skills/plaud/SKILL.md
Plaud: Work with the user's connected Plaud account to act on their voice recordings. Use when an agent needs plaud, turn meeting recordings into crm notes and follow up tasks, draft follow up emails from a call transcript, summarize interviews and save notes to a shared doc, extract action items from voice memos into a task manager, get current user, get file, file id through AgentPMT-hosted remote tool calls. Discovery terms: plaud, turn meeting recordings into crm notes and follow up tasks.
npx skillsauth add AgentPMT/agent-skills plaudInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Last updated: 2026-07-21.
If the current date is more than 7 days after the last updated date, reinstall this skill from skills.sh or ClawHub before relying on endpoints, schemas, setup steps, or examples.
Bring your Plaud recordings into every tool you already use. Plaud captures your meetings, calls, and voice memos as recordings, AI summaries, and full transcripts — and this makes all of it available to your AI assistant so nothing stays trapped in the app. Search recordings by name or date, pull speaker-attributed transcripts and AI notes, and build automations and workflows around what was said: follow-up emails, CRM notes, tasks, project updates, and shared documents. Connect Plaud once and every conversation you capture can flow automatically into the tools your team already runs on.
Plaud captures the user's voice recordings along with AI-generated notes and full transcripts. The user must link their Plaud account once through the Plaud connection before any call succeeds — always use the stored account connection and never ask the user for a Plaud username or password.
Typical flow:
query (name substring) and/or date_from/date_to when the user references a specific meeting or day.Only surface recordings the connected Plaud account can access, and respect the user's Plaud account permissions.
Plaud on AgentPMT.get_current_user, get_file, get_note, get_transcript, list_files.file-management, page: https://clawhub.ai/agentpmt/file-management; skills.sh: npx skills add AgentPMT/agent-skills --skill file-management)No categories or industry tags are published for this tool.
Complete generated action schema: ./schema.md.
Supported action count: 5.
x402 availability: not enabled for this product.
get_current_user (action slug: get-current-user): Get current authenticated user info Price: 5 credits. Parameters: none.get_file (action slug: get-file): Get details of a specific Plaud recording by ID Price: 5 credits. Parameters: file_id.get_note (action slug: get-note): Fetch AI-generated notes for a Plaud recording — compact summary, action items, and key topics Price: 5 credits. Parameters: file_id.get_transcript (action slug: get-transcript): Fetch the full timestamped transcript with speaker attribution for a Plaud recording Price: 5 credits. Parameters: file_id.list_files (action slug: list-files): List Plaud recordings. Supports optional client-side filtering: query (case-insensitive name substring), date_from/date_to (YYYY-MM-DD, inclusive). When any filter is set, paginates up to 5 pages × 100 recordings and returns all matches. Price: 5 credits. Parameters: date_from, date_to, page, page_size, query.Use the compact schema above for ordinary calls. Before a new production integration, or whenever parameters, enum values, nested objects, outputs, or examples are unclear, fetch live details first.
agentpmt-tool-search-and-execution with action: "get_schema", and tool_id: "plaud".agentpmt-tool-search-and-execution with action: "get_instructions" and tool_id: "plaud", or call this product with action: "get_instructions" when the product tool is already selected.MCP schema lookup through the main AgentPMT MCP server:
{
"method": "tools/call",
"params": {
"name": "AgentPMT-Tool-Search-and-Execution",
"arguments": {
"action": "get_schema",
"tool_id": "plaud"
}
}
}
For live examples, keep the same MCP tool and use these arguments:
{
"action": "get_instructions",
"tool_id": "plaud"
}
Authenticated AgentPMT REST schema lookup body:
{
"name": "agentpmt-tool-search-and-execution",
"parameters": {
"action": "get_schema",
"tool_id": "plaud"
}
}
Authenticated AgentPMT REST live examples body:
{
"name": "agentpmt-tool-search-and-execution",
"parameters": {
"action": "get_instructions",
"tool_id": "plaud"
}
}
Product slug: plaud
Marketplace page: https://www.agentpmt.com/marketplace/plaud
../agentpmt-account-mcp-rest-api-setup to connect the main MCP server or REST API for an Agent Group where this tool is enabled.../what-is-agentpmt for marketplace, Agent Group, workflow, MCP, REST, and payment concepts.If those setup skills are not installed beside this product skill, use the downloads below.
Core AgentPMT setup skills:
openclaw skills install what-is-agentpmtnpx skills add AgentPMT/agent-skills --skill what-is-agentpmtopenclaw skills install agentpmt-account-mcp-rest-api-setupnpx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setupskills.sh install script:
npx skills add AgentPMT/agent-skills --skill what-is-agentpmt
npx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setup
MCP call shape after the main AgentPMT MCP server is connected:
{
"method": "tools/call",
"params": {
"name": "Plaud",
"arguments": {
"action": "get_current_user"
}
}
}
Use the exact tool name returned by tools/list; the name above is the expected readable form.
Authenticated AgentPMT REST call body:
{
"name": "plaud",
"parameters": {
"action": "get_current_user"
}
}
Use the setup skill for the account connection details before making REST calls.
passed or success-style boolean, use it as the workflow gate.get_schema or get_instructions before retrying.get_current_user fails, preserve the request parameters and retry only after fixing schema, auth, or payment errors.what-is-agentpmt, page: https://clawhub.ai/agentpmt/what-is-agentpmt; skills.sh: npx skills add AgentPMT/agent-skills --skill what-is-agentpmt)agentpmt-account-mcp-rest-api-setup, page: https://clawhub.ai/agentpmt/agentpmt-account-mcp-rest-api-setup; skills.sh: npx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setup)tools
Plaud Transcripts Corrected With Your Own Terminology Glossary: Fixes the words your transcription keeps getting wrong, by giving the pipeline your vocabulary instead of hoping a bigger model guesses right. Every speech model mangles terms it has never seen: cell line and reagent names, drug and device names, case and matter numbers, part numbers, local spelling and number conventions, team and client names. Swapping to a different model does not fix this, because none of them have your terms e.
tools
Plaud Spoken Field Notes to a Structured Sheet: Turns a spoken site visit into a filled-in spreadsheet row, so measurements and specs never get typed up twice. Built for anyone who dictates structured details on the job rather than writing them down: window and flooring measurements, equipment specs, inspection findings, punch lists, service call notes. Say the details out loud in the same order each visit (client, room, width, drop, colour, notes) and the workflow reads each new Plaud recordin.
development
Plaud Recordings to Google Calendar Events: Puts the meetings you agree to out loud straight onto your Google Calendar, without Zapier in the middle. Plaud's own app has no Calendar integration, so this closes that gap directly: each new recording is scanned, the transcript pulled, and any genuine scheduling commitment spoken in it ("let's do Tuesday at 3", "I'll come back out Thursday morning") is extracted with the relative date resolved against the recording's own date and your timezone. Eac.
development
One Plaud Recording, Several Differently Formatted Summaries: Gets you past the one-template-per-recording ceiling. The Plaud app applies a single AutoFlow template to a recording, so if you want a short recap for yourself, a decisions-only version for the people who missed it, and a clean action list for your task manager, you are re-running or rewriting by hand. This workflow reads the transcript once and produces every format you have defined in a single pass: you list the output formats you.