| 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 |
switching-cost — L3 attention-switch scorer
Framework context
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.
When to invoke
- User says "should I switch to X" / "is it worth pausing Y for Z"
- Auto-invoke before tunnel-state(target) when user was just in a different tunnel-state
- Pair with context-recovery when score is high but switch is necessary
Input
current_domain: str
target_domain: str
Output contract
## 🔀 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}, ...
Does NOT do
- Recommend which domain is "better"
- Factor in deadlines or external constraints (user does that)
- Cache the score — always recomputed from latest summaries
- Extrapolate to 3+ domains (pairwise only)
Fallback
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].
Verification checklist
