Name: Skill: scientific threshold and context inference
Author: Dingxingdi

Skill: scientific threshold and context inference

Use this skill when the user wants SQL data where the agent must infer hidden expert rules rather than just read column names. Trigger it for requests like “make the model use an unstated threshold”, “the question should rely on domain conventions”, “approved should not just mean a boolean flag”, or “it should need scientific background to write the SQL correctly.” Example trigger: “The hard part should be an implied threshold.” Example trigger: “I want expert-rule SQL, not literal schema matching.” Example trigger: “The model should have to infer what counts as significant or approved.”

Dingxingdi0 星标2026年4月8日

职业
分类: SQL 数据库

1. Capability Definition & Real Case

Professional Definition: The ability to operationalize implicit domain conventions that are not explicitly encoded in the schema, such as significance thresholds, effect directionality, trial-phase interpretation, or approval logic that depends on external scientific context.
Dimension Hierarchy: Query Reasoning->Domain-Constrained Semantics->scientific threshold and context inference

Real Case

[Case 1]

Initial Environment: A biomedical BigQuery database stores GWAS summary statistics including p-values, beta coefficients, gene mappings, and disease labels. The schema does not itself encode the phrase “increase the risk” as a ready-made field.
Real Question: Are there any C9orf72 gene mutations that increase the risk of Parkinson’s disease?
Real Trajectory: Filter the Parkinson’s GWAS table to the target gene, apply the genome-wide significance threshold, constrain the beta direction to positive effect, and then inspect the remaining variants.
: A correct SQL answer requires applying both p-value and directionality conventions rather than merely filtering on the gene name.

Skill: scientific threshold and context inference

Dingxingdi0 星标2026年4月8日

职业
分类: SQL 数据库

1. Capability Definition & Real Case

Professional Definition: The ability to operationalize implicit domain conventions that are not explicitly encoded in the schema, such as significance thresholds, effect directionality, trial-phase interpretation, or approval logic that depends on external scientific context.

Dimension Hierarchy: Query Reasoning->Domain-Constrained Semantics->scientific threshold and context inference

Real Case

[Case 1]

Initial Environment: A biomedical BigQuery database stores GWAS summary statistics including p-values, beta coefficients, gene mappings, and disease labels. The schema does not itself encode the phrase “increase the risk” as a ready-made field.

Real Question: Are there any C9orf72 gene mutations that increase the risk of Parkinson’s disease?

Real Trajectory: Filter the Parkinson’s GWAS table to the target gene, apply the genome-wide significance threshold, constrain the beta direction to positive effect, and then inspect the remaining variants.

: A correct SQL answer requires applying both p-value and directionality conventions rather than merely filtering on the gene name.

Skill: scientific threshold and context inference

1. Capability Definition & Real Case

Real Case

Skill: scientific threshold and context inference

1. Capability Definition & Real Case

Real Case

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