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Runtime operator

Skill fengsihao23-eng/shen-hua/skills/runtime-operator

Shen-Hua V2 runtime operator for minimizing the gap to model-level long-task agents. Use when Codex needs real task queueing, durable event logs, memory indexing/search, resume prompt generation, verification gates, automation handoff prompts, or external-sync outbox files for long-running project work.From its SKILL.md

Install
npx -y skills add fengsihao23-eng/shen-hua --skill runtime-operator

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
  • runs commandsInstructs the agent to run 2 commands, including `py -3 .\.agents\skills\persistent-memory\scripts\shenhua_runtime.py <command>` and 1 more.

SKILL.md

4.5 KB, 978 tokens by cl100k_base, as published. Nobody here has run it

Runtime Operator

Runtime Operator adds a real, project-local runtime layer under .agent/. It does not create unlimited autonomy, but it makes long-task operation resumable, inspectable, queue-driven, and ready for Codex automations or external sync.

Trigger Conditions

Use this skill when:

  • The user asks to reduce gaps around automatic continuation, tool scheduling, external state sync, long-term memory retrieval, or task queues.
  • A long-running project needs queue state, event logs, memory search, or resume prompts.
  • $project-commander needs a harder runtime substrate than Markdown-only memory.
  • Codex automations, GitHub/CI/task-board sync, or MCP integration must be prepared.

Do Not Trigger

Do not use this skill when:

  • The task is a simple one-shot answer.
  • The user forbids creating .agent/state/ or scripts.
  • A project already mandates a different runtime/state system.

Runtime Files

Maintain:

  • .agent/state/tasks.jsonl: durable local task queue.
  • .agent/state/events.jsonl: append-only runtime event log.
  • .agent/state/memory-index.json: searchable local memory index.
  • .agent/state/sync-outbox.jsonl: external sync actions waiting for a target.
  • .agent/state/sync-export.json: latest sync snapshot.
  • .agent/state/sync-targets.json: sync target policy and requirements.
  • .agent/state/automation-profile.json: automation readiness settings.
  • .agent/resume-prompt.md: prompt for future Codex sessions or automations.
  • .agent/automation-prompt.md: prompt body for a Codex heartbeat/cron automation.
  • .agent/RUNTIME.md: human-readable runtime operating guide.
  • .agent/GATES.md: required verification gates.

Script

Use:

py -3 .\.agents\skills\persistent-memory\scripts\shenhua_runtime.py <command>

Key commands:

  • init: create runtime state files and prompts.
  • task add <title>: add a task to the local queue.
  • task list: show queue status.
  • task update <id> --status done --note "..."
  • event --type <type> --message "..."
  • index: rebuild local memory index.
  • search <query>: search indexed project memory.
  • resume: regenerate .agent/resume-prompt.md.
  • automation-prompt: regenerate .agent/automation-prompt.md.
  • sync-export: export queue/events/handoff for external sync.
  • gate: run runtime self-checks, skill validation, memory index, and resume generation.

Five Gap Minimization

  1. Automatic persistent running:
    • Generate an automation prompt and runtime queue.
    • Use Codex heartbeat/cron automation only after a user chooses cadence.
  2. Forced tool scheduling:
    • Encode gates in AGENTS.md, skills, and gate.
    • Use CI or external checks for hard enforcement when available.
  3. External state sync:
    • Export a machine-readable outbox and sync snapshot.
    • Actual remote writes require the chosen target, credentials, and MCP/CLI availability.
  4. Long-term memory retrieval:
    • Rebuild and query .agent/state/memory-index.json.
    • Upgrade to SQLite/vector/MCP memory only when project scale needs it.
  5. Platform-level task queue:
    • Use .agent/state/tasks.jsonl as the local queue.
    • Mirror it to GitHub Issues/Projects, Linear, or other systems when configured.

Required .agent/ Updates

Always update:

  • .agent/LOG.md
  • .agent/TASKS.md
  • .agent/HANDOFF.md

When runtime state changes, also update:

  • .agent/state/events.jsonl
  • .agent/state/tasks.jsonl when queue tasks change
  • .agent/resume-prompt.md after major state changes

Other Skills

  • Use $project-commander for choosing the next task.
  • Use $persistent-memory for memory hygiene.
  • Use $verification-loop after script or state changes.
  • Use $self-reviewer and $handoff-writer before ending.

Subagents

Runtime Operator does not require subagents. Subagents can consume tasks from tasks.jsonl only when the current Codex runtime and user authorization permit delegation.

Verification

Run:

py -3 .\.agents\skills\persistent-memory\scripts\shenhua_runtime.py gate

The gate must pass before claiming the runtime layer is ready.

Output Format

RUNTIME STATUS
Queue:
Events:
Memory index:
Automation readiness:
External sync:
Gate result:
Remaining hard limits:

What ships with it: 1 file

255 B alongside SKILL.md

agents/

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