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
npx -y skills add fengsihao23-eng/shen-hua --skill runtime-operatorAssembled 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-commanderneeds 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
- Automatic persistent running:
- Generate an automation prompt and runtime queue.
- Use Codex heartbeat/cron automation only after a user chooses cadence.
- Forced tool scheduling:
- Encode gates in
AGENTS.md, skills, andgate. - Use CI or external checks for hard enforcement when available.
- Encode gates in
- External state sync:
- Export a machine-readable outbox and sync snapshot.
- Actual remote writes require the chosen target, credentials, and MCP/CLI availability.
- Long-term memory retrieval:
- Rebuild and query
.agent/state/memory-index.json. - Upgrade to SQLite/vector/MCP memory only when project scale needs it.
- Rebuild and query
- Platform-level task queue:
- Use
.agent/state/tasks.jsonlas the local queue. - Mirror it to GitHub Issues/Projects, Linear, or other systems when configured.
- Use
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.jsonlwhen queue tasks change.agent/resume-prompt.mdafter major state changes
Other Skills
- Use
$project-commanderfor choosing the next task. - Use
$persistent-memoryfor memory hygiene. - Use
$verification-loopafter script or state changes. - Use
$self-reviewerand$handoff-writerbefore 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/
- openai.yaml255 B