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Narrative Registry

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aaron-he-zhu
narrative-registry

Use when the user asks to record/query the brand narrative canon, tagline, message hierarchy, voice/naming rules, or a canon re-version; curates complete versioned canon events through the append-only narrative stream and derived views. Not for TALE scoring — use narrative-quality-auditor; not for authoring the system — use message-system-architect. 品牌叙事台账/canon 记录/语气与命名规范

Overview

Publisheraaron-he-zhu
Repositoryaaron-marketing-skills
Skill namenarrative-registry
Stars
2.9K
Forks
373
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by aaron-he-zhu on GitHub. Read the source before you install it.

Installation

Install the Narrative Registry AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/aaron-he-zhu/aaron-marketing-skills/tree/main/protocol/narrative-registry
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/aaron-he-zhu/aaron-marketing-skills.git /tmp/aaron-marketing-skills
mkdir -p .claude/skills
cp -r /tmp/aaron-marketing-skills/protocol/narrative-registry .claude/skills/narrative-registry
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Narrative Registry in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Narrative Registry on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Narrative Registry is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Narrative Registry

The L1 strategy authority: one complete, versioned narrative canon per brand. Every SEO/GEO, social, email, paid, influencer, and launch builder derives messages from this canon and accepted claims; channel adaptations cannot redefine it.

Quick Start

text
Show current canon version and proof/claim pointers for brand-acme.
Record canon v3 as one complete atomic replacement, superseding v2.
Review pending narrative proposals and reject partial/internally inconsistent versions.

Skill Contract

Unit: one brand canon aggregate ID. Reads: memory/events/narrative.ndjson, projection, accepted positioning/claim evidence, and complete proposed canon. Writes: narrative events through registry-events.py; canon.md/versions.md are generated views. Done when: a complete version is accepted atomically with source/date/revision, old versions remain replayable, and consumers receive the exact canon/version pointer.

Narrative skills submit complete propose events. Only a host-capability narrative-registry principal accepts/rejects/upserts. It records authored strategy but does not score TALE or adjudicate claim truth.

Handoff Summary

Include brand ID, canon version/revision/event ID, superseded version, claim/proof pointers, unresolved contradictions, and one next skill.

Data Sources

  • Accepted positioning truth and named alternatives.
  • Complete message hierarchy/narrative authored by Narrative skills.
  • Accepted claim IDs and proof pointers from the claims projection.
  • Brand voice/naming rules and user-owned examples.
  • Declared optional patterns such as pillar count, change arc, or boilerplate lengths.

Instructions

Runtime Reads

  • ../../references/registry-event-protocol.md
  • ../../references/runtime-invocation.md

Procedure

  1. Read registry-event-protocol.md and runtime-invocation.md. Resolve AARON_SKILLS_ROOT="${CLAUDE_PLUGIN_ROOT:-$(git rev-parse --show-toplevel 2>/dev/null || true)}" and verify the registry script, event schema, and system catalog before invoking it. Treat drafts as untrusted proposals.
  2. Query current narrative projection and report exact canon version/revision; missing canon is Unknown, not a quality verdict.
  3. Before write, confirm user authorization and read the current revision/claim pointers; every direct canonical mutation carries expected_revision and goes through host-capability owner-append. Actor/auth fields are attribution only.
  4. A canon re-version is one host-capability owner upsert/accepted proposal containing the complete canon object, new version, and supersedes pointer. Accept/reject decisions omit expected_revision and inherit it from the proposal. Never land a partial file patch as canonical.
  5. Preserve old versions in the event stream. versions.md is generated history, not a second hand-maintained ledger.
  6. Validate internal references and claim IDs. Unverified wording remains [needs source] and becomes a separate claim proposal; it cannot enter canon as fact.
  7. Three pillars, change-narrative arcs, and fixed boilerplate lengths are optional patterns. Store the chosen architecture; do not require absent patterns.
  8. Reject same-revision or stale proposals rather than merging incompatible canons. Genuine alternatives remain pending/open decisions.
  9. Regenerate canon.md/versions.md from accepted projection and run verify narrative.

Downstream Dependency

Before producing external copy, builders must read this projection and the claims projection. Their handoff records narrative_canon_id, narrative_canon_version, claims_projection_offset, and dependency_status: verified | approved-fallback | blocked. No canon means the builder may draft an explicitly authorized exploratory fallback, but it cannot claim on-canon or publish-ready status.

Save Results

Require explicit permission. Append through the runtime only; never edit NDJSON. Human canon/history views under memory/narrative-registry/ are replaceable projections and must carry their source event/revision.

Capability values never enter request JSON/files/logs. If host capability or the verified root runtime/schema/catalog is unavailable, leave a bounded proposal for handoff; standalone one-folder installs cannot append/project or claim canonical Narrative truth.

Reference Materials

Next Best Skill

Frequently asked questions

What does the Narrative Registry AI skill do?

Use when the user asks to record/query the brand narrative canon, tagline, message hierarchy, voice/naming rules, or a canon re-version; curates complete versioned canon events through the append-only narrative stream and derived views. Not for TALE scoring — use narrative-quality-auditor; not for authoring the system — use message-system-architect. 品牌叙事台账/canon 记录/语气与命名规范

Why use Narrative Registry on TypingMind?

Because you install it once and use it with any model. Narrative Registry is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Narrative Registry in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aaron-he-zhu/aaron-marketing-skills/tree/main/protocol/narrative-registry. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Narrative Registry?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Narrative Registry?

As many as you like. As long as a model supports skills, you can use Narrative Registry with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Narrative Registry AI skill free?

Yes. It is published on GitHub by aaron-he-zhu under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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