القائمة
Songwriting craft and Suno AI music prompts.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Use when a problem or request is underspecified and you need to decide WHAT to clarify before doing the work — the NEXT-BEST QUESTIONS to answer, ranked. Interrogates the prompt into candidate questions, projects plausible answers with probabilities, estimates each question's value of information (how much the answer would change the recommended plan, weighted by likelihood and stakes), discards low-value/redundant ones, and keeps generating until a diverse bucket of high-value questions is filled. Reports a ranked list with recommendations (pre-answer / assume-default) using role-specialized local Ollama models. Reports only — it does not ask the user or answer the questions itself. Triggers: "what should I clarify", "what questions matter here", "is this spec complete", "what am I missing before I start".
Use to run one improvement iteration on the next-best-questions skill: review its learnings journal, research opportunities, pre-register a cost-aware experiment, build off-default, evaluate Δresult AND Δcost, and journal the verdict either way. Triggers: 'improve nbq', 'run the nbq loop', 'next-best-questions iteration'. There are NO scripts; this protocol is agent-executed.
Prompt any model or alias via "ask <model> <question>". Resolves short names (deepseek, kimi, qwen, glm) to full model IDs. Captures session IDs for follow-up questions. Comparison mode: "ask deepseek kimi <question>" dispatches multiple models in parallel. Each call is a full Hermes agent with tools and multi-turn reasoning. Replies inline with a model badge.
Autonomous end-to-end build/debug engine. Use it when asked to build, implement, fix, or debug a module/feature: it runs the WHOLE loop unattended — drafts a checkable Definition of Done, fail-closed gates it (vague or ambiguous requests come back with the blocking questions instead of guesses), generates tests, then loops implement -> lint -> evidence until coverage + two distinct-model judges + real exit codes + a whole-suite regression gate all pass — and on COMPLETE AUTO-MERGES the work into the target repo's current branch (no repo named = a fresh workspace under the write-safe root is the deliverable). Prefer this over the `dev` skill for any multi-file task whose outcome should be verified, merged code rather than role-by-role assistance. NOT for trivial one-shot asks (a quick answer, a one-line edit, running a command) — just do those directly. Run: `devloop "<request>" [--repo PATH]` (or python3 ${HERMES_HOME}/skills/software-development/devloop/scripts/devloop_cli.py) — see "How to run".
An LLM authors a JSON/YAML workflow spec (states, prompts, routing, failure policy); a durable interpreter runs it, passing state from step to step, with suspend/resume, human gates, and replay that never re-runs completed steps. Use when an LLM should define-and-run a multi-step workflow that must pause for a human (approve, decide, fix something) and resume later, survive a crash and continue exactly once, or route declaratively on step errors. Rides a durable-execution-lite engine (append-only journal, deterministic replay). Triggers: LLM-authored workflow, workflow spec, prompt routing, durable resume, resumable script, pause and resume, checkpoint and continue, don't re-run completed steps.
Cron job that reviews Hermes conversation history and captures durable knowledge into the wiki. Handles triage (SKIP/NOTE/PAGE), Slack-session cleanup, and post-capture lint.
| name | songwriting-and-ai-music |
| description | Songwriting craft and Suno AI music prompts. |
| tags | ["songwriting","music","suno","parody","lyrics","creative"] |
| platforms | ["linux","macos","windows"] |
| triggers | ["writing a song","song lyrics","music prompt","suno prompt","parody song","adapting a song","AI music generation"] |
| version | 1.0.0 |
| author | Fortified Strength |
| license | MIT |
| metadata | {"hermes":{"config":[{"key":"songwriting-and-ai-music.enabled","description":"Enable songwriting-and-ai-music skill behavior","default":true,"prompt":"Enable songwriting-and-ai-music skill?"}],"tags":["songwriting"],"category":"creative"}} |
Everything here is a GUIDELINE, not a rule. Art breaks rules on purpose. Use what serves the song. Ignore what doesn't.
Common skeletons — mix, modify, or throw out as needed:
ABABCB Verse/Chorus/Verse/Chorus/Bridge/Chorus (most pop/rock)
AABA Verse/Verse/Bridge/Verse (refrain-based) (jazz standards, ballads)
ABAB Verse/Chorus alternating (simple, direct)
AAA Verse/Verse/Verse (strophic, no chorus) (folk, storytelling)
The six building blocks:
You don't need all of these. Some great songs are just one section that evolves. Structure serves the emotion, not the other way around.
RHYME TYPES (from tight to loose):
Mix them. All perfect rhymes can sound like a nursery rhyme. All slant rhymes can sound lazy. The blend is where it lives.
INTERNAL RHYME: Rhyming within a line, not just at the ends. "We pruned the lies from bleeding trees / Distilled the storm from entropy" — "lies/flies," "trees/entropy" create internal echoes.
METER: The rhythm of stressed vs unstressed syllables.
Think of a song as a journey, not a flat road.
ENERGY MAPPING (rough idea, not prescription): Intro: 2-3 | Verse: 5-6 | Pre-Chorus: 7 Chorus: 8-9 | Bridge: varies | Final Chorus: 9-10
The most powerful dynamic trick: CONTRAST.
"Whisper to roar to whisper" — start intimate, build to full power, strip back to vulnerability. Works for ballads, epics, anthems.
SHOW, DON'T TELL (usually):
THE HOOK:
PROSODY — lyrics and music supporting each other:
AVOID (unless you're doing it on purpose):
When rewriting an existing song with new lyrics:
THE SKELETON: Map the original's structure first.
FITTING NEW WORDS:
CONCEPT:
KEEP SOME ORIGINALS: Leaving a few original lines or structures intact adds recognizability and lets the audience feel the connection.
FORMULA (adapt as needed): Genre + Mood + Era + Instruments + Vocal Style + Production + Dynamics
BAD: "sad rock song"
GOOD: "Cinematic orchestral spy thriller, 1960s Cold War era, smoky
sultry female vocalist, big band jazz, brass section with
trumpets and french horns, sweeping strings, minor key,
vintage analog warmth"
DESCRIBE THE JOURNEY, not just the genre:
"Begins as a haunting whisper over sparse piano. Gradually layers
in muted brass. Builds through the chorus with full orchestra.
Second verse erupts with raw belting intensity. Outro strips back
to a lone piano and a fragile whisper fading to silence."
TIPS:
STRUCTURE: [Intro] [Verse] [Verse 1] [Pre-Chorus] [Chorus] [Post-Chorus] [Hook] [Bridge] [Interlude] [Instrumental] [Instrumental Break] [Guitar Solo] [Breakdown] [Build-up] [Outro] [Silence] [End]
VOCAL PERFORMANCE: [Whispered] [Spoken Word] [Belted] [Falsetto] [Powerful] [Soulful] [Raspy] [Breathy] [Smooth] [Gritty] [Staccato] [Legato] [Vibrato] [Melismatic] [Harmonies] [Choir] [Harmonized Chorus]
DYNAMICS: [High Energy] [Low Energy] [Building Energy] [Explosive] [Emotional Climax] [Gradual swell] [Orchestral swell] [Quiet arrangement] [Falling tension] [Slow Down]
GENDER: [Female Vocals] [Male Vocals]
ATMOSPHERE: [Melancholic] [Euphoric] [Nostalgic] [Aggressive] [Dreamy] [Intimate] [Dark Atmosphere]
SFX: [Vinyl Crackle] [Rain] [Applause] [Static] [Thunder]
Put tags in BOTH style field AND lyrics for reinforcement. Keep to 5-8 tags per section max — too many confuses the AI. Don't contradict yourself ([Calm] + [Aggressive] in same section).
AI vocalists don't read — they pronounce. Help them:
PHONETIC RESPELLING:
DELIVERY CONTROL:
ALWAYS:
EXPECT: ~3-5 generations per 1 good result. Revision is normal. Style can drift in extensions — restate genre/mood when extending.