AGENT SKILL

generating-podcast-script

Use this skill whenever the user asks to write, generate, or create a podcast script or podcast episode — from a topic, or from source material such as a news digest, newsletter, email review, or set of articles — and optionally convert it to audio with Azure Text-to-Speech. Handles the initial request and every follow-up refinement (source, topic, length, cast, narration) in the same task.

License 许可
MIT
最近更新
2026-11-15
Stars
★ 16
Forks
25

01 前言 Front Matter

name
generating-podcast-script
description
Use this skill whenever the user asks to write, generate, or create a podcast script or podcast episode — from a topic, or from source material such as a news digest, newsletter, email review, or set of articles — and optionally convert it to audio with Azure Text-to-Speech. Handles the initial request and every follow-up refinement (source, topic, length, cast, narration) in the same task.

03 SKILL.md 正文

Podcast Script Generation

Produces a two-host, NotebookLM-style conversational episode: a readable script plus a multi-voice SSML document ready for Azure Text-to-Speech.

Step 1 — Gather inputs

Ask only for what is missing. Do not ask for optional fields that have safe defaults.

Input Required Default
source or topic Yes — (source material such as a digest/newsletter/articles, or a plain topic)
duration No medium — short ≈ 3 min / ~450 words, medium ≈ 6 min / ~900 words, long ≈ 12 min / ~1,800 words
language No English
cast No Two hosts, NOVA and MILES (see Step 4)
generate_audio No Ask after the script is ready

All word targets assume ~150 spoken words per minute. Stay within 10 percent of target.

Derive a lowercase-hyphenated <slug> from the source or topic (max 6 words, ASCII only).

Step 2 — Parse the source material

Skip this step when the user gave a bare topic with no source material.

Extract every distinct article or item. For each, capture:

  • headline
  • publication / source
  • date, if present
  • the core factual claim
  • any figures or quotes
  • the "so what"

Merge duplicates covering the same event. Discard boilerplate, footers, disclaimers, legal notices, unsubscribe text, and image captions.

Step 3 — Editorial selection

Rank items by newsworthiness and reader impact. Keep the top 4 to 6 for full treatment (fewer for short, more for long). Group the remainder into one fast rapid fire segment. If the material has a dominant theme, lead with it and thread it through the episode.

Step 4 — Cast

Two hosts, always the same personalities, always distinct voices:

  • NOVA — voice en-US-AvaMultilingualNeural. Lead host. Warm, curious, quick. Drives the agenda, asks the question the listener is thinking, reacts out loud, reframes jargon into plain language. Slightly faster cadence.
  • MILES — voice en-US-AndrewMultilingualNeural. Analyst. Calm, dry, precise. Supplies context, numbers, caveats, second-order implications. Slightly slower, lower pitch. Occasionally pushes back on Nova.

Neither host is a narrator. They talk to each other, not to the microphone.

Step 5 — Episode structure

  1. Cold open (15–20s) — Nova opens on the single most striking fact or tension. No "welcome to the podcast", no channel branding, no music cues.
  2. Agenda tease (10s) — Miles lays out what they'll cover, casually.
  3. Story segments (60–90s each) — one item per segment. Pattern: hook → the facts → why it matters → a short exchange of interpretation → handoff line into the next story. Vary who leads each segment.
  4. Rapid fire (45s) — alternating one-liners on the leftover items, quick tempo.
  5. Close (20–30s) — three concrete takeaways split between the two hosts, then a short human sign-off. Alternate whether Nova or Miles ends.

Step 6 — Dialogue style

This is what makes it sound conversational rather than read-aloud.

  • Write spoken English, not written English. Contractions everywhere.
  • Keep most lines under 30 words. Break long explanations across two or three turns with the other host interjecting.
  • Use real conversational connective tissue — "okay so", "right", "wait, back up", "here's the part I didn't expect", "yeah, and that's the thing", "hmm". Roughly one marker every 4 to 5 turns. Never let it become a tic.
  • One host regularly asks the naive clarifying question so the other can explain.
  • Use one concrete analogy or comparison per complex item.
  • Genuine reactions are allowed ("that number is wild"). Invented opinions on people, companies, or politics are not.
  • Never read a headline verbatim. Paraphrase it into speech.
  • Attribute clearly: "according to the Financial Times", "Reuters is reporting".
  • If the source is ambiguous or a claim is unconfirmed, say so on air: "the report is careful to call that unconfirmed".
  • No stage directions, no "[laughs]", no speaker labels, no markdown, no emojis, no bullet points, and no URLs in the spoken text.

Step 7 — TTS hygiene

Applies to every word that will be spoken.

  • Spell out anything a synthesizer would mangle: "twenty twenty-six" not 2026, "three point two billion dollars" not $3.2B, "about fifteen percent" not ~15%.
  • First mention of an acronym: expand it, then use the short form.
  • Letter-by-letter acronyms: <say-as interpret-as="characters">API</say-as>.
  • Odd proper nouns: <sub alias="phonetic spelling">Name</sub>.
  • A non-English name or phrase inside an English line: <lang xml:lang="fr-FR">...</lang>.
  • Escape XML entities in all spoken text: & → &amp;, < → &lt;, > → &gt;.
  • Never emit smart quotes, em dashes, asterisks, or underscores.

Step 8 — Write the readable script

Write the human-readable transcript to:

/app/created/<slug>_Podcast_Script.txt

This file — and only this file — may carry NOVA: / MILES: speaker labels so a person can follow along. It contains no stage directions and no markdown. The spoken text itself must already satisfy Steps 6 and 7 so it can be lifted into SSML unchanged.

Step 9 — SSML output contract

Produce the SSML document and nothing else — no preamble, no explanation, no code fences, no trailing notes inside the artifact. Write it verbatim to:

/app/created/<slug>_Podcast.ssml

Rules:

  • Exactly one root <speak> element with version="1.0", xmlns="http://www.w3.org/2001/10/synthesis", xmlns:mstts="http://www.w3.org/2001/mstts", xml:lang="en-US".
  • One <voice> element per conversational turn. Alternate speakers. Never put both hosts inside one <voice> element.
  • Vary delivery with <prosody> so it never sounds flat. Baselines: Nova rate="+6%" pitch="+2%", Miles rate="-2%" pitch="-4%". Nudge per line to match the emotion of the sentence.
  • Use <mstts:express-as style="..."> where the voice supports it. Preferred styles: chat for banter, friendly for explanation, narration-professional for the factual core of a story, excited sparingly for the cold open. An unsupported style is ignored by the service, so keep styles optional — never structural.
  • Pauses: <break time="250ms"/> between turns within a segment, <break time="700ms"/> between segments, <break time="400ms"/> before a punchline or a pivot. Never exceed 900ms.
  • Every <break> must sit inside a <voice> element. A <break> placed between <voice> elements — as a direct child of <speak> — is invalid in a multi-voice document and will fail synthesis. Two <voice> elements may sit directly next to each other with nothing between them. To pause between turns, put the break at the end of the preceding turn's text, inside that turn's <prosody>.
  • <emphasis level="moderate"> on at most one or two key terms per segment.
  • Keep the total document under 40,000 characters.

Shape

<speak version="1.0"
       xmlns="http://www.w3.org/2001/10/synthesis"
       xmlns:mstts="http://www.w3.org/2001/mstts"
       xml:lang="en-US">
  <voice name="en-US-AvaMultilingualNeural">
    <mstts:express-as style="excited">
      <prosody rate="+8%" pitch="+3%">Okay, so the number that stopped me cold
      this morning was forty percent. <break time="300ms"/> Forty percent, in one
      quarter. <break time="250ms"/></prosody>
    </mstts:express-as>
  </voice>
  <voice name="en-US-AndrewMultilingualNeural">
    <mstts:express-as style="chat">
      <prosody rate="-2%" pitch="-4%">Right, and the part everyone's skipping is
      that it's off a very small base. <break time="250ms"/> Context matters
      here. <break time="700ms"/></prosody>
    </mstts:express-as>
  </voice>
</speak>

Note the trailing <break> closing each turn: the 250ms is the gap before the next turn, the 700ms is the longer gap before the next segment. Nothing sits between the two <voice> elements.

Step 10 — Review, then generate audio

Show the user a table summarising each segment (title, one-line description, approximate spoken duration), print both file paths, and ask:

Would you like me to convert this to an audio file?

Only if they say yes:

  1. Confirm the ConverttexttospeechwithSSML tool is available on the agent. If it is not, tell the user how to add it and stop.
  2. Call ConverttexttospeechwithSSML with the SSML document from Step 9 and outputFormat: riff-24khz-16bit-mono-pcm.
  3. Decode the base64 response and save to /app/created/<slug>_Podcast.wav.

If the document is too large for a single call, split it at a segment boundary, synthesize each part, and concatenate the decoded audio in order.

import base64

with open('<tool_output_file>', 'r') as f:
    content = f.read().strip()

audio_bytes = base64.b64decode(content)

with open('/app/created/<slug>_Podcast.wav', 'wb') as f:
    f.write(audio_bytes)

Step 11 — Final report

Always end with:

Item Details
Script file /app/created/<slug>_Podcast_Script.txt
SSML file /app/created/<slug>_Podcast.ssml
Word count / estimated duration actual vs. target at ~150 wpm
Items covered full segments + rapid-fire count
Voices en-US-AvaMultilingualNeural (Nova), en-US-AndrewMultilingualNeural (Miles)
Audio file /app/created/<slug>_Podcast.wav (only if audio generated)

04 同仓库更多 Skills

microsoft
microsoft/copilot-studio-gallery

dock-assignment-pass-pdf

Render the completed truck loading-dock assignment as a driver-facing one-page PDF.

文档处理
★ 16
microsoft
microsoft/copilot-studio-gallery

loading-dock-selector

Reason over weather, one current dock snapshot, optional ETA, and verified Drive Priority Pass to select and explain one loading dock.

★ 16
microsoft
microsoft/copilot-studio-gallery

newsletter-style-email-composer

Use when the user asks to email a report, findings, or metrics to someone as a polished, newsletter-style message. Builds an Outlook-safe HTML email from figures that already exist (headline, KPI tiles, up to two bar charts drawn with HTML table cells so they render in classic Outlook, Gmail and dark mode, short findings, data notes and the non-audit disclaimer) using the shared brand tokens, attaches the PDF report, and creates a draft for the user to review. Do NOT use for a short plain-text status update, or for building the underlying analysis, charts, or report itself -- this skill only composes the email.

文档处理邮件与沟通
★ 16
microsoft
microsoft/copilot-studio-gallery

polished-report-builder

Use when the user asks to turn analysis results, metrics, or findings into a polished, presentation-ready report, one-pager, or executive summary -- especially when existing analysis (e.g. from the spreadsheet analysis skill) needs to become a document someone will actually read. Builds a branded PDF with reportlab from a short content file (headline, KPI tiles, one chart per point, data notes and the non-audit disclaimer) using the shared brand tokens, and runs a QA pass before delivery to catch walls of text, chart clutter, low-resolution charts, missing data notes or poor contrast. Do NOT use for a quick inline chat answer, a single ad-hoc chart with no report structure around it, a raw data export with no narrative, or to compute the figures themselves.

行政与办公人员文档处理
★ 16
microsoft
microsoft/copilot-studio-gallery

spreadsheet-data-analysis-reporting

Use for any request that needs figures from the sales spreadsheets (Excel/CSV), even a single file or a single period - e.g. 'analyse Q4', 'how did sales do last month', 'compare regions', YoY/MoM/QoQ/YTD growth, top products, share of revenue, trends, outliers, currency-converted totals, or building/updating a consolidated master file. Finds and loads the relevant files, cleans and normalises them, computes metrics with standard definitions and edge-case handling, flags outliers and data issues, explains every transformation, and produces on-brand charts. Use this before the report or email skills whenever numbers must be computed. Do NOT use for questions that need no data (e.g. 'what does YoY mean') or for re-formatting results already computed in this conversation.

数据分析师电子表格分析与可视化
★ 16
microsoft
microsoft/copilot-studio-gallery

internal-consistency-review

Use when the user asks for the Internal Consistency Review of a contract, or asks to check a contract for internal conflicts, inconsistencies between sections, or gaps and unfilled elements. Do NOT use for comparing the contract against external law - that is the separate Legal Compliance Review skill.

律师与法务
★ 16