spoken-longform-dialogue

name	spoken-longform-dialogue
description	Transform scenes with long dialogue or monologue into human-feeling spoken thought using transcript-derived storytelling patterns. Use when revising fiction, memoir, essays, scripts, interviews, or book dialogue where one speaker needs to hold the floor across multiple paragraphs without sounding like exposition, lecture, AI prose, or a clean essay.

Spoken Longform Dialogue

Purpose

Use this skill to make long spoken sections feel like a real person thinking, remembering, correcting themselves, and steering a listener through a point. The model source is professional long-form speech from interviews and talks, not the advice topic itself.

Core Equation

Long dialogue works when it combines:

argument + wound + object + listener

• argument: what the speaker claims or tries to explain.
• wound: why the speaker cannot say it neutrally.
• object: the physical anchor keeping the speech embodied.
• listener: the pressure of another person hearing it now.

If a long turn has only argument, compress it or rewrite it.

Revision Workflow

1. Identify why this speaker gets a long turn now.

   • Use a trigger line: "No.", "That is not what happened.", "I can answer that, but not quickly."
   • Do not let a character speak for paragraphs because the author needs information delivered.

2. Build the spoken thought chain.

   • Start with a claim.
   • Orient the listener: place, time, people, stakes.
   • Prove it with one concrete memory, object, mistake, or person.
   • Allow one controlled divergence.
   • Return with a steering phrase.
   • Land in the present scene.

3. Keep the listener active.

   • Add one interruption, silence, glance, flinch, object movement, or refusal to answer.
   • The listener does not need to speak much, but their presence must change the pressure.

4. Cut essay smoothness.

   • Break perfect logical order.
   • Keep meaningful corrections and turns.
   • Remove throat-clearing, filler, and podcast transcript clutter.
   • Preserve useful steering phrases only when they sound like the character.

5. End with a coda.

   • Return from the story-world to the current room, road, table, trial, fight, or silence.
   • The last sentence should change the present scene, not summarize the theme.

Long-Turn Shape

Use this default structure:

claim
orientation
specific example
controlled side path
return phrase
sharper claim
present-tense consequence

Good return phrases:

• "That is why..."
• "So when I say..."
• "What I mean is..."
• "I am telling you this because..."
• "But the point is..."
• "And that was before..."

Use these as structural tools, not canned language.

Scene Audit

Score a long dialogue passage out of 10:

• 2: clear reason this person speaks now
• 2: concrete memory or example
• 2: emotional pressure underneath
• 1: listener reaction
• 1: physical object, sound, or setting anchor
• 1: controlled divergence
• 1: clean return/coda

Under 6: likely exposition. 6-7: workable but may feel written. 8-10: can safely run multiple paragraphs.

Semantic Bus Integration

When an AgentBusResult, GeoSealPlan, or semantic decomposition is available, use it before manual scoring. Expected fields:

• semantic.atoms[].semanticId
• semantic.atoms[].count
• semantic.discourseProfile or top-level discourse_profile

Map the bus output into the rubric:

• long_turn or ANNOUNCE + EXPAND: baseline support for turn management.
• CARRY or warranted_claim: memory-backed credibility; raise the concrete example score if the scene actually contains a specific remembered event.
• HOLD or backchannel: listener co-construction; if absent from the semantic layer and absent from the prose, mark listener presence weak.
• REQUEST or floor_hold: permission token; useful when the speaker knows they are taking space.
• PIVOT: steering move; useful in moderation, confusing when dense without return phrases.
• PIVOT + BLOCK or governance_steer: treat as argument/redirection, not ordinary intimate dialogue.

Do not let atom detection override reading judgment. A scene can say "I remember" and still fail if the memory is generic. A scene can lack explicit HOLD text and still have listener pressure through silence, gesture, or object movement.

For the full scoring map, read references/semantic-bus-scoring.md.

Output Rules

When revising:

• Preserve the character's existing voice and power dynamics.
• Keep culturally and historically appropriate phrasing.
• Do not make every character sound like a podcast guest.
• Do not add modern filler unless the book's voice already supports it.
• Prefer one vivid remembered example over three abstract reasons.
• Keep the prose manuscript-ready, not transcript-raw.

When diagnosing:

• Name the missing component from the core equation.
• Point to the exact sentence where the speech loses pressure.
• Suggest one object anchor and one listener-pressure beat.

Reference

For transcript-derived patterns, examples, and anti-patterns, read references/transcript-patterns.md when doing a substantial dialogue rewrite or building a craft worksheet.

For tokenizer-assisted scoring from the agent-bus semantic layer, read references/semantic-bus-scoring.md.