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story-engine-for-creator

这是专业剧情创作工具,基于确定性因果推理,核心功能含剧情逻辑校验、自动世界观生成、伏笔追踪、时空一致性检查、增量审计等,支持全流程创作验证。适用于长篇小说、游戏/影视剧本、IP衍生创作场景,采用自然语言输入,可输出剧情内容与可溯源防篡改的审计报告,默认纯本地运行,也可接入OpenAI兼容LLM增强能力。

nohn3043-arch
nohn3043-arch
热度 55.82
最近更新 2026-09-01 22:06:30
分类:创作依赖:代码执行 / 第三方 API / 内部调用大模型 / 读写文件应用场景:故事创作 / 校对润色

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add story-engine-for-creator
Metadata
name
story-engine-for-creator
slug
story-engine-for-creator
version
2.4.0
displayName
Creator Story Causal Engine
description
Deterministic plot architecture tool with built-in Second Perspective causal reasoning, logic vulnerability detection, automatic worldbuilding generation, narrative presentation layer audit, foreshadowing ledger, spacetime consistency check, hash-chained audit reports, and incremental diff-only audit.
required_commands
["python3"]
metadata
{"openclaw":{"required_binaries":["python3"],"emoji":"✍️","homepage":"https://github.com/nohn3043-arch/story-engine"}}

Creator Story Causal Engine

A professional plot creation tool based on deterministic causal reasoning, providing full-process logic verification and generation support for epic novels, game scripts, and film & television screenplays from outline to final draft.

Safety & Responsible Use

  • Fiction-writing aid only. This engine generates and audits fictional narrative text via an LLM. It is a writing/consistency tool, not a substitute for human editorial, legal, or safety review.
  • No sexualization of minors. Never use this engine to generate, refine, or optimize any content that sexualizes, eroticizes, or exploits anyone depicted as a minor or under 18.
  • You are responsible for output. All generated text is your responsibility. Ensure it complies with applicable laws, platform policies, and your own ethical standards before publishing or sharing.
  • License-bound. Personal non-commercial research use only; commercial use requires prior written authorization (see Licensing).

Trigger Scenarios

Automatically trigger when the user asks about the following content:

  • Novel/script/game plot architecture design
  • Worldbuilding generation and consistency verification
  • Plot logic vulnerability detection and repair
  • Character behavior consistency verification
  • Multi-thread narrative timeline alignment
  • Plot rhythm optimization and detail completion
  • Foreshadowing plant/pay-off reconciliation across chapters
  • Character spacetime conflict detection (long novels)

Core Capabilities

🧠 Second Perspective Causal Reasoning Kernel

  • Natural language outline automatically converted to auditable causal chains
  • Automatic plot logic vulnerability detection and repair suggestions
  • Full-link character behavior consistency verification
  • Automatic multi-thread narrative timeline alignment

🌍 Worldbuilding Generation and Verification

  • Rule-based automatic generation of fictional worldviews
  • Automatic setting conflict audit
  • Power system balance verification
  • Historical timeline self-consistency validation

✍️ Plot Generation and Rendering

  • Multilingual plot bridging and localization
  • Automatic scene detail completion
  • Dialogue style consistency maintenance
  • Automatic plot rhythm optimization

🎭 Narrative Presentation Layer Audit (Added in v2.1)

  • Chronicler observer / no omniscience: Three-gear narrative position verification (chronicler / limited / omniscient)
  • Line era anachronism detection: Automatically identifies modern word anachronisms, supports genre exemptions (urban/sci-fi/modern etc.)
  • Line cognitive boundary audit: Characters only speak information they know, no knowledge leakage
  • Automatic style recognition: Five-dimensional profile of genre/person/perspective/language/rhythm

🔒 Engine Isolation Protection (Added in v2.1)

  • Namespace isolation between Creator engine and Business engine, prevents crashes caused by mixing of data classes with the same name
  • Automatic detection and alerting of concurrent loading of multiple engines

🪝 Foreshadowing Ledger (Added in v2.3, P0)

  • Full-lifecycle tracking of planted (SET) vs. paid-off (PAY) foreshadowing via explicit keywords only — no guessing what counts as a foreshadow
  • Per-chapter scanning of causal nodes, outputs unrecovered_topics and all_closed
  • Feeds into audit_text gating: an unclosed foreshadow fails the audit

🧭 Spacetime Consistency Check (Added in v2.3, P1)

  • Three-way cross-check of character × time × place, catches "same character in two places at the same time"
  • Nodes missing any coordinate are skipped rather than assumed (no fabrication)

⛓️ Hash-Chained Audit Reports (Added in v2.3, P2)

  • Every audit report is linked into an engine-level SHA-256 hash chain (audit_hash / audit_prev_hash), making reports tamper-evident

⚡ Incremental Diff-Only Audit (Added in v2.3, P1)

  • audit_text(..., diff_only=True) audits only the passed-in text and skips global state recomputation — short path for real-time single-chapter/fragment gatekeeping

Usage

# Initialize engine
from scripts.story_engine import UltimateCausalNovelEngine, GlobalState
state = GlobalState()
engine = UltimateCausalNovelEngine("Your Novel Title", state)
# Load worldview setting
engine.conceive_world("Worldview outline text")
# Create chapter from natural language outline
chapter = engine.create_chapter_from_outline(1, "Chapter Title", "Natural language outline text")
# Perform logic audit
audit_result = engine.audit_text("Chapter content", "consistency")
print(audit_result)
# Generate chapter content
content = engine.render_chapter(chapter)
# v2.3: attach a real LLM (any OpenAI-compatible API, zero external deps)
from scripts.story_engine import OpenAIProvider
engine.set_llm_provider(OpenAIProvider(api_key="sk-...", model="gpt-4o",
                                       base_url="https://api.openai.com/v1"))
# v2.3: single-chapter real-time gatekeeping (skips global recomputation)
quick = engine.audit_text("Chapter content", diff_only=True)
# v2.3: foreshadow + spacetime + hash-chain fields
print(quick["foreshadow"]["ledger"]["unrecovered_topics"], quick["spacetime"],
      quick["audit_hash"])

audit_text return shape (v2.3): presentation / causal / logical / foreshadow / spacetime / audit_hash / audit_prev_hash / all_passed. all_passed is a five-way AND: presentation + causal + logical + foreshadow closed + spacetime. Stricter than v2.1.0 — text that passed before may now fail on unclosed foreshadowing or spacetime conflicts.

v2.0 Upgrade Capabilities (P0-P2)

🔗 Character-Narrative Interlink (P0)

Shares the same character_id with the AI Drawing Composition Template: Visual identity (drawing template) → behavioral identity (this engine) → emotional state (anthropomorphic engine), three sources one truth. Runs continuity checklist per chapter (immutable facts retained verbatim, temperament-consistent behavior, prop continuity, emotional arc, line style). See references/CharacterToNarrativeLink.md.

🌍 Worldbuilding Versioning (P0)

Worldviews are managed like code: Three layers (core_rules (immutable) / derived_rules (evolvable) / canon (narrative facts)) + semantic versioning (major = core rule change / minor = derived rule change / patch = canon addition). Generates diff per chapter, rejects rule violations or requires explicit version upgrade. See references/WorldviewVersioning.md.

🪟 Long Narrative Window Management (P1)

Three-level checkpoints (chapter gate / arc gate / volume gate) + rolling summary window + foreshadowing ledger (promise → fulfillment tracking, alert if >10 chapters unfulfilled). Chapter 20 will never betray Chapter 1. See references/LongNarrativeWindow.md. Status: as of v2.3 only the foreshadowing ledger part is implemented in the engine (ForeshadowLedger SET/PAY reconciliation); the three-level checkpoints, rolling summary window, and the >10-chapter threshold alert remain design-level documents with no code behind them.

🕵️ Logic Vulnerability Detection Integration (P2)

Vulnerability detection directly reuses the five-operator chain from the NOMOS Decision Hub for plot causal audit — the same deterministic engine, migrated from the decision domain to the narrative domain.

v2.1 Upgrade Highlights

  • Full engine core refactor: 840 lines → 2800+ lines, added Second Perspective causal engine, narrative presentation layer audit, style recognition, visual audit reports
  • Narrative presentation layer audit: Three detectors: chronicler observer/no omniscience, line era anachronism, line cognitive boundary
  • Engine isolation mechanism: Namespace isolation between Creator/Business engines, automatic alert on mixing
  • Constructor change: UltimateCausalNovelEngine(novel_title, initial_global_state, output_language="zh")
  • New APIs: recognize_style(), audit_text(), simulate_chapter(), repair_presentation_issues()

v2.3 Upgrade Highlights

  • Real LLM provider: OpenAIProvider — zero-dependency urllib client for any OpenAI-compatible API; error responses degrade to [LLM Error] … instead of raising
  • Foreshadowing ledger (P0): ForeshadowLedger.scan_nodes() / reconcile() — SET/PAY keyword reconciliation with an unrecovered_topics list. Note: the >10-chapter unfulfilled alert promised in v2.0 is still not implemented (no chapter-distance threshold in code); the ledger reports unclosed topics unconditionally
  • Spacetime consistency (P1): audit_spacetime_consistency(nodes); CausalNode gains time / place / foreshadow / foreshadow_topic
  • Hash-chained audit (P2): _hash_block() + engine._stamp_audit_hash(); engine keeps audit_chain_prefix (genesis "GENESIS")
  • Incremental audit (P1): audit_text(..., diff_only=True) + _build_audit_report()
  • Engine state: UltimateCausalNovelEngine gains foreshadow_ledger and audit_chain_prefix
  • Backward compatible: public API is additive only; the 3 removed lines were internal to audit_text
  • Version note: the local 2.2.0 tag was never published to ClawHub; this capability set ships directly as 2.3.0 (predecessor on the registry is 2.1.1)

Files

  • references/CharacterToNarrativeLink.md (P0 character-narrative interlink)
  • references/WorldviewVersioning.md (P0 worldview versioning)
  • references/LongNarrativeWindow.md (P1 long narrative window management)
  • scripts/ (Engine core)

Typical Scenarios

  1. Epic novel creation: Worldview verification, plot deduction, logic audit for million-word level long novels
  2. Game script development: Consistency verification of multi-branch plots, outcome rationality deduction
  3. Film & television script creation: Plot rhythm optimization, character behavior logic verification
  4. IP derivative creation: Ensure consistency of derivative content with original worldview and character settings

Technical Features

  • No probabilistic black boxes: All generation and verification results support full causal traceability
  • Audit chain on-chain: All modifications and decisions are logged and auditable; since v2.3 each audit report is sealed into a SHA-256 hash chain (tamper-evident)
  • Pure local operation: No internet connection required, all data stored locally only. v2.3 note: network is used only if you explicitly attach OpenAIProvider; the default path (MockLLM / no provider) stays fully offline
  • Zero learning cost: Supports pure natural language input, no professional markup language required

Licensing

Only allowed for personal non-commercial research use. Commercial use requires written authorization.