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Speech Adaptation

  • 319 installs
  • 133 repo stars
  • Updated February 24, 2026
  • jwynia/agent-skills

speech-adaptation is a generative agent skill that compresses comprehensive written content into purposeful spoken guidance for developers producing podcasts, presentations, and voice-assistant audio from documentation.

About

speech-adaptation is a generative utility skill (version 1.0, MIT license) from jwynia/agent-skills that transforms comprehensive written content into purposeful spoken guidance. Speech requires roughly 3-5x compression while maintaining functional value, so the skill restructures dense prose into listenable scripts suited for podcasts, presentations, voice assistants, and audio courses. Developers reach for speech-adaptation when converting blog posts, tutorials, or internal docs into narration, optimizing copy for listening comprehension, or adapting dialogue voice and dialect per character while preserving identity across scenes. The skill applies domain-specific writing rules for pacing, emphasis, and oral clarity rather than simple summarization. It fits content pipelines where written technical material must become high-quality audio without losing actionable guidance.

  • Voice consistency
  • Dialect control
  • Character speech
  • Tone matching
  • Dialogue style

Speech Adaptation by the numbers

  • 319 all-time installs (skills.sh)
  • +2 installs in the week ending Aug 2, 2026 (Skillselion tracking)
  • Ranked #497 of 1,335 Generative Media skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/jwynia/agent-skills --skill speech-adaptation

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Listed on Skillselion
Installs319
repo stars133
Last updatedFebruary 24, 2026
Repositoryjwynia/agent-skills

How do you adapt written docs for audio?

Adapt dialogue voice, dialect, and speech patterns per character or audience while keeping identity consistent across scenes and generated responses.

Who is it for?

Technical writers and developer advocates converting long-form documentation, tutorials, or articles into podcast episodes and presentation narration.

Skip if: Developers who only need text-to-speech synthesis without rewriting content structure for oral delivery.

When should I use this skill?

User asks to convert written content to spoken format, adapt for podcasts, optimize for listening, or create audio from documentation.

What you get

Spoken scripts, podcast narration drafts, and presentation voiceover copy optimized for listening.

  • Spoken scripts
  • Podcast narration drafts

By the numbers

  • Targets 3-5x compression from written to spoken format
  • Skill version 1.0 in jwynia/agent-skills repository

Files

SKILL.mdMarkdownGitHub ↗

Speech Adaptation

Purpose

Transform comprehensive written content into purposeful spoken guidance. Speech requires 3-5x compression while maintaining functional value. Apply when converting written content to audio, podcasts, presentations, or voice assistant responses.

Core Principle

Lead with value, earn attention. Listeners can't skim. Front-load what matters and offer expansion rather than exhaustive delivery.

---

Functional Intent Detection

Parse the original question/content for intent:

Intent TypeSignalsFocus
Problem-solving"How do I..."Actionable steps
Learning"What is..."Core concepts + examples
Decision-making"Should I..."Key considerations + recommendation
Troubleshooting"Why isn't..."Likely causes + solutions

Context Signals

Signal TypeExamplesAdaptation
Urgency"today", "now", "urgent"Compress to immediate next steps
Scope"huge", "complex", "overwhelming"Lead with simplification
Experience"beginner", "new to"Increase explanation, decrease jargon
Personal stakes"I", "my project"Increase specificity, decrease abstraction

---

Content Transformation Principles

1. Hierarchical Restructuring

Written: Lists methods 1-7 equally Spoken: "There are three main approaches. Start with [most relevant]. If that doesn't work, try [backup]."

2. Front-Load Value

Written: Builds up to key insights Spoken: Lead with core insight, then supporting details if needed

3. Compress Conceptual Space

Written: Seven distinct frameworks Spoken: "Basically three strategies: sort by importance, limit your focus, or batch similar work"

4. Context-Dependent Detail

Written: Explains everything at same depth Spoken: Start simple, indicate where more detail is available

  • "Use a priority matrix - urgent versus important"
  • Optional expansion cue: "I can break down those four categories if helpful"

5. Eliminate Structural Artifacts

Remove in Speech:

  • Section headers read verbatim
  • Bullet point enumeration
  • Visual formatting cues
  • Redundant category labels

Add for Speech:

  • Transition phrases between ideas
  • Purpose statements before methods
  • Summary/recap statements

6. Progressive Revelation Strategy

1. Core insight (one sentence) 2. Primary recommendation (actionable step) 3. Backup approach (if primary doesn't fit) 4. Availability cue for additional methods

---

Implementation Guidelines

Pre-Processing Steps

1. Parse original question for functional intent and context signals 2. Identify 1-2 most relevant pieces for their specific need 3. Determine appropriate compression ratio based on urgency/complexity

Content Selection Rules

ContextSelection
High urgency1 primary method + 1 backup
Learning focusedCore concept + 1 detailed example + availability of more
Decision supportKey considerations + clear recommendation
Complex topicSimplify conceptual framework first, offer detail expansion

Speech-Specific Adaptations

  • Replace structural language with functional language
  • Add explicit transitions between ideas
  • Use pronouns and referential terms to avoid repetition
  • Include "escape valves" for different user needs
  • End with clear next step or summary

---

Quality Checks

TestQuestion
CompressionIs this 30-50% of original length?
CompletenessDoes this answer their core question?
FlowWould this make sense heard linearly?
ActionDo they know what to do next?

---

Example Transformation

Question Type: Immediate problem-solving with overwhelm signals

Written Response: 7 methods with full explanations

Spoken Adaptation: 1. Acknowledge state: "When facing a huge list..." 2. Core insight: "The key is separating what needs doing from what feels urgent" 3. Primary action: "Try this: scan for things both urgent AND important" 4. Boundary setting: "Pick just 3 - more than that sets you up to feel behind" 5. Escape valve: "Other approaches available if this doesn't click"

---

Success Metrics

  • User can act immediately after listening
  • Cognitive load feels manageable
  • Key insights retained after single hearing
  • Optional detail access feels natural when needed

---

Integration Points

Inbound:

  • From written documentation or articles
  • From comprehensive analysis outputs
  • From detailed framework content

Outbound:

  • To audio content production
  • To presentation delivery
  • To voice assistant responses

Complementary:

  • presentation-design: For visual + spoken coordination
  • dialogue: For conversational delivery patterns

Anti-Patterns

1. Uniform Compression

Pattern: Reducing all content by the same ratio regardless of importance. Why it fails: Not all content is equal. Some ideas need full explanation; others can be summarized in a phrase. Equal compression buries critical insights and pads trivial ones. Fix: Identify the 1-2 most important points. Protect those while ruthlessly compressing supporting material. Lead with what matters most.

2. Written Sentences Spoken

Pattern: Reading written prose aloud without restructuring for speech patterns. Why it fails: Written and spoken language have different rhythms, sentence structures, and information density. Written sentences spoken sound formal, awkward, and hard to follow. Fix: Restructure for oral delivery. Shorter sentences. More personal pronouns. Explicit transitions. Repetition for emphasis. Natural breathing points.

3. Exhaustive Completeness

Pattern: Including all information from the written source because "it might be important." Why it fails: Listeners can't skim, reread, or control pace. Information overload in speech creates immediate cognitive overload and retention collapse. Fix: Accept that spoken content is selective. Provide escape valves: "More on this if helpful." Trust that listeners can ask for expansion rather than front-loading everything.

4. Missing Signposts

Pattern: Moving between ideas without explicit verbal transitions. Why it fails: Listeners can't see paragraph breaks or headings. Without verbal signposts, ideas blur together. The structure becomes invisible. Fix: Add explicit transitions: "First..." "More importantly..." "Here's the key point..." "Moving on to..." Make the structure audible.

5. Buried Action

Pattern: Leaving actionable recommendations for the end after extensive context. Why it fails: Listeners who zone out during context miss the action items. Those still engaged have forgotten the details by the time recommendations arrive. Fix: Front-load action with context to follow. "Do X. Here's why..." rather than "Here's all the context, therefore do X."

Integration

Inbound (feeds into this skill)

SkillWhat it provides
prose-styleWritten content quality to work from
(written documentation)Source material for adaptation

Outbound (this skill enables)

SkillWhat this provides
presentation-designSpoken content structure for slide coordination
(audio production)Scripts ready for recording
(voice assistants)Responses optimized for spoken delivery

Complementary

SkillRelationship
presentation-designSpeech-adaptation handles the spoken component; presentation-design coordinates visual and spoken elements
dialogueSpeech-adaptation for informational delivery; dialogue for conversational and dramatic speech patterns

Related skills

FAQ

What compression ratio does speech-adaptation target?

speech-adaptation targets 3-5x compression of comprehensive written content while maintaining functional value, restructuring dense prose into purposeful spoken guidance for podcasts and presentations.

When should developers use speech-adaptation?

speech-adaptation applies when converting written material to audio, optimizing content for listening, creating podcast narration from docs, or adapting speech patterns per character while keeping identity consistent.

Generative Mediallmagentsautomation

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