category-sorting
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npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/category-sortingClassifies candidates into predefined categories using multi-criteria decision methods.
- Solves classification tasks where alternatives must be assigned to distinct categories.
- Uses ELECTRE-Tri, FlowSort, AHPSort, and DRSA methods for structured decision-making.
- Determines category membership based on criteria scores, weights, and thresholds.
- Returns a classification result with each candidate assigned to a category.
SKILL.md
.github/skills/category-sortingView on GitHub ↗
--- name: category-sorting description: Classify candidates into predefined categories using ELECTRE-Tri, FlowSort, AHPSort, or DRSA methods. used-by: multi-criteria-scoring --- # Category Sorting **Purpose:** Classify candidate alternatives into predefined categories (e.g., A/B/C grades, compliant/non-compliant), supporting ELECTRE-Tri, FlowSort, AHPSort, DRSA, and other classification methods. **When to use:** - User needs to classify alternatives rather than rank them - Predefined category boundaries exist (e.g., pass/fail, excellent/good/poor) - Need to independently determine category membership for each alternative ## Budget | Base SOP | Target | ±10% Range | |----------|--------|------------| | criterion-definition | 5-8 criteria | 4-9 | | weight-elicitation-sop | 1 weight vector | 1 | | threshold-setting | 1 threshold set | 1 | | alternative-scoring | 1 score matrix | 1 | | scoring-synthesis | 1 classification | 1 | ## State Ledger ```yaml strategy: category-sorting status: pending categories_defined: false criteria_defined: false weights_computed: false thresholds_set: false scores_computed: false classified: false result: null ``` ## Available Tactics - **scoring-matrix-construction** — Build scoring foundation - **screening-then-scoring** — Hybrid workflow: screen first, then classify ## Available SOPs ### Import (from tactics) - criterion-definition - weight-elicitation-sop - alternative-scoring - threshold-setting ### Subagent - scoring-synthesis ## Execution Guidance 1. Define category definitions and boundary conditions 2. Invoke criterion-definition to determine classification criteria 3. Invoke threshold-setting to set category boundaries 4. Score each alternative independently and determine category membership 5. Handle borderline cases (pessimistic vs optimistic assignment) ## Output Format ```markdown ## Classification Results **Method:** [ELECTRE-Tri / FlowSort / AHPSort / DRSA] **Category Definitions:** [A=Excellent, B=Good, C=Needs Improvement, D=Unqualified] ### Classification Table | Alternative | Category | Confidence | Boundary Distance | |-------------|----------|------------|-------------------| ### Borderline Cases [List alternatives near category boundaries and their sensitivity] ```