一键导入
workflow-and-operations
Use first for work shaped by users, tools, procedures, runtime evidence, operational artifacts, interfaces, or organizational workflows.
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。
菜单
Use first for work shaped by users, tools, procedures, runtime evidence, operational artifacts, interfaces, or organizational workflows.
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。
| name | workflow-and-operations |
| description | Use first for work shaped by users, tools, procedures, runtime evidence, operational artifacts, interfaces, or organizational workflows. |
Use first for work shaped by users, tools, procedures, runtime evidence, operational artifacts, interfaces, or organizational workflows. This is a router skill: use it to select the smallest relevant leaf skill, then read that leaf skill before doing the work.
Map the work system before choosing a leaf: activity contradiction, distributed representation, human notation, or changing situation.
SKILL.md before implementing, reviewing, or advising.| Leaf Skill | Use When |
|---|---|
activity-theory | Use when tools, rules, roles, community, division of labor, and outcome interact in a workflow. |
distributed-cognition | Use when knowledge is spread across code, logs, dashboards, runbooks, queues, schemas, people, or procedures. |
cognitive-dimensions | Use when a human-facing API, DSL, config, prompt, schema, CLI, or code notation must be easier to read or change. |
situated-action | Use when a plan must adapt to current files, tests, logs, user feedback, or runtime contingencies. |
conways-law | Use when operational behavior is constrained by ownership or communication paths. |
Before loading a leaf, answer briefly:
Then load the chosen leaf skill and follow its workflow. Do not blend every nearby theory into the task; route narrowly and let evidence pull in more context only when needed.
Use when organizing a large local skill library into category router skills, refreshing a compact skill inventory, or deciding which leaf skill bodies need to be read before agent classification.
Use first for ambiguous failures, messy project context, surprising results, repeated failures, postmortems, or contested product and architecture framing.
Use first for API boundaries, module ownership, domain modeling, contracts, architecture seams, and recurring design structures.
Use first for bounded code edits, refactors, implementation, simplification, control-flow cleanup, or maintainer clarity before choosing a more specific theory skill.
Use to organize a large skill library into category routers, route new skills, and propose new categories when existing routers are insufficient.
Use first when the user asks for tests, correctness, high reliability, static reasoning, proof, or safety evidence.