菜单
Quantify cognitive cost of switching from current domain to target domain. Formula-driven (0.0-1.0). Returns recommendation. Use BEFORE committing to a domain switch.
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
Evaluate a decision against the user's stated principles + related past thinking. Loads principles from YAML, matches by keyword, surfaces semantically similar prior decisions.
Raw accounting of what's in the brain. Counts messages, embeddings, summaries, domains. Use when user asks "how much is in my brain" or "what's the size of the corpus."
Surface patterns in how the user thinks — cognitive pattern, problem-solving approach, emotional tone, content category. Optional domain scope. Use when user asks "when do I think best" or "what patterns show up in breakthroughs."
Full re-entry brief for a domain — recent summaries + accumulated open questions, decisions, insights, quotes. Longer and deeper than tunnel-state. Use after days/weeks away from a project.
Browse conversations by calendar date. Use when user asks "what was I working on last Thursday" or specifies a date.
Surface abandoned domains with unresolved breakthrough/significant open questions. Ranked by breakthrough count → question count → conversation count. Use when user feels important threads have been dropped.
| name | switching-cost |
| description | Quantify cognitive cost of switching from current domain to target domain. Formula-driven (0.0-1.0). Returns recommendation. Use BEFORE committing to a domain switch. |
| layer | L3 |
| reads | ["L2.summaries"] |
| writes | [] |
| citations | required |
| determinism | pure-function |
| allowed-tools | mcp__my-brain__switching_cost |
Flagship L3 skill. The only quantified attention-economics tool in the suite. Score is a deterministic function of current-domain open-question count, current-domain thinking stage, and concept overlap between domains.
Formula (copied from tools_prosthetic.py:683-686):
oq_cost = min(len(cur_open_questions) / 10.0, 1.0)
overlap_discount = min(len(shared_concepts) / max(len(cur_concepts), 1), 1.0)
stage_cost = {executing: 0.8, refining: 0.6, crystallizing: 0.4, exploring: 0.2}[cur_stage]
score = (oq_cost * 0.35) + (stage_cost * 0.35) - (overlap_discount * 0.3)
Score thresholds: <0.3 low / 0.3–0.6 moderate / >0.6 high.
current_domain: str
target_domain: str
## 🔀 Switching Cost: {current} → {target}
**Score**: 0.XX (✅ Low / ⚠️ Moderate / 🔴 High)
**Recommendation**: "Low cost — go for it" | "Moderate — consider noting open questions first" | "High — significant unfinished work"
### Breakdown
- oq_cost: X.XX (N open questions in current)
- stage_cost: X.XX (current stage: {stage})
- overlap_discount: X.XX ({shared} shared concepts out of {total})
### Questions you'd leave behind (top 5)
- {question} [conv_id · date]
### Shared concept bridges
{concept}, {concept}, ...
Without summaries: heuristic based on (question count, message volume, shared conversation titles). Returns a score of same range but with different weights. Output explicitly labels [heuristic fallback].