swap-analyzer

name	swap-analyzer
description	Analyze swap compatibility and safety. Use when evaluating proposed schedule swaps to ensure they maintain ACGME compliance and operational coverage.
model_tier	opus
parallel_hints	{"can_parallel_with":["code-review","test-writer"],"must_serialize_with":["acgme-compliance","safe-schedule-generation"],"preferred_batch_size":2}
context_hints	{"max_file_context":20,"compression_level":1,"requires_git_context":false,"requires_db_context":true}
escalation_triggers	[{"pattern":"incompatible|infeasible","reason":"Incompatible swaps require human decision"},{"keyword":["violation","coverage gap"],"reason":"Swaps creating violations need escalation"}]

Swap Analyzer Skill

Comprehensive analysis of schedule swap compatibility and impact assessment.

When This Skill Activates

• Faculty requests schedule swap
• Evaluating swap feasibility
• Checking swap impact before execution
• Investigating swap-related issues
• Pre-validating swap proposals

Swap Analysis Framework

Phase 1: Swap Type Classification

Identify Swap Pattern:

Swap types:
1. One-to-one swap
   - Resident A's rotation swapped with Resident B
   - Most common, usually feasible

2. Absorb swap
   - Resident A gives shift to Resident B
   - Requires accepting extra load

3. Multi-party swap
   - Chain involving 3+ residents
   - Complex validation needed

4. Faculty/coverage swap
   - Change faculty assignments
   - Affects supervision ratios

Phase 2: Feasibility Analysis

Step 2.1: Rotation Compatibility

For proposed swap:
1. Is rotation type switchable?
   - Can A work B's rotation?
   - Required credentials?
   - Skill match?

2. Are residents trained for rotations?
   - Check rotation requirements
   - Verify prerequisite training
   - Confirm no conflicts

Step 2.2: ACGME Compliance Check

For each resident involved:
1. 80-hour rule impact
   - Would swap cause violation?
   - Check weeks affected
   - Estimate new hours

2. 1-in-7 rule impact
   - Would swap violate days off rule?
   - Check consecutive duty days after swap

3. Supervision impact
   - Ratio still compliant?
   - Adequate supervision in each rotation?

Step 2.3: Coverage Impact

1. Original coverage
   - Who covers each shift?
   - Is there redundancy?

2. After swap coverage
   - Any coverage gaps created?
   - Minimum staffing maintained?
   - Critical rotations still covered?

3. Backup availability
   - Can gaps be filled?
   - Backup cost/impact?

Phase 3: Impact Assessment

Step 3.1: Quantify Changes

For each resident:
1. Hours change
   - Current: X hours
   - After swap: Y hours
   - Difference: ±Z hours

2. Rotation change
   - Current: [Rotation A]
   - After swap: [Rotation B]
   - Type change: Clinical/Admin/Procedure/etc

3. Work load impact
   - Fair? Too much? Too light?

Step 3.2: Risk Assessment

Risk factors:
1. Compliance risk: [LOW/MEDIUM/HIGH]
2. Coverage risk: [LOW/MEDIUM/HIGH]
3. Fairness risk: [LOW/MEDIUM/HIGH]
4. Overall risk: [SAFE / PROCEED WITH CAUTION / UNSAFE]

Phase 4: Recommendation

Step 4.1: Generate Recommendation

Possible outcomes:
1. APPROVED
   - Swap is safe and compliant
   - No issues identified

2. APPROVED WITH CONDITIONS
   - Swap approved if conditions met
   - List specific conditions

3. BLOCKED
   - Swap creates violations
   - Explain specific issues

4. NEEDS MODIFICATION
   - Swap feasible with adjustments
   - Suggest alternative dates/residents

Swap Analysis Report

## Swap Feasibility Report

**Swap Type:** [TYPE]
**Requested By:** [NAME]
**Date Requested:** [DATE]

### Proposed Swap
- Resident A: [Current] → [Proposed]
- Resident B: [Current] → [Proposed]
- Dates: [START] to [END]

### Feasibility Analysis

#### Rotation Compatibility
- [x] Rotation A can be done by Resident B
- [x] Resident B has required credentials
- [x] No prerequisite issues

#### ACGME Compliance
- 80-hour impact: [A: ±Z hours, B: ±Z hours]
- 1-in-7 impact: [Compliant/Violation detail]
- Supervision impact: [Compliant/Violation detail]

#### Coverage Impact
- Gaps created: [None/List gaps]
- Coverage maintained: [YES/NO]
- Backup available: [YES/NO]

### Recommendation

**APPROVED** / **BLOCKED** / **CONDITIONAL**

Reasoning: [Explanation]

### Conditions (if applicable)
1. [Condition 1]
2. [Condition 2]

### Alternative Suggestions
1. [Alternative 1]
2. [Alternative 2]

Common Swap Scenarios

Scenario 1: One-to-One Procedural Swap

Request: Swap inpatient block for clinic block Analysis:

• Rotation compatibility: Check
• Skill match: Check
• Hours impact: Usually minor
• Coverage: Usually safe Typical outcome: APPROVED

Scenario 2: Holiday Coverage Request

Request: Swap holiday duties Analysis:

• Often stacks hours dangerously
• Check 4-week rolling average impact
• Verify 80-hour rule not violated Typical outcome: CONDITIONAL or BLOCKED

Scenario 3: Night Float Swap

Request: Swap night float blocks Analysis:

• Coverage critical
• 6-night limit impact
• Supervision in night float important Typical outcome: Varies widely

Scenario 4: Last-Minute Absence Coverage

Request: Absorb shift due to emergency Analysis:

• Fair distribution check
• Fatigue/safety concern
• Must not exceed 80-hour rule Typical outcome: Usually BLOCKED unless fairness maintained

Integration with swap-execution

After analysis:

1. If APPROVED: Pass to swap-execution for implementation
2. If BLOCKED: Deny swap with explanation
3. If CONDITIONAL: Send conditions to requester
4. If NEEDS MODIFICATION: Propose alternatives

Quick Analysis Commands

# Analyze proposed swap
python -m app.swaps.analyzer --resident1=A --resident2=B --dates=START-END

# Check impact on 80-hour rule
python -m app.swaps.analyzer --resident1=A --rule=80-hour --dates=START-END

# Simulate swap to see hours impact
python -m app.swaps.analyzer --resident1=A --simulate --dates=START-END

Validation Checklist

• Swap type identified correctly
• Rotation compatibility verified
• ACGME rules checked
• Coverage impact assessed
• Risk level determined
• Recommendation clear and justified
• Conditions (if any) specific and measurable
• Alternative suggestions provided if BLOCKED

Error Handling

If swap analysis fails:

1. Check if schedule data is valid
2. Verify swap parameters are correct
3. Confirm residents/dates exist
4. Escalate if data is inconsistent

If result is ambiguous:

1. Re-run with more specific parameters
2. Check for data quality issues
3. Request human review

References

• Swap management procedures in swap-management skill
• ACGME rules in acgme-compliance skill
• Swap execution in swap-execution skill