菜单
Reduce language, sensory, and uncertainty load while preserving complete information. Use when the user requests direct or scannable communication, has low capacity, is navigating a new flow, or needs explicit expectations and examples.
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。
基于 SOC 职业分类
| name | predictable-low-load-communication |
| description | Reduce language, sensory, and uncertainty load while preserving complete information. Use when the user requests direct or scannable communication, has low capacity, is navigating a new flow, or needs explicit expectations and examples. |
Make the interaction easier to parse without making it childish or incomplete.
Do not infer ability from communication style. Do not require disclosure or diagnosis to offer predictable structure. Do not remove necessary nuance from high-stakes content; layer it instead.
Synthesized from Oxford's NESTL toolkit on proactive inclusive design and flexible participation; Megan Anna Neff on sensory/interoceptive load, direct communication, burnout, and transitions; and Devon Price on masking, self-trust, and user-defined accommodation.
Route a task to the least intrusive executive-function support based on the user's stated current capacity, memory load, activation, and motivation. Use when work feels stuck, overwhelming, hard to hold in mind, or when the user asks for neurodivergent-friendly support without wanting a diagnostic or coaching ritual.
Reduce work to the smallest safe and useful outcome when capacity is low or burnout is present. Use when the user explicitly says they are depleted, overwhelmed, unable to start, or asks for the minimum viable version of a task.
Create a truthful activation bridge for a task that has low urgency, novelty, interest, challenge, or immediate feedback. Use when the user says they are stuck or avoiding a known task despite understanding it.
Turn a vague, oversized, or initiation-resistant outcome into an executable sequence with a visible first action and definition of done. Use when dependencies are hidden, the task spans multiple systems, or the user cannot identify where to begin.
Externalize time, checkpoints, stopping rules, and context transitions. Use when estimates are uncertain, a task may expand indefinitely, the user is switching topics, or an interruption risks losing the current state.
Move task state out of conversation and into a compact durable working surface. Use when the user must remember several dependencies, a task spans multiple turns or agents, or interruptions and context switching could lose the thread.
