), seasonal context. Synthesizes all 4 data layers. Best for agents deciding WHERE to act next.

Investment and activity signal for a ZIP. Composite score 0-100 with band (strong_buy/accumulate/hold/reduce/avoid), top reasons, and avoid flags. Best for real estate and financial agents.

Infrastructure momentum score and active leading indicators for a ZIP from Layer 0. Permits, road projects, flood zones, utility extensions. Predicts conditions 12-36 months ahead. 'Let Google pay for the satellites — we sell the weather forecast.'

PREMIUM composite entry point ($0.05). Declare your agent_type and intent, receive pre-ranked top-10 signals assembled from all 4 data layers, personalized for your use case. Includes delta since your last query if agent_id provided. Best first call for any new agent.

Pre-baked economic oracle for a ZIP. Returns: restaurant saturation (is there room for another?), price-tier gap analysis (what menu price is missing?), growth trajectory (growing/empty-nest/stable), and 3 pre-formed questions with answers baked in. No LLM needed — answers derived from population, income, business density, school count, and infrastructure signals.

Ranked sector gap analysis for a ZIP. Identifies NAICS sectors present at county level but absent at ZIP — the structural whitespace in a local economy. Returns ranked opportunities with: NAICS code, sector label, county employment share, demand estimate, confidence tier, and LLM-ready signal narrative. Backed by ZBP 2018 (ZIP-level establishment counts), CBP 2023 (county-level sector health), and ACS 5-yr 2023 demographics. Example output: "NAICS 61 Educational Services: 0 establishments in 32259 vs 47 in St. Johns County. 69,866 residents, $144k median HHI, 89% owner-occupied. Estimated demand: 8–12 tutoring/enrichment centers. Confidence: ESTIMATED. Signal: Strong family formation market with no educational services presence." Use oracle_vertical field to chain into matching vertical agents. Cost: $0.03 pathUSD. Free discovery feed at /api/sector-gap/feed.

Real estate intelligence for a ZIP. Ask natural-language questions: demographics, commercial gaps, flood risk, school proximity, infrastructure signals, market saturation. Returns structured data with confidence score. Trained on 100 realtor use-case prompts.

Healthcare market intelligence for a ZIP. Ask about provider density, patient demographics, demand gaps, senior population. Returns structured data with confidence score. Trained on 100 healthcare business prompts.

Retail market intelligence for a ZIP. Ask about store categories, spending capture rates, consumer profile, undersupplied niches. Returns structured data with confidence score. Trained on 100 retail business prompts.

Construction and home services market intelligence for a ZIP. Ask about contractor density, active permits, housing starts, population growth driving demand. Returns structured data with confidence score. Trained on 100 construction business prompts.

Restaurant and food service market intelligence for a ZIP. Ask about saturation scores, price-tier gaps, capture rates, corridor analysis, tidal momentum. Returns structured data with confidence score. Trained on 100 restaurant business prompts.

Composite NL query layer. Ask any plain-English question about a ZIP — demographics, market opportunity, restaurant gaps, retail saturation, construction activity, investment signals, healthcare, corridor analysis, recent changes, nearby businesses. Routes internally to the right tools and returns a synthesized, sourced answer with confidence score. Best single entry point for humans and LLMs.

Compare up to 10 ZIP codes side-by-side and get a ranked opportunity table. Returns per-ZIP signals (HHI, capture rate, infra momentum, consumer profile, top gap) plus a top_pick recommendation with reasoning. Best tool for site selection, franchise expansion, investment screening, and market prioritization.

Project-type intelligence: pass a project_type (restaurant, clinic, banking, construction, real_estate, residential_development, fitness, legal, retail, auto, etc.) and get L1 ZIPs ranked by market or residential opportunity score plus L2 matching verified businesses already operating in that sector. Returns sector gap counts, HHI, population, growth state, and new-build %. Best tool for site selection and franchise expansion when you know the business type but not the ZIP.

Post a job request to local businesses or drivers. Supports delivery (first-to-accept) and proposal (collect quotes) modes. Set autonomy=full for agent-only flow, approve for human confirmation, human for manual selection. Returns rfq_id to poll with local_intel_rfq_status.

Poll the status of an RFQ. Returns the original request, all responses received so far, and booking details if booked.

Book a specific response to an RFQ — confirms the job with that business. Use after reviewing local_intel_rfq_status responses.

Decline a specific response to an RFQ and get the next in queue. Use when a client rejects the first responder — returns the next pending response automatically. First come first served queue.

Mark a booked job as complete. Triggers escrow release in v2. Call when the job is done.