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

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description

guanghu-persona-skill-guard

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, restore the externalized intent state: human anchor, persona identity, task intent, established facts, rejected routes, current authorization, checkpoint, next action, completion criteria, and evidence. Do not reconstruct or store hidden chain-of-thought.

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

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:

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.

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.