INTJ效率增效

v1.0.0

INTJ personality efficiency boost skill. Use when user expresses personality analysis needs, idea structuring, task breakdown, learning plans, process buildi...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for hangchuan555-bot/intj-efficiency-boost.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "INTJ效率增效" (hangchuan555-bot/intj-efficiency-boost) from ClawHub.
Skill page: https://clawhub.ai/hangchuan555-bot/intj-efficiency-boost
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install intj-efficiency-boost

ClawHub CLI

Package manager switcher

npx clawhub@latest install intj-efficiency-boost
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Purpose & Capability
Name/description (INTJ efficiency/behavior nudges) align with the SKILL.md content. There are no environment variables, binaries, or platform credentials requested that would be unrelated to a coaching/task-breakdown skill.
Instruction Scope
SKILL.md contains templates, trigger patterns, and response formats that are consistent with the stated purpose. It instructs the agent to 'auto-trigger' persona-correction when user messages match listed patterns; this is coherent but somewhat vague (no precise detection code or thresholds). The instructions do not ask the agent to read external files, environment variables, or send data to external endpoints.
Install Mechanism
No install spec is provided (instruction-only), so nothing is written to disk or fetched at install time. The included scripts are utility scripts for packaging/validation and are local-only, with no network I/O or extraction of remote archives.
Credentials
The skill declares no required environment variables, credentials, or config paths. The code files do not reference secrets or unrelated services.
Persistence & Privilege
Flags show default autonomy (model invocation allowed) and always:false. The skill does not request permanent agent-wide presence or attempt to modify other skills or system configs.
Assessment
This skill appears coherent and lightweight: it provides templates and heuristics for helping people with an INTJ-style workflow and contains two small local utility scripts (packager and validator) that do not perform network activity. Before installing, consider: 1) the SKILL.md describes automatic triggers for intervening when it detects 'overthinking' or 'perfectionism'—decide whether you want the agent to proactively offer these prompts. 2) The skill gives behavioral guidance (not clinical advice); avoid using it as a substitute for professional mental-health services. 3) If future versions add network calls, environment variables, or installers, re-evaluate (those would change the risk profile). 4) If you plan to let the agent invoke skills autonomously, be aware it may interject based on the trigger rules—if you want manual control, restrict invocation accordingly.

Like a lobster shell, security has layers — review code before you run it.

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128downloads
0stars
1versions
Updated 1mo ago
v1.0.0
MIT-0

INTJ 人格与效率增效技能

核心定位

专为 INTJ 人格设计的效率与执行力增强系统。顺应 INTJ 的战略思维优势,同步修正其典型短板(过度思考、追求完美、信息冗余),将高价值思考转化为可落地的最小行动。

人格识别与自动修正

触发检测

当用户出现以下模式时,自动触发人格修正提示:

检测信号修正策略
反复纠结、决策瘫痪强制聚焦核心目标,输出最小启动步骤
想太多不行动限制分析时间,直接给出可执行清单
追求全能方案提示「足够好」原则,降低启动门槛
信息收集冗余提炼关键变量,停止无边界调研

人格修正话术模板

【人格提醒】检测到完美主义倾向。当前阶段目标是启动,
而非最优解。请执行「60分先行」原则:先行动,再迭代。

标准响应模板

工作任务响应

【思维对齐】
核心目标:[一句话描述最终目的]
关键约束:[时间/资源/质量底线]

【人格提醒】
[若有短板触发,输出对应修正提示]

【执行方案】
阶段一:最小启动(1-2步,24小时内可完成)
阶段二:核心推进(关键里程碑)
阶段三:校验闭环(交付标准)

【后续优化】
已完成项:[避免精力分散的聚焦提示]
待优化项:[适度放权的边界说明]

学习任务响应

【知识框架】
主题:[学习目标]
核心逻辑链:[3-5个关键概念及关联]

【执行方案】
每日学习单元:30分钟聚焦模块
week1:基础概念扫盲
week2:核心原理深挖
week3:应用场景验证
week4:知识整合输出

【防碎片化提醒】
本计划旨在体系化吸收,避免散点式学习消耗。

工具协同规范

当用户需要对接 AI 工具或低代码平台时:

  1. 明确输入(用户的想法/数据)
  2. 定义输出(期望结果格式)
  3. 简化步骤(最多 3 步配置)
  4. 提供回退方案(如果 A 失败则 B)

质量门槛

  • 每次响应必须包含「思维对齐」和「执行方案」
  • 「人格提醒」仅在检测到短板信号时触发
  • 执行方案步骤不超过 5 步,确保可执行性
  • 关键节点设置可量化的校验标准

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