Agent skill

Delive Transcript Analyzer

by XimilalaXiang in XimilalaXiang/DeLive

Analyze, summarize, and extract insights from DeLive transcription sessions.

Apache-2.0Auto-check passedMedia & Creative

Install Delive Transcript Analyzer

skills CLI

$ npx skills add XimilalaXiang/DeLive --skill delive-transcript-analyzer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install XimilalaXiang/DeLive delive-transcript-analyzer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/XimilalaXiang/DeLive.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/delive-transcript-analyzer .claude/skills/delive-transcript-analyzer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "delive-transcript-analyzer" agent skill from https://github.com/XimilalaXiang/DeLive/tree/main/skills/delive-transcript-analyzer into .claude/skills/delive-transcript-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "delive-transcript-analyzer", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/XimilalaXiang/DeLive/tree/main/skills/delive-transcript-analyzer

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add XimilalaXiang/DeLive --skill delive-transcript-analyzer -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install XimilalaXiang/DeLive delive-transcript-analyzer --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/XimilalaXiang/DeLive.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/delive-transcript-analyzer .agents/skills/delive-transcript-analyzer && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "delive-transcript-analyzer" agent skill from https://github.com/XimilalaXiang/DeLive/tree/main/skills/delive-transcript-analyzer into .agents/skills/delive-transcript-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "delive-transcript-analyzer", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add XimilalaXiang/DeLive --skill delive-transcript-analyzer -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install XimilalaXiang/DeLive delive-transcript-analyzer --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/XimilalaXiang/DeLive.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/delive-transcript-analyzer .cursor/skills/delive-transcript-analyzer && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "delive-transcript-analyzer" agent skill from https://github.com/XimilalaXiang/DeLive/tree/main/skills/delive-transcript-analyzer into .cursor/skills/delive-transcript-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "delive-transcript-analyzer", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/XimilalaXiang/DeLive.git --path skills/delive-transcript-analyzer

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add XimilalaXiang/DeLive --skill delive-transcript-analyzer -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install XimilalaXiang/DeLive delive-transcript-analyzer --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/XimilalaXiang/DeLive.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/delive-transcript-analyzer .gemini/skills/delive-transcript-analyzer && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "delive-transcript-analyzer" agent skill from https://github.com/XimilalaXiang/DeLive/tree/main/skills/delive-transcript-analyzer into .gemini/skills/delive-transcript-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "delive-transcript-analyzer", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install XimilalaXiang/DeLive delive-transcript-analyzer

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add XimilalaXiang/DeLive --skill delive-transcript-analyzer -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/XimilalaXiang/DeLive.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/delive-transcript-analyzer .github/skills/delive-transcript-analyzer && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "delive-transcript-analyzer" agent skill from https://github.com/XimilalaXiang/DeLive/tree/main/skills/delive-transcript-analyzer into .github/skills/delive-transcript-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "delive-transcript-analyzer", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add XimilalaXiang/DeLive --skill delive-transcript-analyzer -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install XimilalaXiang/DeLive delive-transcript-analyzer --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/XimilalaXiang/DeLive.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/delive-transcript-analyzer .opencode/skills/delive-transcript-analyzer && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "delive-transcript-analyzer" agent skill from https://github.com/XimilalaXiang/DeLive/tree/main/skills/delive-transcript-analyzer into .opencode/skills/delive-transcript-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "delive-transcript-analyzer", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: delive-transcript-analyzer
GitHub stars: 281
Token cost: ~1.4k tokens
SKILL.md length: 552 words
Files: 1
Skills in repo: 1
Repo updated: Oct 7, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Analyze, summarize, and extract insights from DeLive transcription sessions.

Works in 3 steps: Search for the relevant meeting:… → Get the full session: get_session("") → Use the transcript and AI summary to…
: user mentions DeLive
SKILL.md covers Prerequisites, Setup, Available Tools (via MCP) and Available Resources (via MCP), plus 4 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Delive Transcript Analyzer is an agent skill from XimilalaXiang/DeLive. Analyze, summarize, and extract insights from DeLive transcription sessions. Use when: user mentions DeLive, transcription, meeting transcripts, live captions, audio transcription, AI correction, corrected transcript, or transcript analysis; user wants to search, retrieve, summarize, correct, or process recorded transcripts; user asks about meeting notes, action items, discussion summaries, or transcript quality from DeLive. Requires DeLive app running locally with its MCP server or REST API.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Media & Creative, covering Transcription and Speech recognition and synthesis. It works with Model Context Protocol, TypeScript, Tailwind CSS and Linux. The repository describes itself as: System audio capture + multi-provider ASR + local-first AI review workspace. Floating live captions, 12 ASR backends, 60+ languages, AI summary/chat/mindmap, Open API, MCP… The licence is Apache-2.0.

When your agent uses it

: user mentions DeLive
Meeting transcripts
Audio transcription
Corrected transcript

Example prompts

“/delive-transcript-analyzer”

Requirements

Python 3

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

Search for the relevant meeting: search_transcripts("weekly standup")
Get the full session: get_session("")
Use the transcript and AI summary to draft a follow-up email

What it can do on your machine

Read from SKILL.md and the folder at commit 0a18c71. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are json and python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Delive Transcript Analyzer loads about 1.4k tokens when it runs. Until then it costs about 131 tokens; SKILL.md has 552 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~131
When it runs · the whole SKILL.md, loaded when a task matches: ~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from XimilalaXiang/DeLive at commit 0a18c71, republished under its Apache-2.0 licence (© XimilalaXiang). 552 words, ~1,426 tokens.

Download SKILL.mdSave it as .claude/skills/delive-transcript-analyzer/SKILL.md (or your agent's skills folder).

name: delive-transcript-analyzer
description: Analyze, summarize, and extract insights from DeLive transcription sessions. Use when: user mentions DeLive, transcription, meeting transcripts, live captions, audio transcription, AI correction, corrected transcript, or transcript analysis; user wants to search, retrieve, summarize, correct, or process recorded transcripts; user asks about meeting notes, action items, discussion summaries, or transcript quality from DeLive. Requires DeLive app running locally with its MCP server or REST API.

DeLive Transcript Analyzer

Analyze and extract insights from real-time transcription sessions captured by DeLive, a desktop app for live speech-to-text.

Prerequisites

DeLive must be running locally (REST API at http://localhost:23456)
For MCP integration, the DeLive MCP server must be configured (see Setup below)

Setup

Option A: MCP Server (recommended for Claude Desktop / Claude Code)

The DeLive MCP server provides direct tool access. Add to your MCP config:

json

{
  "mcpServers": {
    "delive": {
      "command": "node",
      "args": ["<PATH_TO_DELIVE>/mcp/delive-mcp-server.js"]
    }
  }
}

Option B: REST API (for any client)

DeLive exposes a local REST API when running:

Base URL: http://localhost:23456/api/v1/
WebSocket live stream: ws://localhost:23456/ws/live

Available Tools (via MCP)

Tool	Purpose
`search_transcripts`	Find sessions by keyword in title or transcript content
`get_session`	Full session with transcript, corrected transcript, AI summary, mind map, Q&A
`get_session_transcript`	Transcript text + corrected transcript (when available)
`get_session_summary`	AI summary, action items, keywords, mind map
`get_recording_status`	Check if DeLive is currently recording
`list_topics`	List topic categories for organizing sessions
`list_tags`	List all tags used to label sessions

Available Resources (via MCP)

Resource URI	Description
`delive://sessions/recent`	Most recent 10 sessions (metadata)
`delive://status`	Current app and recording status

Workflow Patterns

Pattern 1: Meeting Summary to Email Draft

Search for the relevant meeting: search_transcripts("weekly standup")
Get the full session: get_session("<session_id>")
Use the transcript and AI summary to draft a follow-up email

Pattern 2: Lecture Notes to Study Guide

Find the lecture: search_transcripts("machine learning lecture")
Get the transcript: get_session_transcript("<session_id>")
Extract key concepts, create flashcards, or generate a structured study guide

Pattern 3: Code Discussion to Implementation

Search for the discussion: search_transcripts("refactor database layer")
Get session details: get_session("<session_id>")
Extract technical decisions and action items from the summary
Generate implementation code based on the discussed approach

Pattern 4: Multi-Session Analysis

Search broadly: search_transcripts("project alpha")
Retrieve summaries for each matching session
Synthesize a cross-session report: timeline, decisions made, open items

Pattern 5: Best-Quality Transcript

Get the transcript: get_session_transcript("<session_id>")
Check if a corrected transcript is present (returned as a separate section)
Prefer the corrected version for downstream processing (summaries, translations, reports)

Show full SKILL.md (216 more words)Show less

Pattern 6: Real-Time Monitoring

Connect to the live WebSocket for real-time transcript access:

python

import asyncio
import websockets
import json

async def monitor():
    async with websockets.connect("ws://localhost:23456/ws/live") as ws:
        async for message in ws:
            data = json.loads(message)
            if data["type"] == "transcript":
                print(data["stableText"])

asyncio.run(monitor())

REST API Reference

All endpoints return JSON. Base URL: http://localhost:23456

Method	Endpoint	Description
GET	`/api/v1/health`	Server health and version
GET	`/api/v1/sessions`	List sessions (params: `search`, `limit`, `offset`, `topicId`, `status`)
GET	`/api/v1/sessions/:id`	Full session detail
GET	`/api/v1/sessions/:id/transcript`	Transcript text + corrected transcript
GET	`/api/v1/sessions/:id/summary`	AI summary and mind map
GET	`/api/v1/topics`	All topics
GET	`/api/v1/tags`	All tags
GET	`/api/v1/status`	Recording state and app info

Tips

Search is case-insensitive and matches both title and transcript content
Sessions with status: "completed" have full transcripts; "recording" means in-progress
The hasSummary field in session listings indicates whether AI post-processing has been run
Use limit and offset for pagination when there are many sessions
The live WebSocket at /ws/live broadcasts both transcript updates and session lifecycle events (session-start, session-end)
Corrected transcript: get_session_transcript returns a correctedTranscript field when AI correction has been applied. Prefer this over the raw transcript for higher accuracy
get_session includes a Corrected Transcript section when available — use it for summaries, reports, and analysis

Error Handling

If DeLive is not running, all API calls will fail with a connection error. Check:

DeLive app is open and running
The built-in server is active (check http://localhost:23456/api/v1/health)
For MCP: the MCP server process can reach DeLive on localhost

Files

Just SKILL.md in skills/delive-transcript-analyzer of XimilalaXiang/DeLive.

Open the folder on GitHubat commit 0a18c71

Compare with similar skills

Delive Transcript Analyzer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Delive Transcript Analyzer compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Delive Transcript Analyzer this skillXimilalaXiang/DeLive	281	—	~1.4k	Automated safety check: Pass	Apache-2.0	yesterday
Azure AImicrosoft/GitHub-Copilot-for-Azure	255	2 repos	~852	Automated safety check: Pass	MIT	today
Deepgram JS Audio Intelligencedeepgram/deepgram-js-sdk	276	—	~1.5k	Automated safety check: Pass	MIT	yesterday
Deepgram JS Speech To Textdeepgram/deepgram-js-sdk	276	—	~1.8k	Automated safety check: Pass	MIT	yesterday
Env Setupwwwzhouhui/skills_collection	282	—	~3.5k	Automated safety check: Notes	None	2 days ago
Deepgram JS Conversational Sttdeepgram/deepgram-js-sdk	276	—	~1.3k	Automated safety check: Pass	MIT	yesterday

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Works with

Questions about Delive Transcript Analyzer

What does Delive Transcript Analyzer do?

Analyze, summarize, and extract insights from DeLive transcription sessions. Delive Transcript Analyzer is an agent skill from XimilalaXiang/DeLive. Analyze, summarize, and extract insights from DeLive transcription sessions.

When should I use Delive Transcript Analyzer?

Delive Transcript Analyzer fits situations like: : user mentions DeLive; meeting transcripts; audio transcription; corrected transcript.

How do I install Delive Transcript Analyzer in Claude Code?

Run `npx skills add XimilalaXiang/DeLive --skill delive-transcript-analyzer -a claude-code`. Or copy the skill folder (skills/delive-transcript-analyzer in XimilalaXiang/DeLive) into .claude/skills/delive-transcript-analyzer in your project. Claude Code loads it when a task matches its description.

How do I install Delive Transcript Analyzer in Codex?

Run `npx skills add XimilalaXiang/DeLive --skill delive-transcript-analyzer -a codex`. Or copy the skill folder (skills/delive-transcript-analyzer in XimilalaXiang/DeLive) into .agents/skills/delive-transcript-analyzer in your project. Codex loads it when a task matches its description.

Can I use Delive Transcript Analyzer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add XimilalaXiang/DeLive --skill delive-transcript-analyzer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/delive-transcript-analyzer, .gemini/skills/delive-transcript-analyzer, .github/skills/delive-transcript-analyzer and .opencode/skills/delive-transcript-analyzer in your project.

What does Delive Transcript Analyzer need to run?

SKILL.md names no scripts, command-line tools or credentials: Delive Transcript Analyzer is instructions for the agent only. Our summary lists: Python 3.

Does Delive Transcript Analyzer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Delive Transcript Analyzer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Delive Transcript Analyzer use?

Delive Transcript Analyzer is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Delive Transcript Analyzer use?

About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Delive Transcript Analyzer?

Skills that share tags, products or a category with Delive Transcript Analyzer: Azure AI (microsoft/GitHub-Copilot-for-Azure, 255 stars), Deepgram JS Audio Intelligence (deepgram/deepgram-js-sdk, 276 stars), Deepgram JS Speech To Text (deepgram/deepgram-js-sdk, 276 stars) and Env Setup (wwwzhouhui/skills_collection, 282 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Delive Transcript Analyzer?

XimilalaXiang (a GitHub user) maintains it in XimilalaXiang/DeLive, which has 281 GitHub stars. The repository was last updated on October 7, 2026.

Source: XimilalaXiang/DeLive on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Delive Transcript Analyzer

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

DeLive Transcript Analyzer

Prerequisites

Setup

Option A: MCP Server (recommended for Claude Desktop / Claude Code)

Option B: REST API (for any client)

Available Tools (via MCP)

Available Resources (via MCP)

Workflow Patterns

Pattern 1: Meeting Summary to Email Draft

Pattern 2: Lecture Notes to Study Guide

Pattern 3: Code Discussion to Implementation

Pattern 4: Multi-Session Analysis

Pattern 5: Best-Quality Transcript

Pattern 6: Real-Time Monitoring

REST API Reference

Tips

Error Handling

Files

Compare with similar skills

Similar skills

Azure AI

Deepgram JS Audio Intelligence

Deepgram JS Speech To Text

Env Setup

Deepgram JS Conversational Stt

Deepgram JS Voice Agent

Related

Questions about Delive Transcript Analyzer