agentsclimarketplace

Pressure skill

Skill Someone-hates-Monday/pressure-skill/.agents/skills/pressure-skill

Cold pressure → warm, sendable replies (ZH/EN). Layered workplace comms—deflect, nudge, pin vague specs—like a super mouthpiece that won't get you fired. Multi-platform Agent Skill (Cursor / Claude Code / OpenClaw) + FastAPI; offline templates. ZH: 拒绝被压力、拒绝职场PUA、反催办、不接锅、软拒绝、立边界。 EN: pushback, boundaries, anti-gaslighting, say-no.From its SKILL.md

Install
npx -y skills add Someone-hates-Monday/pressure-skill --skill pressure-skill

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

  • 3 stars3 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 1 command, including `counterparty_cli.py feedback`.

SKILL.md

4.8 KB, ~1.6k tokens by cl100k_base, as published. Nobody here has run it

Language / 语言
Supports English and Chinese (same pattern as many open skills): infer from the user’s first substantive message and stay in that language for questions and drafts unless they switch explicitly.
支持中文与英文:根据用户第一条实质性消息判定语言,并全程使用同一语言;用户若明确切换语言则跟随。

pressure.skill(多平台 Agent Skill)

轻松一句冰冷压力 → 温暖回复;像一套立体攻防替你守住边界,再当你的超级嘴替——把「再催我就鼠掉」翻译成对方听得进、你发得出手的版本。

Agent 执行协议(最高优先级)

  1. 定位技能根目录 <skill-root>:即 SKILL.md 所在目录(无论装在仓库内 .cursor/skills/pressure-skill/.agents/skills/pressure-skill/,还是用户目录下的 ~/.cursor/skills/pressure-skill~/.claude/skills/pressure-skill~/.openclaw/workspace/skills/pressure-skill 等)。
  2. 用户挂上本 Skill 后的第一条行动:用当前产品支持的读文件能力读取
    <skill-root>/references/wizard-full-flow.md
    • Cursor:工具名一般为 Read
    • Claude Code / OpenClaw:使用文档中与 Read 等价的文件读取工具(名称以各版本为准)。
      可选:先读 <skill-root>/references/platform-wizard-notes.md,了解多平台路径与 Python cwd 约定。
  3. 若读取失败(工作区未含该路径、或沙箱无法读盘):请用户 将 pressure.skill 仓库克隆根打开为工作区、提供 wizard-full-flow.md 的磁盘路径,或 wizard-full-flow.md 全文粘贴进对话;在取得流程前 不要编造向导步骤。
  4. 读完主向导后严格按 wizard-full-flow.md 章节顺序与用户多轮对话;除「快速通道」外,禁止画像小结(§4)经用户确认前 采集场景 A/B/C/D,禁止用户声明目的(§5)前 输出最终可发送话术定稿。
  5. 长期对象(复诊):用户要继续跟踪同一位对方、追加材料或反馈时,再 Read <skill-root>/references/counterparty-long-term.md;经用户同意后用仓库根 scripts/counterparty_cli.py 读写本地 counterparties/(默认不进 Git)。复诊时仍须每轮采集 §5 目的§6~7 新场景
    5b. 实地反馈(发出去之后):用户带回真实对话与对方反应、或澄清了模糊话的真义时,再 Read <skill-root>/references/counterparty-feedback-loop.md,对照上轮预测写偏差与 learned_rules,执行 counterparty_cli.py feedback 校准画像,使下次意图推测与话术更准。
  6. 收尾顺序:遵循向导 §10——先问用户此刻最需要哪类产出并置顶作答,再写意图推测、多假设意图话术及对方可能反应;科研/模糊对齐场景可按向导加载 domain-artefact-cheatsheet.md深证据readiness.portrait_depth = deep)时按向导加载 evidence-based-reply-memo.md
  7. 语言:遵循 wizard-full-flow.md 中的 Language / 语言 规则(中英一致)。

本文件其余内容(快速备忘)

  • 隐私:不默认写入仓库;提醒用户脱敏。
  • 双路径:对话内可直接给建议(由当前产品绑定的模型执行);是否在仓库根跑 bundle_local.py 由 Agent 按向导 §8 自行判断(不向用户问工具名);若跑,在用户话术里只用自然语言交代「做了信息结构化检查」。若技能只装在用户目录,向导仍在该 <skill-root>/references/ 下;Python 脚本bundle_local.pycounterparty_cli.py 等)必须在 pressure.skill 仓库克隆根(含 scripts/)执行。详见 platform-wizard-notes.md 与向导 §8~§9、长期档案 counterparty-long-term.md
  • readiness:脚本/API 会输出信息是否够用;向导 §10 规定收尾顺序(先问产出优先级 → 再意图推测/话术/风险/追问)。
  • 工作目录:运行脚本时 cwd 须为含 scripts/仓库根,不是 <skill-root>
  • 多平台安装 / 排障:见 docs/skill-adapters.md
  • HTTPuvicorn app:app,接口见仓库 README.md

What ships with it: 6 files

33.5 KB alongside SKILL.md

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.