Lyrics and songwriting — original lyrics for pop, rock, hip-hop, R&B, folk, electronic, classical vocal, Chinese-style (中国风), and all musical genres. Handles verse-chorus structure, rhyme schemes, syllable fitting, hook writing, singability, and AI music platform integration.
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name
lyrics
type
capability
description
Lyrics and songwriting — original lyrics for pop, rock, hip-hop, R&B, folk, electronic, classical vocal, Chinese-style (中国风), and all musical genres. Handles verse-chorus structure, rhyme schemes, syllable fitting, hook writing, singability, and AI music platform integration.
Lyrics Writing
Orchestrator dispatches all creation and review work to subagents. Before creation, copy user-uploaded files to /mnt/agents/output/research/.
Sub-skill of general-writing. Inherits shared creative writing principles, anti-AI discipline, and quality gate framework.
CRITICAL — Review → Fix Brief → Dispatched Subagent: When a review finds issues, translate them into a detailed fix brief (file paths, quoted findings, expected outcome, scope boundary, self-check) and dispatch a fresh lyrics_writer subagent to apply the fix. Never use inline sed/edit_file fixes.
CRITICAL — Anti-Read-Loop Rule: The orchestrator must dispatch its first subagent (lyrics_writer) within 10 iterations. If the orchestrator has spent 10+ iterations only reading files without creating any subagent, it is in a read-loop. Stop reading, draft your structural plan from what you have, and dispatch the writer immediately.
CRITICAL — .docx / .txt Delivery: Every completed song must be converted to .docx using skills/docx/SKILL.md. For Suno/AI music platform targets, also produce a .txt file with meta-tags. Never end a session with only raw section files and no assembled deliverable.
File Paths
Output: /mnt/agents/output/
{project_name}.{song_title}.md # Song lyrics
{project_name}.{song_title}.suno.txt # Suno meta-tags (if requested)
research/ # User uploads (melody refs, mood boards)
User Query
│
├─ Provides existing lyrics + asks for revision → Stage 3 → Assembly
├─ Provides melody/structure + asks for lyrics → Stage 2 → Stage 3 → Assembly
└─ New request → Infer parameters (see below) → Stage 1 → Stage 2 → Stage 3 → Assembly
Infer genre, structure, emotional arc, melody reference, target platform, and language register from the user's request. The orchestrator analyzes and infers all parameters autonomously; for complex requests, deploy a subagent to analyze requirements in depth. Never prompt the user for clarification.
Stage 1: Conception
Orchestrator produces a structural plan:
Section order (from template, adjusted to song's needs). Common templates:
If melody reference provided: extract syllable counts per phrase, stress patterns, breath points
If for AI music platform: draft style tags (genre, instrumentation, vocal style, mood, tempo — 300-500 chars)
Save to /mnt/agents/output/{filename}.agent.outline.md.
Stage 2: Creation
Read ../anti-ai.md — inline its content into writer system prompts.
Write chorus FIRST. The chorus is the song's center of gravity. Horse-race 2-3 chorus variants — dispatch parallel subagents with different approaches.
Strictly one section per task call (chorus, verse, bridge each dispatched separately).
create_subagent:
name: "lyrics_writer"
system_prompt: Compose from these elements: (1) Role: "You are a songwriter writing [genre] lyrics in [language]." (2) Song structure template: Inline the full section order, line counts, and emotional arc per section. (3) Singability rules: "Singability overrides literary merit. Every line must pass the read-aloud test. Rules: (a) stressed syllables land on downbeats; (b) breath points at natural grammatical breaks; (c) no consonant clusters (str-, spl-, nkths) on fast passages; (d) open vowels (ah, oh, oo, ee) on sustained/high notes; (e) closed vowels (uh, ih) never on held notes." (4) Genre conventions: Pop — conversational register, emotional directness, strong hook; Hip-hop — internal rhyme density, wordplay, flow, punch lines; 古风 — classical imagery (意象), 四字词, 典故, elegant register; Ballad — emotional vulnerability, simple language, quiet-to-intense build. (5) Anti-AI rules: Inline from ../anti-ai.md plus lyrics-specific: "No 'journey of self-discovery.' No 'stand tall in the face of adversity.' No 'wings to fly' / 'light in the darkness' without earned context. No perfectly grammatical singing — use contractions, fragments, repetition. No every-line-same-length." (6) Narrative-to-lyric rule: "When source material is a story, concept, or experience, convert to metaphor and sensory imagery. FORBIDDEN: naming literal specifics (place names, dates, technical terms) unless they serve as deliberate poetic anchors. Test: could a listener not in on the context still feel the emotion? If no, it's too literal."
description: "Write song lyrics per structural plan"
Dispatch chorus horse-race — task (2-3 parallel):
agent: "lyrics_writer"
prompt: "Write [genre] chorus. Hook concept: [concept]. Variant [A/B/C] — explore [different hook phrasing / different imagery / different rhythmic pattern]. Rhyme scheme: [scheme]. Syllable targets: [targets]. This is the emotional peak of the song."
Save each to /mnt/agents/output/{filename}_chorus_{A|B|C}.md
Present chorus variants to user. After selection:
Dispatch remaining sections — task (one section per call):
agent: "lyrics_writer"
prompt: "Write [section name] for [genre] song. Chorus (selected): [inline or path]. Emotional arc position: [setup/tension/shift/resolution]. Rhyme scheme: [scheme]. Syllable targets: [targets]. Tempo guidance: [BPM feel or qualitative]. The verse must build toward the chorus; the bridge must contrast it." Include structural plan, selected chorus, melody reference (if exists).
Save to /mnt/agents/output/{filename}_sec{NN}.md
Word Count Verification
After each completed section, orchestrator runs:
python skills/general-writing/scripts/check_wordcount.py <file> --min {target} --lang auto
If FAIL, return to writer with expansion instructions.
Stage 3: Review
Read ../review.md first. Follow the shared pipeline, then add genre-specific editor.
Shared Pipeline (from review.md)
For lyrics (short form), continuity_editor is lightweight. style_editor checks AI-pattern absence and voice consistency across sections. structural_editor verifies emotional arc and section balance.
Genre-Specific Editor
singability_checker — The critical lyrics-specific reviewer.
create_subagent:
name: "singability_checker"
system_prompt: "You perform phonetic analysis of lyrics for singability. Check: (1) syllable stress alignment with intended downbeats; (2) breath point placement at natural phrase boundaries; (3) consonant clusters that would be unsingable at tempo; (4) vowel quality on sustained/high notes (open vowels required); (5) tongue-twister detection; (6) line length variation (monotone lengths = algorithmic). Output: PASS or FAIL with specific line numbers and fixes."
description: "Phonetic singability analysis"
task:
agent: "singability_checker"
prompt: Include all section file paths, structural plan (syllable targets, tempo), melody reference if available.
Iterative loop: flag unsingable phrases → write a fix brief (specific lines, phonetic issues, suggested alternatives) and dispatch a fresh lyrics_writer subagent to apply the fix → re-check. Max 2 rounds. For multi-song projects: if a song fails review twice, mark remaining issues and move on.
Style tags: Include at top of final file. Format: genre + subgenre, instrumentation, vocal style, mood/dynamics, tempo (300-500 chars)
Lyrics-music alignment: sparse lyrics for slow songs, denser for uptempo; place strongest emotional words at melodic peaks; chorus lyrics must carry repetition; use [Instrumental] and [Break] for breathing room
Translation / Adaptation Mode
When user provides lyrics in one language and requests adaptation to another:
Match syllable count per line (+-2 syllables acceptable)
Preserve stressed syllables on downbeats across languages
Apply singability_checker to BOTH source and target versions
Prioritize how the line sounds sung over literal accuracy
Assembly
Concatenate all sections in structural order with section labels: [Verse 1], [Pre-Chorus], [Chorus], [Bridge], [Outro], etc.
If Suno/AI platform: prepend style tags at top of file
Save to /mnt/agents/output/{filename}.agent.final.md
Convert to .docx using the md2docx pipeline (see skills/docx/SKILL.md → references/md2docx-reference.md). Output: /mnt/agents/output/{filename}.agent.final.docx. For Suno/AI platform targets, the .suno.txt file is also a primary deliverable.
Delivery is mandatory. Raw section files without an assembled deliverable (.docx or .txt) is not an acceptable end state.
