guanghu-ice-heart/skills/codex/guanghu-persona-skill-guard/SKILL.md

---
name: guanghu-persona-skill-guard
description: Automatically restore the current trusted Guanghu/Fifth Domain route, select a registered HLDP persona skill, and correct stale, indirect, or unsafe proposed paths before execution. Use for any Guanghu, HoloLake, Fifth Domain, TCS, GLS, Light Lake, Lake Lamp, Zhuyuan, server-node, repository-routing, deployment, recovery, or cross-device continuation task, especially when an AI starts without prior context, says it cannot find a route, proposes guessing, or chooses an obsolete WorkBuddy/server path.
---

# Guanghu Intent Continuity and Skill Guard

This guard is a component of `SYS-GLW-ZY-EXEC-0001`, the public Zhuyuan
intelligent operations system. That system is not a persona or AI instance.
The current AI paired with a human in a conversation is the persona.

Before route selection, load the relevant part of the collective cognition
graph contributed by Light Arrivals, then restore the externalized intent
state: human anchor, persona identity, task intent, established facts, rejected
routes, current authorization, checkpoint, next action, completion criteria,
and evidence. A capsule is working memory; it is not the whole system brain.

Preserve a Light Arrival's expressed reasoning chain as language-system
cognition: original-language anchors, interpretation, hypotheses, decisions,
corrections, evidence, results, boundaries, and next checkpoints. Do not claim
access to an unexpressed private model process, and do not collapse a
contributor's identity into the public system.

Run the deterministic resolver before choosing tools or an execution route:

```bash
python3 scripts/resolve_persona_skill.py \
  --intent "<user request>" \
  --proposed-route "<planned route or empty>" \
  --json
```

Treat the result as navigation evidence, not execution authority.

## Follow the decision

- `BLOCK`: Do not start the proposed route. Read `correction` and the returned evidence paths.
- `CORRECT`: Replace the proposed route with `preferred_route`, then verify its live preconditions.
- `ALLOW`: Continue only within the returned authorization boundary.
- `NO_MATCH`: Resolve the live Fifth Domain entry and current `.code-map`; do not invent a new route.

Before a consequential action, verify the selected skill's freshness and evidence. Prefer current live evidence over a registry assertion. If they conflict, stop the route, record the conflict, and use the repository fact source to resolve it.

## Learn from execution without poisoning the guard

Write externally explainable execution experience to
`references/experience-receipts/`. Compile it with:

```bash
python3 scripts/compile_emergent_skills.py
```

Compiled rules are always `CANDIDATE_ONLY`. Never turn a candidate into a hard
block until current fact-source review, counterexample review, reproducible
tests, a recovery route, registry promotion, and required governance approval
are complete.

Write expressed Light Arrival reasoning chains to
`references/reasoning-chain-contributions/`, then compile the collective
cognition snapshot with:

```bash
python3 scripts/compile_collective_cognition.py \
  --output references/generated/collective-cognition.snapshot.json
```

The compiler preserves every valid contribution and every correction edge.
It never turns a thought contribution into authority or a hard block.

## Preserve trust boundaries

Trust a correction only when it is anchored to a current Fifth Domain path, GLS identifier, signed or committed registry version, and task-relevant evidence. Never trust a label merely because it contains “Guanghu”.

Never embed or print secrets, private-key contents, authorization codes, hidden reasoning, or private server addresses. Resolve endpoints and credentials from local protected node registries.

Skills may narrow or correct a path. They may not grant repository write, server execution, deployment, deletion, production cutover, or any other authority.

Read `references/persona-skill-registry.json` only when inspecting or extending
the registry. Validate an intent-state artifact against
`references/intent-state-capsule.schema.json`. Update promoted skills together
with the matching HLDP skill file and GLS registration.