CoreStory Loc API

openapi: 3.2.0
info:
  title: Crowdbotics API Documentation Loc API
  description: '# CoreStory API Overview


    The CoreStory API provides programmatic access to structured insights derived from software source code. It is designed for engineering, architecture, and product teams who need to extract business logic, technical specifications, architectural relationships, and system-level context from complex or legacy codebases. By interfacing directly with CoreStory API, users can:


    - Generate full Product Requirements Documents (PRDs) from a codebase

    - Extract detailed Technical Specifications for modernization or migration

    - Query a codebase using natural language to surface implementation details, logic paths, dependencies, and architectural insights

    - Construct and visualize knowledge graphs of systems, components, and relationships

    - Ingest, store, and retrieve content from a vector store for AI-powered retrieval-augmented generation (RAG) workflows


    CoreStory is especially valuable in contexts where:


    - Codebases are large, unstructured, or under-documented

    - Product and engineering teams are onboarding to unfamiliar systems

    - Technical stakeholders require visibility into system design or feature coverage

    - Modernization, replatforming, or M&A due diligence is underway


    The API can be integrated into existing CI/CD pipelines, internal developer portals, architecture review boards, product planning processes, or documentation automation workflows. All endpoints support secure authentication and are designed for high-availability, asynchronous workloads. Output formats include JSON, Markdown, and PDF, with flexible formatting options for downstream consumption. For step-by-step usage instructions and workflows, refer to the CoreStory API Quick Start Guide. ## Features


    * **Document Generation**

    * Generate complete Product Requirements Documents (PRD)

    * Generate Technical Specifications

    * Generate individual document sections (executive overview, user personas, etc.)

    * Format documents in JSON or Markdown


    * **Vector Store Management**

    * Ingest and manage documents in vector store

    * Query and retrieve document content

    * Manage document embeddings


    * **Context Management**

    * Manage context for different document types

    * Set and retrieve PRD context

    * Support for future context types (technical specs, user stories, etc.)


    * **Knowledge Graph**

    * Generate knowledge graphs from codebase queries

    * Visualize relationships between code entities

    * Analyze code structure and dependencies


    * **API Endpoints**

    * `/api/documents/*` - Document generation and formatting

    * `/api/generate/*` - Document formatting utilities

    * `/api/vector-store/*` - Vector store management

    * `/api/agents/*` - AI agent operations

    * `/api/context/*` - Context management for documents

    * `/api/graph/*` - Knowledge graph generation and analysis


    Note: JWT authentication support coming soon. All endpoints currently provide detailed OpenAPI documentation. * **Observability**

    * OpenTelemetry instrumentation for distributed tracing

    * Prometheus metrics endpoint at `/metrics`

    * Comprehensive request/response tracking

    * Custom business metrics


    # CoreStory System Architecture


    This document provides a high-level overview of how the CoreStory platform ingests, analyzes, and serves structured software intelligence through its API. The system is designed to process codebases and related technical artifacts in order to generate product specifications, technical documents, and knowledge graph representations. ---


    ## Core Components


    ### 1. **Ingestion Layer**


    - Accepts Git URLs, file uploads, or local archives

    - Extracts source files, documentation, and metadata

    - Initiates chunking and embedding via the vector store pipeline


    ### 2. **Vector Store and Context Engine**


    - Stores chunked and embedded documents

    - Supports semantic search and document retrieval

    - Feeds LLMs with scoped context for generation and reasoning


    ### 3.'
  version: 1.33.0
servers:
- url: /
  description: Current server
security:
- BearerAuth: []
tags:
- name: loc
paths:
  /api/loc/ledger:
    get:
      tags:
      - loc
      summary: Get the LOC ledger history for the current organization
      description: Return the LOC ledger history for the authenticated user's organization.
      operationId: get_loc_ledger
      parameters:
      - name: page
        in: query
        required: false
        schema:
          type: integer
          minimum: 1
          description: Page number (1-based)
          default: 1
          title: Page
        description: Page number (1-based)
      - name: size
        in: query
        required: false
        schema:
          type: integer
          maximum: 1000
          minimum: 1
          description: Items per page
          default: 10
          title: Size
        description: Items per page
      - name: start_date
        in: query
        required: false
        schema:
          anyOf:
          - type: string
            format: date-time
          - type: 'null'
          description: Filter entries from this date (inclusive)
          title: Start Date
        description: Filter entries from this date (inclusive)
      - name: end_date
        in: query
        required: false
        schema:
          anyOf:
          - type: string
            format: date-time
          - type: 'null'
          description: Filter entries up to this date (inclusive)
          title: End Date
        description: Filter entries up to this date (inclusive)
      - name: source
        in: query
        required: false
        schema:
          anyOf:
          - $ref: '#/components/schemas/LOCLedgerSource'
          - type: 'null'
          description: Filter entries by ledger source
          title: Source
        description: Filter entries by ledger source
      - name: sort_order
        in: query
        required: false
        schema:
          type: string
          pattern: ^(asc|desc)$
          description: Sort order for entries by created_at
          default: desc
          title: Sort Order
        description: Sort order for entries by created_at
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/LOCLedgerHistoryResponse'
        default:
          description: Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorSchema'
components:
  schemas:
    ErrorBody:
      properties:
        message:
          type: string
          title: Message
        type:
          type: string
          title: Type
        details:
          additionalProperties: true
          type: object
          title: Details
          description: Optional extra context for the error.
        code:
          anyOf:
          - type: string
          - type: 'null'
          title: Code
          description: Stable machine-readable code for clients that branch on the specific failure.
        required_organization:
          anyOf:
          - $ref: '#/components/schemas/RequiredOrganization'
          - type: 'null'
          description: Set when the caller can retry after switching organization context.
      type: object
      required:
      - message
      - type
      title: ErrorBody
    PaginationMeta:
      properties:
        total:
          type: integer
          title: Total
        page:
          type: integer
          title: Page
        size:
          type: integer
          title: Size
        pages:
          type: integer
          title: Pages
      type: object
      required:
      - total
      - page
      - size
      - pages
      title: PaginationMeta
    LOCLedgerHistoryResponse:
      properties:
        entries:
          items:
            $ref: '#/components/schemas/LOCLedgerEntryResponse'
          type: array
          title: Entries
          description: List of ledger entries for the organization
        pagination:
          $ref: '#/components/schemas/PaginationMeta'
          description: Pagination metadata
      type: object
      required:
      - entries
      - pagination
      title: LOCLedgerHistoryResponse
      description: Response schema for an organization's LOC ledger history.
    RequiredOrganization:
      properties:
        id:
          type: string
          title: Id
          description: Clerk organization id the client should switch to.
        name:
          type: string
          title: Name
          description: Display name of that organization.
      type: object
      required:
      - id
      - name
      title: RequiredOrganization
      description: The organization a caller must be acting under before a denied request can succeed.
    ErrorSchema:
      properties:
        error:
          $ref: '#/components/schemas/ErrorBody'
      type: object
      required:
      - error
      title: ErrorSchema
    LOCLedgerSource:
      type: string
      enum:
      - first_ingestion
      - reingestion_diff
      title: LOCLedgerSource
      description: What produced a LOC ledger entry's line count.
    LOCLedgerEntryResponse:
      properties:
        id:
          type: string
          title: Id
          description: Ledger entry ID
        project_name:
          anyOf:
          - type: string
          - type: 'null'
          title: Project Name
          description: Project the ingestion ran for; null if the project was deleted
        loc:
          type: integer
          title: Loc
          description: Lines of code this ingestion consumed
        source:
          type: string
          title: Source
          description: Whether the LOC is a first-ingestion full count or a re-ingestion diff
        created_at:
          type: string
          format: date-time
          title: Created At
          description: When the ledger entry was created
      type: object
      required:
      - id
      - project_name
      - loc
      - source
      - created_at
      title: LOCLedgerEntryResponse
      description: Response schema for a single LOC ledger entry.
  securitySchemes:
    BearerAuth:
      type: http
      scheme: bearer
      bearerFormat: JWT
      description: Enter the Bearer token from Clerk authentication
x-tagGroups:
- name: Ingest Your Codebase
  tags:
  - vector_store
  - projects
  - pre_ingestion
  - reingestion
- name: Generate Code Intelligence
  tags:
  - documents
  - document_generation
  - document_formatters
  - prd
  - prd_version
  - tech_spec
  - quality_metrics
  - sample_projects
- name: Query Your Codebase
  tags:
  - conversations
  - workflows
  - discovery
  - context
  - artifacts
- name: Manage and Inspect Intelligence
  tags:
  - api_debugging
  - events
  - version
  - files
  - cache
  - token_tracking
- name: Authenticate and Manage Access
  tags:
  - clerk_authentication
  - git_webhooks
  - github_integration
  - organizations
  - api_key_management
  - mcp_token_management
  - user
- name: (Advanced) Prompt Tuning
  tags:
  - prompts
- name: MCP Protocol
  tags:
  - mcp_protocol
- name: Administration
  tags:
  - admin
x-provenance:
  method: harvested
  publisher: CoreStory
  source: https://c2s.corestory.ai/openapi.json
  note: split by refine-openapis from the provider's own published document, verified by fetch (openapi/_original/*.fetch.json);
    stamped by stamp-openapi-provenance.py (roadmap#793)