riskmodels-app Privacy API

openapi: 3.2.0
info:
  title: RiskModels Privacy API
  version: 3.0.0-agent
  description: 'POST /decompose returns variance shares and ETF hedge ratios for any US equity, separating factor exposure from the residual bet so you can hedge what you don''t want. Daily history to 2000 across ~3,000 US equities.

    Precision equity risk intelligence platform with AI agent integration.


    **New in v3.0.0-agent:**

    - OAuth2 client credentials flow for machine-to-machine auth

    - Plaid Investments integration for live portfolio sync

    - MCP (Model Context Protocol) server for AI agent tools

    - Compliance manifests for AI marketplace integration

    - Per-key rate limiting and scoped access control


    **Data**: Universe `uni_mc_3000` (top ~3,000 US stocks by market cap), date range 2000 to present (deep panel; stock-specific skill series from ~2001 after warmup), updated daily end-of-day. Model outputs are computed by the ERM3 regression system (Huber/Ridge), with Zarr v2 archives on Google Cloud Storage for research pipelines. The live API reads primarily from Supabase **V3** tables: long-form `security_history` (returns, volatility, L1/L2/L3 hedge ratios and explained-risk metrics), wide latest rows in `security_history_latest`, identity in `symbols`, plus supporting surfaces such as `trading_calendar`, `erm3_landing_chart_cache`, and `macro_factors`. Cross-sectional **rankings** (`GET /rankings/*`) are served from precomputed rank metric keys in `security_history`, not a separate `erm3_rankings` table. Hedge ratios (`*_hr`) are **dollar_ratio** ETF notionals per $1 stock and are distinct from regression **betas** (`l1_mkt_beta`, `l2_sec_beta`, `l3_sub_beta`), which are dimensionless coefficients from the hierarchical L1/L2/L3 regression. Both are exposed under `MetricsV3` and on `security_history_latest`. See `SEMANTIC_ALIASES.md` for the full HR-vs-beta convention.


    **Authentication Methods:**

    1. Session cookies (web app)

    2. API Key/Secret via Bearer token (external integrations)

    3. OAuth2 client credentials (AI agents, npm package)


    **Security Features:**

    - GCP KMS envelope encryption for portfolio data

    - Cryptographic shredding on key deletion

    - HMAC-SHA256 webhook verification

    - Row-level security (RLS) via Supabase


    **Pricing**: Per-request billing with prepaid balance. Cached responses are free. Many metered responses include `_agent.cost_usd` in the JSON body; others bill silently — always check the `X-API-Cost-USD` response header when present. Metered operations also expose `x-pricing` (OpenAPI extension) with `capability_id`, `tier` (`baseline` | `premium`), `model`, `cost_usd`, `billing_code`, and optional `min_charge` / per-token fields — aligned with `GET /pricing` and `lib/agent/capabilities.ts`.

    **Lineage**: JSON data responses include `_metadata` (model version, data_as_of, factor set) and headers `X-Risk-Model-Version`, `X-Data-As-Of`, `X-Factor-Set-Id`, `X-Universe-Size`. Parquet and CSV bodies omit `_metadata`; use the same `X-Risk-*` headers on the HTTP response.

    **Tabular exports (Parquet / CSV):** For bulk historical loads, time-series endpoints accept `format=parquet` or `format=csv`, or (when `format` is omitted) `Accept: application/vnd.apache.parquet` or `Accept: text/csv`. Successful responses use `Content-Type: application/vnd.apache.parquet` or `text/csv; charset=utf-8` and `Content-Disposition: attachment` with a descriptive filename. Each export is a single flat table; column names and types match the per-operation schemas referenced in the response media type descriptions (aligned with JSON row objects or zipped parallel arrays). Parquet is produced via schema inference from the first row (UTF8 strings, DOUBLE floats, INT64 integers, BOOLEAN, TIMESTAMP_MILLIS for JavaScript Date values). CSV uses a header row, comma separators, UTF-8, and RFC 4180-style quoting when needed. Prefer Parquet for typed columnar stacks (pandas, Polars, Arrow); use CSV for spreadsheets and lightweight scripting.'
  contact:
    name: RiskModels Support
    email: service@riskmodels.app
    url: https://riskmodels.app
  termsOfService: https://riskmodels.app/legal
  license:
    name: Commercial
    url: https://riskmodels.app/legal
servers:
- url: https://riskmodels.app/api
  description: Production — all metered endpoints (`/metrics`, `/snapshot`, `/decompose`, `/batch/analyze`, `/portfolio/*`, etc.).
- url: https://riskmodels.app
  description: Discovery origin — `/.well-known/*` manifests (`mcp.json`, `ai-plugin.json`, `agentic-disclosure.json`) live at the site origin without the `/api` prefix. Generated clients that hard-code the first server entry must strip `/api` before requesting these paths.
security:
- BearerAuth: []
tags:
- name: Privacy
  description: Data handling and privacy disclosure.
paths:
  /.well-known/agentic-disclosure.json:
    get:
      summary: Agentic Privacy Disclosure
      servers:
      - url: https://riskmodels.app
        description: Site origin (discovery)
      description: 'Comprehensive data handling and privacy disclosure for AI marketplace compliance. Documents encryption, retention, third-party sharing, and regulatory compliance.

        **Discovery URL:** Served at the **site origin** (`https://riskmodels.app/.well-known/agentic-disclosure.json`), not under `/api`.


        **Key sections:**

        - Data handling (AES-256-GCM, GCP KMS)

        - Cryptographic shredding for GDPR compliance

        - Third-party sharing policy (none)

        - AI model usage (no training on user data)

        - Compliance (GDPR, SOC2, PCI-DSS)'
      operationId: getAgenticDisclosure
      tags:
      - Privacy
      security: []
      responses:
        '200':
          description: Privacy disclosure document
          content:
            application/json:
              schema:
                type: object
                properties:
                  service:
                    type: object
                  data_handling:
                    type: object
                  compliance:
                    type: object
                  security:
                    type: object
                  transparency:
                    type: object
components:
  securitySchemes:
    BearerAuth:
      type: http
      scheme: bearer
      bearerFormat: rm_agent_{environment}_{random}_{checksum}
      description: 'API key in format `rm_agent_{live|test}_{random}_{checksum}` or `rm_user_{random}_{checksum}`. Obtain via `POST /api/auth/provision` or from riskmodels.app/settings → API Keys. Include as: `Authorization: Bearer rm_agent_live_...`

        '
    OAuth2AuthorizationCode:
      type: oauth2
      description: 'OAuth 2.0 authorization code flow with PKCE (S256), used by MCP clients (Claude Desktop, Cursor, ChatGPT Developer Mode, Grok) that self-register via `POST /api/oauth/register`. Public clients only — no `client_secret` is issued and `token_endpoint_auth_method` is `none`.


        The access token this flow returns **is** an `rm_user_*` API key (1 h TTL, 30 d rotating refresh token), so it authenticates every `BearerAuth` operation below, not just `/api/mcp/sse`. Scope is currently informational: the API records the presented scope for telemetry but authorises by key validity and account balance, not by scope.


        Discovery metadata: `/.well-known/oauth-authorization-server`.

        '
      flows:
        authorizationCode:
          authorizationUrl: https://riskmodels.app/oauth/authorize
          tokenUrl: https://riskmodels.app/api/oauth/token
          refreshUrl: https://riskmodels.app/api/oauth/token
          scopes:
            mcp:read: Read access to risk analytics (the only scope the authorization server advertises)