Results for “goal-management”

Automates ClickUp task, list, folder, and space management via the REST API v2, including time tracking, goals, custom fields, dependencies, and webhooks.

当需要将模糊的长期愿景转化为可执行的日常行动，以提升专注力和生活掌控感时

Optimize prompts via process goals (controllable behavioral instructions) rather than outcome goals (sparse end-result demands). Grounded in sports psychology meta-analysis showing process goals (d=1.36) vastly outperform outcome goals (d=0.09). Use when designing prompts, optimizing LLM steering, implementing CoT/decomposition patterns, or building automatic prompt optimization pipelines. Instantiates surrogate loss paradigm for discrete prompt space.

Agent skill for goal-planner - invoke with $agent-goal-planner

Frames tasks with explicit goals, success evidence, stop conditions, and boundaries before execution, then routes work to the appropriate workflow.

当设定新目标或检视现有目标时，确保目标能通过高效的行为系统自动达成

Clade goal-driven autonomous improvement loop (Blueprint architecture — deterministic pre/post phases + LLM supervisor/worker nodes, converges when goal met or max-iter hit). NOT the Claude Code built-in /loop (which polls a prompt on an interval like `/loop 5m /foo`) — if the user wants interval polling, route to the built-in.

Design a structured goal-setting protocol using SMART or implementation-intention frameworks for students. Use when launching units, projects, or developing student self-direction habits.

Create and execute durable repo-native multi-goal plans over Codex goal mode artifacts.

Manage teams using Andy Grove's principles: production thinking for knowledge work, output indicators, managerial leverage, effective meetings, clean decisions, OKRs, and task-relevant maturity.

Durable multi-goal workflow that persists plan/ledger artifacts under .omc/ultragoal and prints Claude /goal handoff text for the active session

Goal-Oriented Action Planning skill for world state and action costs.

当需要规划或评估一个高强度工作阶段（如冲刺项目、密集训练、创作期）时，调用此模型来设定合理的边界并确保可持续性

分析健康目标数据、识别目标模式、评估目标进度,并提供个性化目标管理建议。支持与营养、运动、睡眠等健康数据的关联分析。

当意识到当前行为模式可能导致不理想的未来，需要一种具体方法来激发改变动力时

Run metric-driven iterative optimization loops -- define a measurable goal, run parallel experiments, measure each against hard gates or LLM-as-judge scores, keep improvements, and converge on the best solution. Use when optimizing clustering quality, search relevance, build performance, prompt quality, or any measurable outcome that benefits from systematic experimentation.

当需要将个人知识或经验转化为商业机会，或希望建立有意义的个人发展路径时

当设定个人或工作目标，希望目标本身能带来持续的内在动力和满足感时

Agent skill for agent - invoke with $agent-agent

Provides a catalog of sales prompts covering pipeline management, prospecting, closing, proposals, objections, retention, and sales intelligence, with behavioral frameworks like SPIN, Challenger, and MEDDIC.

Help the user define a concrete, measurable goal before starting work, especially when they ask to use the goal tool, create a goal, set an objective, clarify success criteria, or turn a fuzzy intention into a quantitative outcome. Use this skill for goal creation and goal refinement only; it does not manage durable snapshots, decision logs, or long-running execution artifacts.

Designs and reviews feedback loops for AI agents to ensure goals are machine-decidable, loops are damped, and human judgment is preserved.

Drafts structured goal-loop prompts for long-running agent work with verifiable stop conditions, validation commands, and documentation requirements.

当需要在2-3个月内集中精力攻克一个重大、有挑战性的个人或职业目标时，使用此模型

当需要将生活或工作中的复杂情境转化为可管理、可执行的系统时，或当感到迷茫、缺乏动力、陷入社会比较时，调用此模型来重新构建认知和行动框架

当需要系统性地规划个人生活、职业发展或特定项目，以摆脱外部干扰、聚焦核心目标时

Create game plans with strategy and tactics. TRIGGERS - Use when user needs help with game-plan related tasks.

当个体感到生活缺乏方向、陷入重复性任务或被动接受外部目标，导致焦虑、无聊或停滞时，调用此模型以重新获得对生活的掌控感和成长动力

Audits fuzzy goals into checkable deliverables using Wittgenstein's philosophy of language, ensuring every word does work.

Defines Objectives and Key Results (OKRs) for product teams, including goal setting and progress tracking.

Tracks team OKRs with quarter banner, objective columns, key result progress bars, owner avatars, and status pills.

Benchmarks language model agents on the C2C multi-agent negotiation task, reporting win rate across starting positions.

当需要系统性地提升工作专注度和生产力，实现高质量成果时