story-bank-builder

name	story-bank-builder
description	Use when mining, building, auditing, prioritizing, or updating a candidate's reusable interview stories from confirmed career experiences and project dossiers.

Story Bank Builder

REQUIRED BACKGROUND: Use career-state-protocol. Use project-deep-dive when a source project is too thin to support a story.

Goal

Build a compact portfolio of distinctive, evidence-backed stories that covers the candidate's real interview needs. Optimize for coverage and defensibility, not a fixed story count.

Inputs

Read the Career Profile, P### dossiers, confirmed and bounded C### claims, existing S### stories, target models when available, and prior interview use or feedback. Do not invent missing project detail in the story layer.

Workflow

1. Build a coverage matrix from the supplied T### model. Without a target, use broad career signals such as ownership, ambiguity, product or technical judgment, evaluation, collaboration, conflict, failure, customer or user insight, measurable impact, and learning.
2. Inventory candidate events that contain a real tension, decision, action, result, or changed operating method.
3. Score each event for relevance, evidence, ownership, distinctiveness, follow-up safety, and overlap with other stories.
4. Select the smallest portfolio that provides strong coverage and useful backups.
5. For thin but promising events, create a G### item and route to project-deep-dive before drafting.
6. Draft each story from linked claims, then test skeptical follow-ups.
7. Ask the user to confirm any new framing that changes emphasis, causality, or personal attribution.
8. Update story strength, follow-up risks, use count, and interview feedback after reuse.

Read references/coverage-and-selection.md before selecting stories and references/story-contract.md before writing them.

Story construction

Prefer a decision narrative over mechanical STAR labels in spoken output:

• context and stakes;
• exact responsibility;
• hard tension or decision;
• specific actions and mechanisms;
• evidence-supported result and attribution;
• learning that changed later behavior.

Prepare a 30-second version for retrieval, a 90-second version for normal answers, and deep-dive bullets for follow-up. All versions must use the same claims and boundaries.

Portfolio rules

• One strong story may answer several questions, but do not pretend reuse creates broader evidence.
• Track follow-up risks and use count to prevent repetitive interviews.
• Preserve honest adjacent bridges where a perfect story does not exist.
• A failure story needs a real miss and changed method, not a disguised success.
• A conflict story needs a real disagreement and resolution mechanism, not "we communicated."
• Target-specific mappings belong under T###; the base story remains target-neutral.