Resources overview

A resource is a single step in a workflow. It has an ID, optional dependencies, optional validation, and exactly one action. kdeps builds a dependency graph from all resources and runs them in order.

Where it runs

All resource types work in both workflow mode and agent mode. In workflow mode, resources execute as DAG steps ordered by requires:. In agent mode, whole workflows are registered as callable tools - the LLM invokes a workflow as a unit, and all resource dependencies inside it resolve correctly.

The shape of a resource

# resources/my-resource.yaml
actionId: myResource        # required: unique ID -- used by requires: and get()
name: My Resource           # required: human-readable label
description: What it does   # optional
category: api               # optional grouping label

requires:                   # like imports -- these run first and must produce output
  - otherResource           # myResource will not run until otherResource is done

items:                      # optional: run this resource once per item -- see /workflow/items
  - item1
  - item2

loop:                       # optional: repeat while a condition holds -- see /workflow/loop
  while: "loop.index() < 5"

# Gate whether the resource runs at all -- see /workflow/validation
validations:
  methods: [POST]                # only run on POST requests
  routes: [/api/v1/endpoint]    # only run on this route
  headers: [Authorization]      # only run when this header is present
  params: [q, limit]            # only run when these params are present
  skip:
    - get('skip') == true       # skip silently if true
  check:
    - get('q') != ''            # fail with the error below if false
  error:
    code: 400
    message: Query required

# Expressions that run around the action -- see /workflow/expressions
before:                 # prepare values the action reads
  - set('pre', 'value')
after:                  # process the output for downstream resources
  - set('post', 'value')

# Exactly one primary action per resource (apiResponse: may accompany it
# on the same resource to format the HTTP response):
chat: { ... }        # send a prompt to an LLM; reply text at .message.content
httpClient: { ... }  # make an HTTP request; output is the parsed response body
sql: { ... }         # run a SQL query; output is the row set
python: { ... }      # run a Python script; output is its stdout (parsed as JSON)
exec: { ... }        # run a shell command; output is its stdout
email: { ... }       # send SMTP email or read/search/modify IMAP messages
telephony: { ... }   # in-call action (say, ask, menu, ...); output is TwiML
botReply: { ... }    # reply to the bot platform that delivered the message
file: { ... }       # filesystem operations: read, write, patch, list, delete
git: { ... }        # version control: status, diff, log, commit, push, pull
codeIntelligence: { ... }  # code navigation: search, definitions, diagnostics
agent: { ... }       # run another agent's full workflow; output is its apiResponse
apiResponse: { ... } # build the HTTP response returned to the caller
component:           # call an installable registry component
  name: botreply
  with:
    platform: telegram
    message: "Hello!"

actionId and requires

actionId is the resource's unique name. It is what targetActionId points to, and the key you pass to get() to read the resource's output.

# resources/response.yaml
actionId: response
name: API Response
requires: [llm]          # response will not run until llm is done
apiResponse:
  response:
    answer: get('llm').message.content   # reply text from the llm resource

requires: lists direct dependencies only. kdeps resolves transitive dependencies automatically - you do not list the whole chain.

Resource types

All executors are compiled into the kdeps binary and require no installation. They are grouped here by function; each links to its own reference page.

AI & language

YAML key	Description	Page
chat	LLM interaction - responses, generation, tools, vision	LLM
chat (routing)	Delegate model choice to config / auto-fit	LLM routing
-	Model backends, providers, API keys	LLM backends
loader	Load PDF, HTML, CSV, text, or a directory into text chunks	Loader
embedding	Local SQLite keyword store: index / search / upsert / delete	Embedding
vectorStore	External vector DB: Qdrant, Chroma, Pinecone, pgvector, ...	Vector store
transcribe	Speech to text via Whisper (OpenAI, Groq, local, offline)	Transcribe
ocr	Text from an image via tesseract - local, no API key	OCR

Web

YAML key	Description	Page
httpClient	HTTP requests - APIs, webhooks, auth, retry, cache	HTTP client
scraper	Fetch a URL and extract text, optional CSS selector	Scraper
browser	Playwright browser - navigation, forms, JS, screenshots	Browser
searchLocal	Glob + keyword search across local files	searchLocal
searchWeb	Web search: DuckDuckGo (default), Brave, Bing, Tavily	searchWeb

Data & system

YAML key	Description	Page
sql	Database queries and transactions	SQL
file	Read, write, patch, list, delete, copy, move files	File
git	Status, diff, log, commit, branch, push, pull	Git
python	Run a Python script, stdout parsed as JSON	Python
exec	Run a shell command, stdout captured	Exec
codeIntelligence	Symbol search, definitions, references, folder graph	Code intelligence · folder graph

Messaging

YAML key	Description	Page
email	SMTP send, IMAP read / search / modify	Email
telephony	Voice call handling (say, ask, menu, dial, record)	Telephony
botReply	Reply to the chat platform that delivered the message	Bot reply

Orchestration

YAML key	Description	Page
agent	Call another agent in an agency	Agent
component	Call a reusable resource bundle	Component
apiResponse	Return data to the HTTP caller	API response

Registry components (installable via kdeps registry install)

Some install names (scraper, browser, embedding) also exist as native YAML keys. The native action is compiled into the binary; the registry component is a separate, richer package. They are not interchangeable.

Install name	Description
scraper	Extended content extraction: PDFs, .docx, .xlsx, images (type auto-detected)
browser	Playwright browser with stealth mode, persistent sessions, and file upload
botreply	Chat bot reply (Discord, Slack, Telegram, WhatsApp)
embedding	Vector embeddings via OpenAI Embeddings API
search	Web search via Tavily API

See the Components guide for installation and usage details.

Execution flow

See also

• Validation and control flow - the validations: block
• Expressions - before:/after:, get(), set()
• Items iteration and While-loop
• Error handling (onError) - retry and fallback
• Agencies - multi-agent orchestration
• Components - installable capability extensions