Skill

Build reusable case libraries from cross-frame materials

Sub-skill that converts CrossFrame case materials into anonymized, reusable casebook entries with mechanism and responsibility chains.


80
Spark score
out of 100
Updated last month
Version 5.1.7-20260624

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Why it matters

Transform complex cross-domain materials-chat logs, project retrospectives, organizational records, public disputes-into anonymized, structured case entries that extract mechanisms, responsibility chains, and reusable concepts for future analysis while maintaining source integrity and privacy boundaries.

Outcomes

What it gets done

01

Redact personal identifiers and sensitive details from source materials while preserving interaction structure and observable behaviors

02

Extract mechanism chains and responsibility chains from narrative materials to identify structural patterns beyond surface storytelling

03

Map scale windows and reverse conditions to clarify judgment boundaries and prevent inappropriate scale transfers

04

Generate indexed case entries with fact boundaries, source ledgers, reusable concepts, and follow-up observation signals

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-crossframe-casebook | bash

Overview

CrossFrame Casebook

A CrossFrame sub-skill that converts routed case materials into anonymized, structurally-grounded casebook entries - mechanism chain, responsibility chain, reverse conditions, reusable concepts - rather than narrative or advice. Use it only via crossframe-suite routing for explicit casebook/mechanism-extraction tasks, never as an independent or default reasoning layer.

What it does

CrossFrame Casebook is a parallel case-library skill to CrossFrame, not a replacement for it - it does not trigger independently, and is only loaded when crossframe-suite routes explicit CrossFrame materials into reusable entries. Its job is narrowly scoped: turn source material into reusable case entries by first protecting facts, sources, and privacy boundaries, then extracting the scale window, mechanism chain, responsibility chain, reverse conditions, reusable concepts, and follow-up observations. The skill body is Chinese-canonical - English is used only for skill IDs, filenames, field names, or external summaries, and Chinese terms govern wherever the two conflict.

When to use - and when NOT to

Use it only when crossframe-suite routes explicit CrossFrame materials into casebook entries, anonymized case records, mechanism extraction, or retrieval indexes - the goal is future reuse, not immediate advice. Do not use it independently unless the user explicitly names this sibling skill; if the goal shifts to writing up, teaching, debating, or making a public/organizational judgment from an accumulated case, the suite's main dispatcher must be consulted first, since this skill only handles casebook entry structure.

Inputs and outputs

A mandatory sequence: read the base CrossFrame skill for the gates and expression boundaries that apply, consult the routing map to select the right protocol/concept cards/judgment tier for the material's topic, and - if the material triggers high-responsibility, public-institution, intimate-relationship, long-term-evolution, framework-governance, AI-reality-verification, weak-signal/opaque, no-exit, instrumentalization, or metaphor/source-transparency conditions - pull in the continuity bundles and run a source-continuity worksheet (skipping this means the output must be downgraded). It reuses the base skill's read-state-capsule template rather than reinventing source routing, applies material-boundary protocols to separate source/fact/speculation/privacy/publishability layers, and a casebook-build protocol to decide whether the task is a new case, cleaning an old one, batch indexing, comparing cases, or converting a retrospective into a case. A field guide ensures every case records at least nine elements: case summary, factual boundary, material sources, scale window, mechanism chain, responsibility chain, reverse conditions, reusable concepts, and follow-up observations - with privacy/redaction rules applied to names, organizations, locations, timestamps, raw chat text, screenshots, links, and other identifying detail. A mechanism-extraction protocol specifically prevents the output from being just narrative or a pile of concepts without an actual causal chain.

Integrations

Hard rules: never copy the full CrossFrame skill text (only relative-path reads of the canonical skill and routing map); never turn raw chat text or personal information directly into a case asset unless the user explicitly requests it within a confirmed publishable scope; never write speculation, motive inference, or secondhand opinion as fact; every case must extract at least one mechanism chain and one responsibility chain, not just tell a story; never let CrossFrame terminology substitute for case facts - concepts must serve reuse, not decorate output; never let a casebook become a character trial, organizational conviction, public verdict, or compliance endorsement; and when evidence is insufficient but risk is urgent, only low-risk, revocable, observable follow-up items may be output.

Who it's for

Users working within the CrossFrame suite who need source material distilled into a reusable, privacy-safe, structurally-grounded case library entry rather than a one-off narrative or advice response.

FAQ

Common questions

Discussion

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