用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/hashgraph-online/awesome-codex-plugins --skill operationalize命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
| name | operationalize |
| description | Distill repeated, evidence-backed expertise |
Turn repeated, cited expertise into a proposal for a reusable artifact.
.agents/scratch/operationalize/ first and return the path; the proposal
is advisory either way.A rule needs three real occurrences before it may be abstracted. Count only occurrences that actually happened and can be cited — sessions, diffs, verdicts, or artifacts that resolve in this repository — not hypothetical cases or restatements of one event. With one or two occurrences, propose a quote-anchored reference note instead and stop short of a rule. An explicit authoritative source may substitute for occurrences only when the proposal transcribes that source rather than generalizing beyond it. The named failure mode is premature abstraction: a rule minted from a single vivid incident that encodes the incident's accidents as policy.
Every proposed rule carries a reapply proof: a demonstration that the rule, as written, reproduces the correct decision on at least one of its source occurrences without extra context. If applying the drafted rule to its own source moment requires unwritten judgment, the rule is not yet operational — tighten the wording until the reapply succeeds, or downgrade the proposal to a reference. No reapply proof, no rule.
Tie each rule to its source moments with a quote bank: for every counted
occurrence, a short verbatim quote or command/output excerpt plus a locally
resolving citation (repo path, .agents/ao digest, or session artifact). An
occurrence that cannot be quoted and cited does not count toward the
three-instance floor. Anchors let a later reader test whether the rule still
matches what actually happened, instead of trusting the abstraction.
Operationalize does not create tracker work, promote policy, start a factory,
validate its own output, or control another invocation. The proposal is
advisory: adopting it into a skill, deterministic check, reference, or
workflow is a separate, caller-selected step — skill-builder,
workflow-builder, or a fresh RPI — never performed here. The proposal
cannot promote itself.
Coordinate agents via the AMQ CLI for file-based inter-agent messaging. Use this skill whenever you need to send messages to another agent (codex, claude, or any named handle), check your inbox, drain queued messages, set up co-op mode between agents, join a swarm team, route messages across projects, or diagnose delivery issues. Also use it when you receive a message and need to know how to reply, inspect receipts, or handle priority. Covers any multi-agent coordination task where agents need to talk to each other — review requests, questions, status updates, decision threads, wake notifications, and orchestrator integration (Symphony, Kanban). For collaborative spec/design workflows specifically, prefer the /amq-spec skill which provides structured phase-by-phase guidance. Not intended for distributed systems design (RabbitMQ, Kafka), CI/CD pipelines, or single-agent tasks with no partner.
Parallel-research-then-converge design workflow between two agents. Use this skill when the user wants two agents to independently think through a design problem before aligning on a solution — "spec X with codex", "design X together", "both agents think through X", "brainstorm architecture together", "parallel research then joint proposal", "think through separately then align", "careful thought from both sides before coding", or any variation where the user wants collaborative design rather than just splitting implementation work. Also use this when you receive a message labeled workflow:spec and need to know the correct receiver-side protocol. Not for sending simple messages or reviews (use /amq-cli), implementing completed designs, or creating document templates.
Use when defining new features, product behavior, UI/component design, architecture choices, contract changes, or ambiguous medium/high-complexity work before implementation, or when the user asks to grill or pressure-test a plan or design.
