Results for “goal-framing”

Guide teams through MITRE's Problem Framing Canvas to clarify problem statements before jumping to solutions.

当需要在写作中与读者建立情感连接、放大问题严重性，并引出后续解决方案时

Shape a fuzzy intention into a concrete, measurable objective with explicit evidence, scope bounds, and a stop condition before starting work.

Find and own a defensible market position by testing positioning claims, running crawl-walk-run rollouts, and auditing competitor messaging.

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

Nocaps: Novel Object Captioning at Scale

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.

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

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

Draft or revise a scene on a goal-conflict-disaster spine with sensory grounding.

Apag Advantage Framing

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.

Implements gamification elements in educational content with points, badges, leaderboards, and quests

Turn raw ideas into one clear pre-planning concept artifact by choosing the right framing mode: problem framing, audience and value framing, concept shaping, game concept framing, or story packaging. Use when the user needs the next artifact before PRDs, sprint plans, launch execution, or game-production routing.

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

当需要设定人生方向或进行重大行为改变时

Measure declared project fitness goals without recommending or applying work. Triggers: "measure goals", "check project fitness".

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.

GLIP: Grounded Language-Image Pre-training

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

当需要为个人或小型企业建立在线品牌身份，以吸引目标受众并建立共享认知框架时

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

Route goalflow (wanmol/goal-flow) work — a LangGraph framework that combines workflow graphs with agent loops — into exactly one mode: fit check, transpiling a Dify DSL export into runnable LangGraph Python, authoring workflow nodes and edges, building an `agent_kit` loop with middleware and a harness, wiring the serving layer (data adapters, SSE streaming, HITL, Redis/MySQL, API-key registration), or running the pre-publish security gate. Use when the user wants Dify's visual design without Dify's runtime, a graph node that hosts an agent loop, an OpenAI-compatible wire protocol over their own workflows, or prompt-injected `SKILL.md` capabilities. Triggers on: goalflow, goal-flow, dify to langgraph, dify transpiler, dify DSL export, BaseWorkflow, agent_kit, AgentBaseNode, DataAdapter, chunk processor, HITL interrupt, dify2langgraph. Route plain graph-API questions to `langgraph-fundamentals` and `langgraph-workflow`.

Diagnose the PM-to-Director transition using altitude (scope) and horizon (time) axes, identify transition zones, and apply the Cascading Context Map when organizational direction is vague.

Trace and interpret the Pareto frontier across competing objectives using repeated single-objective cuOpt solves (weighted-sum and ε-constraint).

Trains and fine-tunes vision models for object detection, image classification, and segmentation using Hugging Face Transformers on cloud GPUs, with automatic dataset validation and Hub persistence.

Coordinates a goal lifecycle: define, decompose, activate, track, and execute goals using a set of system skills that write markdown files.

Find adjacent vendors and subs (not top market primes) who fill a capability gap against a displacement target using USASpending flows and SAM entity signals. Use when user defines a teaming gap and wants vault-ready partner shortlist with citations.

Multimodal Few-Shot Learning with Frozen Language Models

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

Diagnose frame-rate bottlenecks (CPU vs GPU bound FIRST), control Unreal Insights traces, sample live frame times, and annotate performance captures. Use when FPS is low/bad, the game is slow, or you need to find what is limiting the frame rate.

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.

Clickjacking playbook. Use when testing whether target pages can be framed, whether X-Frame-Options or CSP frame-ancestors are properly configured, and whether UI redress attacks can trigger sensitive actions.

Produce low/mid-fidelity wireframe specifications and annotations for handoff. Use when: (1) early concepting, (2) comparing layout options, (3) PM/engineering alignment. NOT for: high-fidelity branding work.