| name | decompose-constrained-set-search |
| description | Orchestrates a multi-stage filter-and-verify process to find a specific entity satisfying three or more independent constraints. |
When to Use
Use this skill when the user query defines a "needle in a haystack" search requiring the intersection of multiple distinct attributes. Indicators include queries for a single entity (person, place, object, or document) that must satisfy a specific timeframe, a quantitative threshold, a negative constraint (exclusion), and a specific affiliation or category simultaneously.
Decomposition Template
- Constraint Extraction: Parse the query into a checklist of independent constraints (e.g., Constraint A: Timeframe, Constraint B: Quantitative Metric, Constraint C: Exclusion/Negative, Constraint D: Affiliation).
- Primary Candidate Generation: Identify the "most restrictive" or "easiest to index" constraint. Generate a broad list of candidates that satisfy this single primary filter.
- Sequential Filtering: Pass the candidate list through the remaining constraints one by one.
- Deep Verification: For the final 1-2 candidates, perform a dedicated "fact-check" pass against every original constraint, specifically looking for "hidden" requirements or negative exclusions.
Worker Assignment Rules
- Worker 1 (The Scout): Responsible for Step 1 and 2. Must prioritize recall to ensure the "needle" is in the initial set.
- Worker 2 (The Auditor): Responsible for Step 3. Cross-references the candidate list against secondary data points.
- Worker 3 (The Critic): Responsible for Step 4. Acts as a "Red Team" to try and disqualify the final candidate based on the most easily overlooked constraint (e.g., the negative constraint).
Answer Format
The final output must clearly state how the chosen entity satisfies every constraint listed in the prompt.
End with: 最终答案:你的答案
Anti-Patterns
- The "Close Enough" Fallacy: Selecting a candidate that meets 3 out of 4 criteria because it is a high-probability match in other contexts.
- Primary Filter Failure: Starting the search with the broadest constraint (e.g., "a person") rather than the most specific one (e.g., "published in October 2023"), leading to an unmanageable candidate pool.
- Negative Constraint Oversight: Forgetting to check "Except X" or "Not including Y" during the final verification phase.
- Hallucinated Aggregation: Combining attributes from two different entities to create a "perfect" but non-existent match.
