mathematic-inc/earl/recall-ai

Name: recall-ai
Author: mathematic-inc

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Use recall.ai to record video meetings, retrieve transcripts, and access recordings. Use when the user wants to record a meeting, get a transcript, summarize a call, or access meeting audio/video.

Install

npx vskill@latest install mathematic-inc/earl/recall-ai

SKILL.md

Recall.ai

Records video meetings (Zoom, Google Meet, Teams, Webex, GoToMeeting), generates speaker-attributed transcripts, and produces downloadable audio/video files.

Status Reference

Bot lifecycle status (from get_bot):

Status	Meaning
`pending`	Bot created, not yet attempting to join
`joining`	Bot is connecting to the meeting
`joined`	Bot is in the meeting, recording NOT started
`recording`	Bot is actively recording
`stopped`	Recording stopped, processing in progress
`done`	Bot left and all processing complete

Artifact status (media_shortcuts.*.status.code):

Status	Meaning
`waiting`	Not started
`processing`	Being generated
`done`	Ready to retrieve
`failed`	Generation failed — retry or contact support
`deleted`	Artifact was removed

CRITICAL: Async Lifecycle

Creating a bot does NOT start recording. The full sequence is async:

text

create_bot → [wait: pending→joining→joined] → start_recording → [meeting runs] → leave_call/stop_recording → [wait: processing] → get_transcript → download_transcript

Do NOT call `get_transcript` immediately after `create_bot`. You will get an error or empty data. Always poll first.

Polling intervals:

While status is pending or joining: every 10–15 seconds (max 2 minutes — if longer, the meeting URL may be invalid or the meeting hasn't started)
While status is recording: every 30 seconds
After stop_recording or leave_call, while transcript is processing: every 15 seconds

Recipe A: Record a meeting and get the transcript

bash

# 1. Create the bot (schedule 10+ minutes ahead for reliability)
earl call --yes --json recall_ai.create_bot \
  --meeting_url "https://zoom.us/j/123456789" \
  --bot_name "Notetaker" \
  --join_at "2026-02-23T15:00:00Z"
# → SAVE the returned id as bot_id
 
# 2. Poll until the bot has joined (repeat every 10–15s)
earl call --yes --json recall_ai.get_bot --bot_id <bot_id>
# → Wait until status == "joined"
 
# 3. Start recording
earl call --yes --json recall_ai.start_recording --bot_id <bot_id>
 
# 4. (Meeting runs — poll every 30s if you need to monitor)
earl call --yes --json recall_ai.get_bot --bot_id <bot_id>
 
# 5. When the meeting ends, leave the call
earl call --yes --json recall_ai.leave_call --bot_id <bot_id>
 
# 6. Poll until transcript is ready (repeat every 15s)
earl call --yes --json recall_ai.get_bot --bot_id <bot_id>
# → Wait until media_shortcuts.transcript.status.code == "done"
# → Read media_shortcuts.transcript.id from the response
 
# 7. Get transcript metadata (includes download URL)
earl call --yes --json recall_ai.get_transcript --transcript_id <transcript_id>
# → Read data.download_url from the response
 
# 8. Download full transcript text
earl call --yes --json recall_ai.download_transcript --url "<data.download_url>"
# → Returns speaker-attributed transcript text — summarize, extract action items, etc.

Recipe B: Retrieve a video or audio recording

bash

# 1. Get bot to find media IDs and confirm artifacts are ready
earl call --yes --json recall_ai.get_bot --bot_id <bot_id>
# → Read media_shortcuts.video_mixed.id and media_shortcuts.audio_mixed.id
# → If media_shortcuts.video_mixed.status.code != "done", poll every 15s until it is
 
# 2. Get video download URL
earl call --yes --json recall_ai.get_video --video_id <video_mixed_id>
# → Returns data.download_url — share this link with the user (expires in ~5 hours)
 
# 3. Get audio download URL
earl call --yes --json recall_ai.get_audio --audio_id <audio_mixed_id>
# → Returns data.download_url — share this link with the user (expires in ~5 hours)

Important: Do not attempt to download or process binary video/audio content. Present the download URL to the user as a clickable link.

Recipe C: Control a live meeting

bash

# Stop recording early (bot stays in meeting; triggers transcript processing)
earl call --yes --json recall_ai.stop_recording --bot_id <bot_id>
# → After stopping, poll get_bot until media_shortcuts.transcript.status.code == "done"
 
# Pause recording during a sensitive segment
earl call --yes --json recall_ai.pause_recording --bot_id <bot_id>
 
# Resume when ready
earl call --yes --json recall_ai.resume_recording --bot_id <bot_id>
 
# Send a message to meeting participants
earl call --yes --json recall_ai.send_chat_message \
  --bot_id <bot_id> \
  --message "Action items so far: 1) Alice to send report 2) Bob to schedule follow-up"

`stop_recording` vs `leave_call`: stop_recording stops capturing but keeps the bot present. leave_call removes the bot from the meeting entirely. Both trigger transcript processing.

Finding a lost bot_id

If you don't have the bot_id, use list_bots to find it:

bash

# List all bots
earl call --yes --json recall_ai.list_bots
 
# List only future scheduled bots
earl call --yes --json recall_ai.list_bots --join_at_after "2026-02-23T00:00:00Z"

Sort the results by join_at or created_at to find the most recent bot. Never create a duplicate bot for a meeting — check the list first.

Scheduling constraint

For reliable joins, join_at must be at least 10 minutes in the future. Ad-hoc bots (no join_at) join immediately from a warm pool but may fail with 507 errors during peak usage. For production workflows, always schedule ahead.

Earl limitation: The create_bot template always sends join_at in the request body. When omitted, it sends "join_at": "". If the recall.ai API rejects this, always provide --join_at with a valid ISO 8601 timestamp. Similarly, list_bots always sends join_at_after in the query — provide a value or expect a possible 400 if the API validates the empty string.

Download URL expiry

data.download_url values are pre-signed AWS S3 URLs that expire in approximately 5 hours. Retrieve and process transcript/media in the same session. Do not save the URL for later use.

Security

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Source

SKILL.md in the repositoryCheckingskills/3p/recall_ai/SKILL.md

Popularity

Repository stars: 113
Repository forks: 7
7-day trend score: 24

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 19 Mar 2026, 7 months ago.

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