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Musical DNA Analysis

Purpose

Extract descriptive musical characteristics from any artist or band without using their name , building a vocabulary of sonic qualities for AI music generation, music description, or creative recombination. Replace "sounds like [Artist]" with specific, technique-focused descriptions.

Core Principle

How, not who. Describe techniques, approaches, and sonic qualities rather than referencing artists. This enables:

• Ethical AI music generation
• Precise communication about sound
• Creative recombination of elements
• Genre-independent vocabulary

Quick Reference: Six Dimensions

Analysis Process

Step 1: Select Representative Tracks

Choose 3-5 tracks that capture:

• Their most recognizable sound
• Range across their catalog
• Both typical and boundary-pushing examples

Step 2: Systematic Deconstruction

Work through each dimension, focusing on specific techniques and approaches.

Step 3: Extract Prompt-Ready Phrases

Convert observations into standalone descriptive phrases that work without artist context.

Dimension 1: Rhythmic Foundation

Drum Character

• Kit composition : Acoustic, electronic, hybrid, sampled
• Stick technique : Brushes, rods, mallets, standard sticks
• Snare approach : Rim shots, ghost notes, cross-stick, tight vs. ringy
• Kick pattern : Four-on-floor, syncopated, polyrhythmic, sparse
• Hi-hat work : Open/closed patterns, 16th note rides, swung
• Fill style : Busy, minimal, tom-heavy, snare rolls

Time & Tempo

• Time signatures : 4/4, 3/4, 6/8, odd meters (5/4, 7/8)
• Tempo range : Locked BPM or flexible? Fast, mid, slow?
• Subdivision emphasis : 8ths, 16ths, triplets, swung
• Polyrhythmic layering : Multiple meters happening simultaneously

Bass Line DNA

• Technique : Fingered, picked, slapped, synth, upright
• Role : Rhythmic anchor vs. melodic counterpoint
• Range : Sub-bass heavy, mid-focused, full range
• Kick relationship : Locked, complementary, independent

Example Phrases:

• "Driving 8th-note hi-hat over syncopated kick"
• "Slapped bass with muted ghost notes"
• "Swung triplet feel at 95 BPM"

Dimension 2: Harmonic Architecture

Chord Progressions

• Major/minor balance : Predominantly one or mixed?
• Modal inflections : Dorian darkness, Mixolydian brightness
• Chromatic movement : Smooth voice leading, sudden shifts
• Chord density : Triads, 7ths, extended (9ths, 11ths, 13ths)
• Harmonic rhythm : Slow changes (1/bar) or rapid (2+/bar)

Tonal Centers

• Key preferences : Sharp keys, flat keys, open-string friendly
• Modulation : None, gradual, sudden, frequent
• Scale choices : Natural minor, harmonic minor, pentatonic, modes
• Dissonance tolerance : Clean resolution, lingering tension

Melodic Contour

• Range : Wide intervals or narrow
• Movement : Stepwise, leaping, arpeggiated
• Phrase length : Short punchy or long flowing
• Repetition balance : Hooks vs. development

Example Phrases:

• "Minor key with Dorian 6th inflection"
• "Slow harmonic rhythm, one chord per 4 bars"
• "Wide interval leaps in vocal melody"

Dimension 3: Instrumental Techniques

Guitar Approaches

• Pickup selection : Bridge (bright), neck (warm), split
• Tone shaping : Treble-forward, mid-scoop, bass-heavy
• Technique : Fingerpicking, flatpicking, hybrid, percussive
• Tuning : Standard, drop D, open tunings, baritone

Effects Chain

• Distortion type : Overdrive, fuzz, high-gain, clean
• Time-based : Reverb (room, hall, plate), delay (analog, digital, tape)
• Modulation : Chorus, phaser, flanger, tremolo, vibrato
• Pitch : Octave, harmonizer, whammy
• Dynamics : Compression (heavy, light, none)

Other Instruments

• Keys/synth : Analog warmth, digital precision, organ, piano
• Percussion : Auxiliary (tambourine, shaker), world instruments
• Brass/strings : Section vs. solo, dry vs. lush
• Electronics : Samples, loops, glitches, synthesis

Example Phrases:

• "Neck pickup through mild tube overdrive"
• "Slap-back delay with plate reverb"
• "Fingerpicked acoustic with percussive body hits"

Dimension 4: Production Aesthetics

Spatial Characteristics

• Environment feel : Professional studio, live room, bedroom, outdoor
• Reverb treatment : Dry, intimate, expansive, cavernous
• Stereo field : Wide, narrow, mono-compatible
• Depth staging : Everything forward, layered front-to-back

Mix Philosophy

• Prominence hierarchy : Drums-first, vocal-forward, guitar-heavy
• Frequency allocation : Each instrument's spectral home
• Dynamic range : Compressed, dynamic, limiting
• Clarity vs. saturation : Pristine separation vs. glued warmth

Sonic Texture

• Signal path : Clean, saturated, distorted, degraded
• High frequency : Bright, airy, rolled-off, harsh
• Low end : Tight, boomy, sub-heavy, absent
• Midrange : Scooped, present, honky, balanced

Example Phrases:

• "Bedroom recording aesthetic with lo-fi saturation"
• "Drum-forward mix with tight low end"
• "Vintage tape warmth with rolled-off highs"

Dimension 5: Genre Fusion Analysis

Influence Mapping

• Primary foundation : The dominant genre base (60%+)
• Secondary elements : Strong secondary influence (20-30%)
• Tertiary accents : Occasional flavor (10% or less)

Integration Methods

• Temporal placement : Genre X in verses, genre Y in choruses
• Instrumental assignment : Drums from A, guitars from B
• Transition approach : Seamless blend vs. jarring contrast
• Era mixing : Vintage techniques + modern production

Innovation Points

• Boundary crossing : Where conventions are broken
• Novel combinations : Unexpected genre marriages
• Signature fusion : Their unique contribution

Example Phrases:

• "Math rock precision over post-punk foundation"
• "Hip-hop production sensibility applied to folk songwriting"
• "Grunge dynamics with shoegaze texture"

Dimension 6: Energy Architecture

Song Structure

• Intro character : Atmospheric, punchy, fade-in, cold start
• Verse energy : Pulled back, driving, building
• Chorus intensity : Lift, explosion, subtle shift
• Bridge/breakdown : Contrast, climax, reflection
• Outro approach : Fade, stop, resolve, evolve

Dynamic Range

• Intensity curves : Gradual build, sudden shifts, flat line
• Peak placement : Early, middle, late, multiple
• Release patterns : Sudden drop, gradual decay

Emotional Trajectory

• Mood arc : Single state, journey, oscillation
• Tension cycles : Build-release frequency
• Climax character : Cathartic, devastating, transcendent

Example Phrases:

• "Slow build across 4 minutes to explosive final chorus"
• "Sudden dynamic drops creating tension"
• "Verse-chorus contrast via density rather than volume"

Documentation Template

One-Sentence DNA

[Rhythmic approach] + [harmonic character] + [instrumental signature] + [production aesthetic]

Example: "Syncopated post-punk drumming over minor modal progressions, angular clean guitar with chorus effect, dry room recording with bass-forward mix"

Detailed Breakdown

## Rhythmic Signature
- Time feel:
- Drum character:
- Bass approach:
- Syncopation style:

## Harmonic DNA
- Chord tendencies:
- Scale preferences:
- Progression patterns:

## Instrumental Character
- Guitar tone/technique:
- Effects signature:
- Other key instruments:

## Production Fingerprint
- Recording aesthetic:
- Mix characteristics:
- Sonic texture:

## Genre Fusion Map
- Primary foundation:
- Secondary elements:
- Innovation points:

## Energy Architecture
- Typical structure:
- Dynamic range:
- Build patterns:

Extractable Prompt Elements

List 5-10 standalone phrases usable in AI generation:

• "..."
• "..."

Ethical Guidelines

Do

• Combine elements from multiple analyses
• Focus on techniques and approaches
• Build reusable vocabulary
• Create novel fusions

Don't

• Copy complete profiles directly
• Replicate signature riffs/melodies
• Use as "sounds like [Artist]" substitute
• Claim to reproduce specific artists

Anti-Patterns

1. The Name Drop

Pattern: Using artist names as shorthand instead of technique descriptions. "Sounds like Radiohead" instead of describing the actual sonic qualities. Why it fails: Defeats the entire purpose. Artist names are black boxes that convey different things to different people and may produce copyright issues in AI generation. Fix: Never use artist names in final output. For every "sounds like X," unpack what that actually means in terms of rhythm, harmony, production, etc.

2. The Single Dimension

Pattern: Analyzing only one dimension (usually rhythm or production) while ignoring others. Producing incomplete profiles. Why it fails: Musical identity emerges from interaction of all dimensions. A rhythmic profile without harmonic context is useless for generation. Fix: Force yourself through all six dimensions. Even if an artist seems "about the guitar sound," their rhythmic choices matter.

3. The Genre Substitute

Pattern: Describing music by genre labels instead of techniques. "Post-punk" instead of describing what makes it post-punk. Why it fails: Genre labels are contested categories, not techniques. AI systems need concrete instructions, not genre negotiations. Fix: Treat genre labels as starting points requiring unpacking. What rhythmic, harmonic, and production choices define this genre for this artist?

4. The Representative Track Trap

Pattern: Analyzing one famous song and extrapolating to entire catalog. Missing range and evolution. Why it fails: Artists vary. Their most famous song may not be representative. Analysis from one track produces narrow profiles. Fix: Analyze 3-5 tracks from different periods and modes. Look for both constants and variations.

5. The Technical Overdose

Pattern: Including so much technical detail that prompts become unusable. Every possible parameter specified. Why it fails: AI generation systems can't process unlimited context. Overly detailed prompts get truncated or confuse the model. Fix: Distill to 5-10 essential phrases. Prioritize what makes this artist distinct rather than comprehensive.

Integration Points

Inbound:

• From listening to music you want to analyze

Outbound:

• To AI music generation prompts
• To lyric-diagnostic for complete song analysis

Complementary:

• lyric-diagnostic: Lyrical analysis (words)
• This skill: Musical analysis (sounds)

Weekly Installs

133

Repository

jwynia/agent-skills

GitHub Stars

37

First Seen

Jan 20, 2026

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