CoreStory discovery API
The discovery API from CoreStory — 3 operation(s) for discovery.
The discovery API from CoreStory — 3 operation(s) for discovery.
openapi: 3.1.0
info:
title: Crowdbotics API Documentation admin discovery API
description: "# CoreStory API Overview\n\nThe 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.\n\nBy interfacing directly with CoreStory API, users can:\n\n- Generate full Product Requirements Documents (PRDs) from a codebase\n- Extract detailed Technical Specifications for modernization or migration\n- Query a codebase using natural language to surface implementation details, logic paths, dependencies, and architectural insights\n- Construct and visualize knowledge graphs of systems, components, and relationships\n- Ingest, store, and retrieve content from a vector store for AI-powered retrieval-augmented generation (RAG) workflows\n\nCoreStory is especially valuable in contexts where:\n\n- Codebases are large, unstructured, or under-documented\n- Product and engineering teams are onboarding to unfamiliar systems\n- Technical stakeholders require visibility into system design or feature coverage\n- Modernization, replatforming, or M&A due diligence is underway\n\nThe API can be integrated into existing CI/CD pipelines, internal developer portals, architecture review boards, product planning processes, or documentation automation workflows.\n\nAll 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.\n\nFor step-by-step usage instructions and workflows, refer to the [CoreStory API Quick Start Guide](#section/CoreStory-API-Quick-Start-Guide).\n\n## Features\n\n* **Document Generation**\n * Generate complete Product Requirements Documents (PRD)\n * Generate Technical Specifications\n * Generate individual document sections (executive overview, user personas, etc.)\n * Format documents in JSON or Markdown\n\n* **Vector Store Management**\n * Ingest and manage documents in vector store\n * Query and retrieve document content\n * Manage document embeddings\n\n* **Context Management**\n * Manage context for different document types\n * Set and retrieve PRD context\n * Support for future context types (technical specs, user stories, etc.)\n\n* **Knowledge Graph**\n * Generate knowledge graphs from codebase queries\n * Visualize relationships between code entities\n * Analyze code structure and dependencies\n\n* **API Endpoints**\n * `/api/documents/*` - Document generation and formatting\n * `/api/generate/*` - Document formatting utilities\n * `/api/vector-store/*` - Vector store management\n * `/api/agents/*` - AI agent operations\n * `/api/context/*` - Context management for documents\n * `/api/graph/*` - Knowledge graph generation and analysis\n\nNote: JWT authentication support coming soon. All endpoints currently provide detailed OpenAPI documentation.\n\n* **Observability**\n * OpenTelemetry instrumentation for distributed tracing\n * Prometheus metrics endpoint at `/metrics`\n * Comprehensive request/response tracking\n * Custom business metrics\n\n\n\n# CoreStory System Architecture\n\nThis 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.\n\n---\n\n## Core Components\n\n### 1. **Ingestion Layer**\n\n- Accepts Git URLs, file uploads, or local archives\n- Extracts source files, documentation, and metadata\n- Initiates chunking and embedding via the vector store pipeline\n\n### 2. **Vector Store and Context Engine**\n\n- Stores chunked and embedded documents\n- Supports semantic search and document retrieval\n- Feeds LLMs with scoped context for generation and reasoning\n\n### 3. **LLM Orchestration Layer**\n\n- Fan-out to multiple large language models\n- Handles prompt templating, context injection, and result normalization\n- Evaluates and scores generated outputs\n\n### 4. **Document Generation Engine**\n\n- Produces:\n - PRDs\n - Technical Specs\n - Individual document sections\n - Markdown and PDF exports\n- Format-flexible output for portals, APIs, and documentation pipelines\n\n### 5. **Graph Construction Module**\n\n- Extracts static and dynamic code relationships\n- Builds DAGs and call graphs of components, services, and files\n- Allows natural-language queries that return graph subviews and LLM explanations\n\n### 6. **Query Engine**\n\n- Accepts free-form questions about codebases\n- Routes queries to code graph, document store, or LLMs\n- Returns structured JSON answers and explanatory text\n\n### 7. **API Gateway**\n\n- Authenticates and rate-limits clients\n- Routes requests to internal services\n- Serves all external-facing endpoints in REST format\n\n---\n\n## Security and Privacy\n\n- All data transfer is encrypted via HTTPS\n- API access is secured using provided auth credentials (JWT tokens coming soon)\n- Uploaded code is only used to generate customer-requested outputs and is not retained indefinitely\n\n---\n\n## Extensibility\n\nThe platform is modular. It can be extended to:\n\n- Add new LLMs for ensemble generation\n- Integrate alternative vector databases\n- Connect to internal developer portals or product management tools via webhook or export endpoints\n\nFor more information, see the Quick Start or contact the CoreStory team.\n\n\n# CoreStory API Quick Start Guide\n\nThe CoreStory API provides programmatic access to structured code intelligence, enabling your team to extract business and technical specifications directly from source code. You can use the API to integrate CoreStory-generated documents into existing workflows, support software modernization and maintenance efforts, or enrich internal platforms with architectural and feature-level metadata.\n\n---\n\n## Overview\n\nThe CoreStory API enables:\n\n- Ingestion of content into a **vector store** for LLM-driven analysis\n- Generation of **Product Requirements Documents (PRDs)** and **Technical Specifications** from code\n- Interrogation of your codebase via a natural language **query engine**\n- Construction of **knowledge graphs** describing code relationships and system architecture\n- Management of **custom document context** and **custom prompts** for improved output relevance and quality\n\nThese capabilities support SDLC workflows such as:\n\n- Application modernization, migration, and maintenance\n- Documentation and auditability of legacy systems\n- Alignment of product, engineering, and architecture teams and systems\n- Developer onboarding and code comprehension\n\n---\n\n**Note for POV customers:** If your codebase has already been ingested as part of a proof-of-value (POV) engagement, you can use your existing authentication credentials and skip step 2 (”Ingest a Codebase or Document Source) of this guide.\n\n## 1. Authentication\n\n```\nPOST /api/auth/login\n```\n\nObtain a JWT for future API calls.\n\n**Request:**\n\n```\n{\n \"email\": \"you@example.com\",\n \"password\": \"your-password\"\n}\n```\n\n**Response:**\n\n```\n{\n \"access_token\": \"...\",\n \"token_type\": \"bearer\"\n}\n```\n\nInclude this token in all subsequent requests:\n\n```\nAuthorization: Bearer <access_token>\n```\n\n---\n\n## 2. Ingest a Codebase or Document Source\n\n```\nPOST /api/vector-store/ingest\n```\n\nTrigger ingestion of code from a Git repo, ZIP file, or local document directory.\n\n**Example Payload (GitHub):**\n\n```\n{\n \"source_type\": \"url\",\n \"source\": \"https://github.com/example/repo.git\",\n \"force\": true\n}\n```\n\nIngestion automatically chunks, embeds, and summarizes source files for downstream analysis.\n\n<details>\n<summary>Supported File Extensions</summary>\n\n### Programming Languages\n- Python: `.py`, `.pyw`, `.pyx`, `.pyi`\n- JavaScript/TypeScript: `.js`, `.mjs`, `.cjs`, `.ts`, `.jsx`, `.tsx`\n- Java: `.java`, `.class`, `.jar`\n- C/C++: `.c`, `.cpp`, `.cc`, `.cxx`, `.c++`, `.h`, `.hpp`, `.hh`, `.hxx`, `.h++`\n- .NET: `.cs`, `.csx`, `.vb`, `.fs`, `.fsx`, `.fsi`\n- PHP: `.php`, `.php3`, `.php4`, `.php5`, `.phtml`\n- Ruby: `.rb`, `.rbw`, `.rake`, `.gemspec`\n- Go: `.go`, `.mod`, `.sum`\n- Rust: `.rs`, `.rlib`\n- Swift: `.swift`\n- Kotlin: `.kt`, `.kts`, `.ktm`\n- Scala: `.scala`, `.sc`\n- Clojure: `.clj`, `.cljs`, `.cljc`, `.edn`\n- Haskell: `.hs`, `.lhs`\n- OCaml: `.ml`, `.mli`, `.mll`, `.mly`\n- R: `.r`, `.R`, `.rmd`, `.rnw`\n- Objective-C: `.m`, `.mm`\n- Perl: `.pl`, `.pm`, `.t`, `.pod`\n- Shell scripts: `.sh`, `.bash`, `.zsh`, `.fish`, `.ksh`, `.csh`, `.tcsh`\n- PowerShell: `.ps1`, `.psm1`, `.psd1`\n- Windows batch: `.bat`, `.cmd`\n- Lua: `.lua`\n- Dart: `.dart`\n- Elm: `.elm`\n- Elixir: `.ex`, `.exs`\n- Erlang: `.erl`, `.hrl`\n- Julia: `.jl`\n- Nim: `.nim`, `.nims`\n- Crystal: `.cr`\n- D: `.d`\n- Pascal: `.pas`, `.pp`, `.inc`\n- Fortran: `.f`, `.f90`, `.f95`, `.f03`, `.f08`, `.for`, `.ftn`, `.fpp`\n- COBOL: `.cob`, `.cbl`, `.cpy`, `.cobol`, `.bms`, `.ctl`, `.jcl`, `.proc`\n- IBM i (AS/400) RPG ILE: `.rpgle`, `.rpgleinc`\n- IBM i (AS/400) CLLE: `.clle`\n- IBM i (AS/400) DDS: `.pf`, `.lf`, `.dspf`\n- PowerBuilder: `.pbt`, `.pbs`, `.pbr`, `.srw`, `.srd`, `.sru`, `.sra`, `.srp`, `.srf`, `.srq`, `.srs`, `.srm`, `.srj`\n- Ada: `.ada`, `.adb`, `.ads`\n- Assembly: `.asm`, `.s`, `.S`\n- Verilog/SystemVerilog: `.v`, `.vh`, `.sv`, `.svh`\n- VHDL: `.vhd`, `.vhdl`\n- Tcl/Tk: `.tcl`, `.tk`\n- Groovy: `.groovy`, `.gvy`, `.gy`, `.gsh`\n- CoffeeScript: `.coffee`, `.litcoffee`\n- PureScript: `.purs`\n- ReasonML: `.reason`, `.re`, `.rei`\n- Racket/Scheme: `.rkt`, `.scm`, `.ss`\n- Lisp: `.lisp`, `.lsp`, `.l`, `.cl`, `.fasl`\n- Prolog: `.prolog`, `.pro`, `.P`\n- MATLAB: `.matlab`, `.fig`\n- Mathematica: `.mathematica`, `.nb`, `.wl`, `.wls`\n- SageMath: `.sage`, `.spyx`\n- Zig: `.zig`\n- Odin: `.odin`\n- V: `.v3`, `.v2`, `.v1`\n- Pony: `.pony`\n- Red: `.red`, `.reds`\n- Io: `.io`\n- Factor: `.factor`\n- Forth: `.forth`, `.fth`, `.4th`\n- J/K/Q/APL: `.j`, `.k`, `.q`, `.apl`\n- Chapel: `.chapel`, `.chpl`\n- X10: `.x10`\n- Arduino/Processing: `.pde`, `.ino`\n\n### Web Technologies\n- HTML: `.html`, `.htm`, `.xhtml`, `.shtml`\n- CSS/Preprocessors: `.css`, `.scss`, `.sass`, `.less`, `.styl`, `.stylus`\n- Frontend frameworks: `.vue`, `.svelte`\n- JSP: `.jsp`, `.jspx`, `.tag`, `.tagx`\n- ASP.NET: `.asp`, `.aspx`, `.ascx`, `.asax`, `.ashx`, `.asmx`\n- Ruby templates: `.erb`, `.haml`, `.slim`\n- PHP templates: `.twig`, `.blade`\n- Template engines: `.mustache`, `.hbs`, `.handlebars`, `.ejs`, `.pug`, `.jade`, `.liquid`, `.ftl`, `.ftlh`, `.vm`, `.vtl`, `.thymeleaf`\n\n### Configuration/Data\n- JSON: `.json`, `.json5`, `.jsonc`, `.jsonl`, `.ndjson`\n- XML: `.xml`, `.xsd`, `.xsl`, `.xslt`, `.dtd`, `.rng`, `.rnc`\n- YAML/TOML: `.yaml`, `.yml`, `.toml`\n- INI/Cfg/Conf: `.ini`, `.cfg`, `.conf`, `.config`, `.properties`\n- Environment: `.env`, `.envrc`, `.env.local`, `.env.development`, `.env.production`\n- Property lists: `.plist`\n- HOCON: `.hocon`\n- RON/HJSON/CSON: `.ron`, `.hjson`, `.cson`\n\n### Documentation/Text\n- Markdown: `.md`, `.markdown`, `.mdown`, `.mkd`, `.mkdn`\n- Plain text: `.txt`, `.text`\n- reStructuredText: `.rst`, `.rest`\n- AsciiDoc: `.asciidoc`, `.adoc`, `.asc`\n- LaTeX: `.tex`, `.latex`, `.ltx`, `.sty`, `.cls`, `.bib`\n- Org mode: `.org`\n- Wiki markup: `.wiki`, `.mediawiki`\n- Textile/Creole/RDoc: `.textile`, `.creole`, `.rdoc`\n\n### Data Formats\n- Delimited: `.csv`, `.tsv`, `.psv`\n- SQL: `.sql`, `.ddl`, `.dml`, `.plsql`, `.psql`, `.mysql`\n- GraphQL: `.graphql`, `.gql`\n- Protocols: `.proto`, `.protobuf`, `.avro`, `.avsc`, `.avdl`, `.thrift`, `.capnp`, `.fbs`\n- Columnar: `.parquet`, `.orc`, `.arrow`\n\n### Build/Dependency\n- Gradle: `.gradle`, `.gradle.kts`\n- Maven: `.maven`, `.mvn`\n- SBT: `.sbt`\n- CMake: `.cmake`, `.cmake.in`\n- Make: `.make`, `.mk`, `.mak`\n- Docker: `.dockerfile`, `.containerfile`, `.dockerignore`\n- Git: `.gitignore`, `.gitattributes`, `.gitmodules`, `.gitkeep`\n- Mercurial/Subversion/Bazaar: `.hgignore`, `.hgrc`, `.svnignore`, `.bzrignore`\n- EditorConfig: `.editorconfig`\n- Linters/Formatters: `.eslintrc`, `.eslintignore`, `.prettierrc`, `.prettierignore`, `.babelrc`, `.babelignore`\n- Node.js: `.npmrc`, `.npmignore`, `.yarnrc`, `.yarnignore`\n- Python: `.pipfile`, `.pipfile.lock`, `.requirements`, `.requirements.txt`, `.poetry.lock`, `.pyproject.toml`, `.setup.py`, `.setup.cfg`, `.manifest.in`, `.tox.ini`, `.noxfile.py`, `.pre-commit-config.yaml`\n- CI/CD: `.github`, `.gitlab-ci.yml`, `.travis.yml`, `.appveyor.yml`, `.circleci`, `.jenkins`, `.jenkinsfile`, `.azure-pipelines.yml`, `.buildkite.yml`\n- Package Managers: `package.json`, `package-lock.json`, `yarn.lock`, `pnpm-lock.yaml`, `composer.json`, `composer.lock`, `gemfile`, `gemfile.lock`, `cargo.toml`, `cargo.lock`, `go.mod`, `go.sum`, `requirements.txt`, `pipfile`, `pipfile.lock`, `poetry.lock`, `pyproject.toml`, `build.gradle`, `build.gradle.kts`, `settings.gradle`, `gradle.properties`, `pom.xml`, `settings.xml`, `build.sbt`, `plugins.sbt`, `makefile`, `gnumakefile`, `makefile.am`, `makefile.in`, `dockerfile`, `containerfile`, `vagrantfile`, `rakefile`, `guardfile`, `capfile`, `gulpfile.js`, `gruntfile.js`, `webpack.config.js`, `rollup.config.js`, `tsconfig.json`, `jsconfig.json`, `deno.json`, `deno.jsonc`, `mix.exs`, `mix.lock`, `rebar.config`, `rebar.lock`, `project.clj`, `deps.edn`, `stack.yaml`, `cabal.config`, `setup.hs`, `dub.json`, `dub.sdl`, `nimble`, `config.nims`, `shard.yml`, `shard.lock`, `pubspec.yaml`, `pubspec.lock`, `elm.json`, `elm-package.json`, `project.json`, `global.json`, `nuget.config`, `packages.config`, `paket.dependencies`, `paket.lock`, `.log`, `.lock`, `.pid`, `.tmp`, `.temp`, `.patch`, `.diff`, `.spec`, `.rpm`, `.deb`, `.control`, `.pkgbuild`, `.ebuild`, `.formula`, `.port`, `.portfile`, `.nix`, `.bzl`, `.bazel`, `.workspace`, `.buck`, `.buckconfig`, `.pants`, `.pants.ini`, `.please`, `.plzconfig`, `.gn`, `.gni`, `.ninja`, `.waf`, `.wscript`, `.scons`, `.sconstruct`, `.sconscript`\n\n</details>\n\n<details>\n<summary>Configuration Files</summary>\n\n- `requirements.txt`\n- `.gitignore`\n- `.dockerignore`\n- `.editorconfig`\n- `.eslintrc.js`\n- `.eslintrc.json`\n- `.prettierrc.js`\n- `.prettierrc.json`\n- `.babelrc.js`\n- `.babelrc.json`\n\n</details>\n\n---\n\n## 3. Generate a Product Requirements Document (PRD)\n\n**Note**: Generating a PRD or technical specification will replace the existing PRD or technical specification. The new outputs will document your codebase as it was when it was most recently ingested.\n\n```\nPOST /api/documents/prd?format=json\n```\n\nGenerates a structured PRD with:\n\n- Executive Overview\n- User Personas\n- High-Level Requirements\n- User Stories\n- Business Value\n\n**Example Response (truncated):**\n\n```\n{\n \"content\": {\n \"executive_overview\": \"Modernize internal authentication platform\",\n \"user_personas\": [...],\n \"user_stories\": [...]\n }\n}\n```\n\n**Tip:** For PRDs or technical specs, use `format=markdown` to return a Markdown-formatted document instead.\n\n---\n\n## 4. Generate a Technical Specification\n\n```\nPOST /api/documents/technical-spec?format=json\n```\n\nReturns system-level implementation details including:\n\n- Architecture and Components\n- Data Models and Relationships\n- User Interface Screens and Components\n- APIs and Integration Points\n- System Interfaces and Specifications\n- Security Considerations\n- Implementation and Deployment Strategy\n\n---\n\n## 5. Query Your Code\n\n```\nPOST /api/graph/query-engine\n```\n\nAsk natural language questions about your codebase to return a structured graph of relationships.\n\n**Example Query:**\n\n```\n{\n \"query\": \"How does the system determine whether a user has admin privileges when accessing the audit log?\"\n}\n```\n\n**Response (truncated):**\n\n```\n{\n \"summary\": \"When a user requests access to the audit log, the system checks their assigned roles in `AuthService.getUserRoles`. If 'admin' is present, access is granted. This check occurs in `AuditLogController` before querying the log database. The middleware `CheckPermissions` is also invoked on this route.\"\n}\n```\n\n---\n\n## 6. Format and Retrieve Document Sections\n\nUse these endpoints to extract or reformat specific document sections:\n\n- `/api/documents/sections/{doc_type}` → generate a specific section\n- `/api/documents/format/markdown-output/{doc_type}` → format JSON as Markdown\n- `/api/documents/format/pdf-output/{doc_type}` → export PDF\n\nExample section names:\n\n- `executive-overview`\n- `data-models`\n- `system-architecture`\n- `integration-points`\n\n---\n\n## Questions?\n\nAfter reviewing this guide and the API docs, we recommend scheduling a short Q&A call if you have integration-specific needs or want assistance mapping this to your environment.\n"
version: 1.26.2
servers:
- url: /
description: Current server
security:
- BearerAuth: []
tags:
- name: discovery
paths:
/api/discovery/{prd_id}/identify-core-features:
get:
tags:
- discovery
summary: Get core application features
description: "Analyzes the codebase to identify the core features and functionalities of the application.\n This endpoint provides a focused view of the main features without generating other document sections.\n\n The response includes:\n - Feature name\n - Feature description\n - Feature category"
operationId: get_core_features
parameters:
- name: prd_id
in: path
required: true
schema:
type: integer
title: Prd Id
responses:
'200':
description: List of core application features
content:
application/json:
schema:
type: array
items:
$ref: '#/components/schemas/Feature-Output'
title: Response Get Core Features
default:
description: Error
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorSchema'
'500':
description: Internal server error
/api/discovery/{prd_id}/questions:
get:
tags:
- discovery
summary: Get suggested questions about the codebase
description: "Analyzes the codebase to generate relevant questions that users can ask about the system.\n These questions are designed to help users explore and understand the codebase through the graph visualization.\n\n The response includes:\n - Question text\n - Question category\n - Question complexity level\n - Total number of questions\n - Requested limit\n\n Parameters:\n - limit: Maximum number of questions to return (default: 10)\n - include_prd_context: Whether to use PRD context in generating questions (default: false)"
operationId: get_discovery_questions
parameters:
- name: prd_id
in: path
required: true
schema:
type: integer
title: Prd Id
- name: limit
in: query
required: false
schema:
type: integer
maximum: 50
minimum: 1
description: Maximum number of questions to return
default: 10
title: Limit
description: Maximum number of questions to return
- name: include_prd_context
in: query
required: false
schema:
type: boolean
description: Whether to use PRD context in generating questions
default: false
title: Include Prd Context
description: Whether to use PRD context in generating questions
responses:
'200':
description: List of suggested questions about the codebase
content:
application/json:
schema:
$ref: '#/components/schemas/QuestionsResponse'
default:
description: Error
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorSchema'
'500':
description: Internal server error
/api/discovery/{project_id}/suggested-questions:
get:
tags:
- discovery
summary: Get Suggested Questions for discovery
description: "Retrieve suggested questions for a specific project, optionally filtered by persona and section.\nArgs:\n project_id (int): The ID of the project.\n persona (str, optional): Filter questions by persona.\n section (str, optional): Filter questions by section.\nReturns:\n SuggestedQuestionListResponse: A list of questions matching the criteria."
operationId: get_suggested_questions
parameters:
- name: project_id
in: path
required: true
schema:
type: integer
title: Project Id
- name: persona
in: query
required: false
schema:
anyOf:
- type: string
- type: 'null'
description: Filter by persona
title: Persona
description: Filter by persona
- name: section
in: query
required: false
schema:
anyOf:
- type: string
- type: 'null'
description: Filter by section
title: Section
description: Filter by section
responses:
'200':
description: Successful Response
content:
application/json:
schema:
$ref: '#/components/schemas/SuggestedQuestionListResponse'
default:
description: Error
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorSchema'
components:
schemas:
ErrorSchema:
properties:
error:
$ref: '#/components/schemas/ErrorBody'
type: object
required:
- error
title: ErrorSchema
Question:
properties:
text:
type: string
title: Text
description: The question text
category:
type: string
title: Category
description: Category of the question (e.g., 'relationships', 'architecture', 'features')
complexity:
type: string
title: Complexity
description: Complexity level of the question (e.g., 'beginner', 'intermediate', 'advanced')
type: object
required:
- text
- category
- complexity
title: Question
description: Model for a suggested question
SuggestedQuestionResponse:
properties:
id:
type: integer
title: Id
text:
type: string
title: Text
persona:
anyOf:
- type: string
- type: 'null'
title: Persona
section:
anyOf:
- type: string
- type: 'null'
title: Section
created_at:
type: string
format: date-time
title: Created At
updated_at:
anyOf:
- type: string
format: date-time
- type: 'null'
title: Updated At
type: object
required:
- id
- text
- persona
- section
- created_at
- updated_at
title: SuggestedQuestionResponse
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.
type: object
required:
- message
- type
title: ErrorBody
QuestionsResponse:
properties:
questions:
items:
$ref: '#/components/schemas/Question'
type: array
title: Questions
description: List of suggested questions
total:
type: integer
title: Total
description: Total number of questions
limit:
type: integer
title: Limit
description: Maximum number of questions requested
type: object
required:
- questions
- total
- limit
title: QuestionsResponse
description: Response model for the questions endpoint
SuggestedQuestionListResponse:
properties:
suggested_questions:
items:
$ref: '#/components/schemas/SuggestedQuestionResponse'
type: array
title: Suggested Questions
total:
type: integer
title: Total
type: object
required:
- suggested_questions
- total
title: SuggestedQuestionListResponse
Feature-Output:
properties:
name:
type: string
title: Name
description: Concise feature name in plain text, no markdown.
description:
type: string
title: Description
description: Plain text description of the feature. No markdown formatting.
category:
type: string
title: Category
description: Category or Epic of the identified feature.
type: object
required:
- name
- description
- category
title: Feature
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
- github_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