Hardcore Mode

Changes made in Hardcore Mode take effect immediately on the next incoming message. Edit with care.

Hardcore Mode gives you direct access to the raw files that define your agent’s behavior. Instead of the visual designer, you edit YAML and Markdown files in a file tree.

File structure

Every agent is a folder with the following layout:

agent/
  workflows/
    main.yaml       # entry-point logic — runs on every message
  skills/
    {name}.md       # config header + system prompt

agent.yaml and flow.yaml are system files managed by the platform — they are not available in Hardcore Mode. Never edit them.

All .md files under skills/ use the same format: a YAML settings header and a system prompt body. The same file type covers agent prompts, sub-agent prompts, and skills — one consistent format for all three.

workflows/

main.yaml is the entry point — the engine runs it for every incoming message. You can have multiple workflow files; additional ones are called via run_workflow actions from main.yaml or other workflows. Each workflow file is a list of steps executed in order. Steps share a WorkflowState — a key-value store you can write to and read from across steps.

Minimal example

steps:
  - type: skill
    id: answer
    skill: answer_question
    result_key: response

  - type: action
    id: send
    action:
      type: respond
      value: "{response}"

Step types

skill
evaluate
if
action

Run an LLM using the config and prompt defined in a skill file.

- type: skill
  id: find_answer           # unique ID within this file
  skill: answer_question    # name of skills/answer_question.md (no extension)
  result_key: response      # save the LLM's reply under this key (default: "response")
  instruction: "Be concise" # optional: extra message injected before the LLM call

The LLM receives the system prompt from the skill file, the full conversation history, and any messages accumulated by earlier steps (e.g. previous tool results).

Extract structured data from the conversation and previous step outputs. No tools, no back-and-forth — one structured LLM call.

- type: evaluate
  id: score_lead
  model: claude-haiku-4-5-20251001
  description: |
    Determine whether the customer has a clear budget and timeline.
  output:
    - field: has_budget
      type: boolean
    - field: timeline
      type: string_or_null   # null when not mentioned
    - field: score
      type: int

Field types: boolean, string, string_or_null, int

Branch on a condition — checks a workflow state value and dispatches an action.

- type: if
  id: route
  branches:
    - condition:
        field: has_budget    # key from workflow state
        op: truthy           # truthy | falsy | eq | neq
      action:
        type: respond
        value: "Score: {score}, timeline: {timeline}"
    - condition:
        field: score
        op: eq
        value: 0
      action:
        type: do_nothing
  else:
    type: transfer_to_human

{key} placeholders in respond.value are replaced with the matching workflow state value.

Direct action, no LLM — immediately executes an action without calling a model.

- type: action
  id: escalate
  action:
    type: transfer_to_human

Actions

Action	Stops execution	Description
`respond`	✓	Sends a reply. Supports `{key}` placeholders from workflow state.
`do_nothing`	✓	Stops silently — no reply is sent.
`transfer_to_human`	✓	Escalates the conversation to a human.
`run_workflow`	✓	Runs another workflow file as a sub-flow.
`set_value`	—	Writes `key: value` to workflow state and continues to the next step.

run_workflow example

action:
  type: run_workflow
  workflow: escalation.yaml   # must exist under workflows/

set_value example

action:
  type: set_value
  key: greeted
  value: true

skills/{name}.md

A skill file has two parts separated by ---:

YAML settings header

Between --- markers — configures the LLM, tools, and iteration limits.

System prompt

Everything after the closing --- — the instructions sent to the LLM.

Full example

---
skill: answer_question
description: Search the knowledge base and answer customer questions
llm:
  model: claude-haiku-4-5-20251001
tools: [search_qa]
max_iterations: 5
---

You are a helpful support agent. Use the search_qa tool to find answers.

Always reply in the same language the customer used.
If nothing is found, say you'll escalate to a human.

Settings header fields

Field	Required	Description
`skill`	✓	Must match the filename without `.md`
`description`	—	Short description shown in the file list
`llm.model`	✓	Model to use (see Models)
`llm.thinking_budget`	—	Anthropic extended thinking budget in tokens (e.g. `8000`)
`llm.reasoning_effort`	—	OpenAI reasoning effort: `low` \| `medium` \| `high`
`tools`	—	List of tool names. Use `[]` for no tools.
`max_iterations`	—	Maximum tool-call loops before stopping (default: `10`)

Injecting workflow state into prompts

Use {values.key} anywhere in the system prompt body to inject a value from workflow state:

The customer's lead score is {values.score}.
Based on this, adjust your tone accordingly.

Models

Anthropic
OpenAI

Recommended for most use cases.

Model	Best for
`claude-haiku-4-5-20251001`	Fast, cost-efficient tasks
`claude-sonnet-4-6`	Balanced performance
`claude-opus-4-6`	Most capable, complex reasoning

Use llm.thinking_budget to enable extended thinking (tokens budget, e.g. 8000).

Model	Best for
`gpt-5.5`	Flagship, highest capability
`gpt-5.4`	Balanced
`gpt-5.4-mini`	Affordable, lighter tasks

Use llm.reasoning_effort (low / medium / high) instead of thinking_budget.

Tools

Tool	Description
`search_qa`	Semantic search over this org’s Q&A knowledge base
`web_search`	Live web search
`list_files`	List files in this agent’s directory
`read_file`	Read a file from this agent’s directory
`write_file`	Create or overwrite a file in this agent’s directory
`delete_file`	Delete a file from this agent’s directory

Rules & gotchas

workflows/main.yaml is required. Without it the agent returns no response.

Step IDs must be unique

id values must be unique within a workflow file. Duplicate IDs cause unpredictable behavior.

skill: must match the filename exactly

skill: must exactly match skills/{skill}.md — the match is case-sensitive.

Stopping actions end execution immediately

respond, do_nothing, transfer_to_human, and run_workflow stop execution immediately. Any steps listed after them in the workflow do not run.

set_value does not stop execution

Unlike other actions, set_value writes a value to workflow state and moves on to the next step — it never stops the workflow.

evaluate outputs land in workflow state

Fields produced by evaluate are stored in workflow state and can be read by any later if branch or respond placeholder.

Never edit agent.yaml or flow.yaml

These are system files managed by the platform. Editing them directly may break your agent in unexpected ways.

Getting started

Customization

Writing content

Agent ready

Agents

File structure

workflows/

Minimal example

Step types

Actions

skills/{name}.md

Full example

Settings header fields

Injecting workflow state into prompts

Models

Tools

Rules & gotchas

Getting started

Customization

Writing content

Agent ready

Agents

Documentation Index

​File structure

​workflows/

​Minimal example

​Step types

​Actions

​skills/{name}.md

​Full example

​Settings header fields

​Injecting workflow state into prompts

​Models

​Tools

​Rules & gotchas

File structure

workflows/

Minimal example

Step types

Actions

skills/{name}.md

Full example

Settings header fields

Injecting workflow state into prompts

Models

Tools

Rules & gotchas