--- summary: "Markdown formatting pipeline for outbound channels" read_when: - You are changing markdown formatting or chunking for outbound channels - You are adding a new channel formatter or style mapping - You are debugging formatting regressions across channels title: "Markdown formatting" --- OpenClaw converts outbound Markdown into a shared intermediate representation (IR) before rendering channel-specific output. The IR keeps plain text plus style/link spans, so one parse step feeds every channel and chunking never splits formatting mid-span. ## Pipeline 1. **Parse Markdown into IR** (`markdownToIR`) - plain text plus style spans (bold, italic, strikethrough, code, code block, spoiler, blockquote, heading 1-6) and link spans. Offsets are UTF-16 code units so Signal style ranges align with its API directly. Tables parse only when the channel opts into a table mode. 2. **Chunk the IR** (`chunkMarkdownIR` / `renderMarkdownIRChunksWithinLimit`) - splitting happens on IR text before rendering, so inline styles and links are sliced per chunk instead of breaking across a boundary. 3. **Render per channel** (`renderMarkdownWithMarkers`) - a style-marker map turns spans into the channel's native markup. | Channel | Renderer | Notes | | ---------------------------------------------------------------- | ------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------- | | Slack | mrkdwn tokens (`*bold*`, `_italic_`, `` `code` ``, code fences) | Links become ``; autolink disabled during parse to avoid double-linking | | Telegram | HTML tags (``, ``, ``, ``, `
`, ``, ``) | Also supports rich-message tables and headings (`
`-`
`) when `richMessages` is on |
| Signal                                                           | plain text + `text-style` ranges                                                     | Links render as `label (url)` when the label differs from the URL                        |
| Discord, WhatsApp, iMessage, Microsoft Teams, and other channels | plain text                                                                           | No IR-based styling; Markdown table conversion still runs via `convertMarkdownTables`    |

## IR example

Input Markdown:

```markdown
Hello **world** - see [docs](https://docs.openclaw.ai).
```

IR (schematic):

```json
{
  "text": "Hello world - see docs.",
  "styles": [{ "start": 6, "end": 11, "style": "bold" }],
  "links": [{ "start": 19, "end": 23, "href": "https://docs.openclaw.ai" }]
}
```

## Table handling

`markdown.tables` controls how a channel converts Markdown tables, per
channel and optionally per account:

| Mode      | Behavior                                                                             |
| --------- | ------------------------------------------------------------------------------------ |
| `code`    | Render as an aligned ASCII table inside a code block (fallback default)              |
| `bullets` | Convert each row into `label: value` bullet points                                   |
| `block`   | Keep native tables where the transport supports them; falls back to `code` otherwise |
| `off`     | Disable table parsing; raw table text passes through unchanged                       |

Per-channel plugin defaults: Signal, WhatsApp, and Matrix default to
`bullets`; Mattermost defaults to `off`; Telegram defaults to `block` (which
resolves to `code` unless the account has `richMessages` enabled). Any
channel without an explicit plugin default falls back to `code`.

```yaml
channels:
  discord:
    markdown:
      tables: code
    accounts:
      work:
        markdown:
          tables: off
```

## Chunking rules

- Chunk limits come from channel adapters/config and apply to IR text, not
  rendered output.
- Fenced code blocks are kept as one block with a trailing newline so
  channels render the closing fence correctly.
- List and blockquote prefixes are part of the IR text, so chunking never
  splits mid-prefix.
- Inline styles never split across chunks; the renderer reopens an open
  style at the start of the next chunk.

See [Streaming and chunking](/concepts/streaming) for chunk-boundary and
delivery behavior across channels.

## Link policy

- **Slack:** `[label](url)` -> ``; bare URLs stay bare.
- **Telegram:** `[label](url)` -> `label` (HTML parse mode).
- **Signal:** `[label](url)` -> `label (url)` unless the label already
  matches the URL.

## Spoilers

Spoiler markers (`||spoiler||`) are parsed for Signal (mapped to `SPOILER`
style ranges) and Telegram (mapped to ``). Other channels treat
`||...||` as plain text.

## Collapsible details

The Control UI and Telegram accounts with `richMessages: true` render
`
Label` disclosures as native collapsible sections.
OpenClaw tells the model about this option only when the current reply surface
supports it. Other channels, including Telegram accounts without rich messages,
flatten each disclosure to `**Summary**` followed by the visible body so no
content is hidden or lost.

## Adding or updating a channel formatter

1. **Parse once** with `markdownToIR(...)`, passing channel-appropriate
   options (`autolink`, `headingStyle`, `blockquotePrefix`, `tableMode`).
2. **Render** with `renderMarkdownWithMarkers(...)` and a style-marker map (or
   custom style-range logic for transports like Signal).
3. **Chunk** with `chunkMarkdownIR(...)` or
   `renderMarkdownIRChunksWithinLimit(...)` before rendering each chunk.
4. **Wire the adapter** to call the new chunker and renderer from the
   outbound send path.
5. **Test** with format tests plus an outbound delivery test if the channel
   chunks.

## Common gotchas

- Slack angle-bracket tokens (`<@U123>`, `<#C123>`, ``) must
  survive escaping; raw HTML still needs to be escaped safely.
- Telegram HTML requires escaping text outside tags to avoid broken markup.
- Signal style ranges use UTF-16 offsets, not code-point offsets.
- Preserve trailing newlines on fenced code blocks so the closing marker
  lands on its own line.

## Related


  
    Outbound streaming behavior, chunk boundaries, and channel-specific delivery.
  
  
    What the model sees before the conversation, including injected workspace files.