yogsoth-ai/de-anthropocentric-research-engine

define-evidence-protocol

Define research questions, evidence scope, queries/concepts, inclusion/exclusion rules, provenance requirements, and stopping evidence for an acquisition task.

소스 보기

사용 방법

설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.

npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill define-evidence-protocol

시작 전 확인

설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.

원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

define-evidence-protocol

Purpose

Define research questions, eligible evidence scope, query concepts, inclusion/exclusion rules, provenance requirements, and stopping evidence.

Input contract

yaml

required: [research_question, evidence_scope, inclusion_rules]
optional: [exclusion_rules, query_concepts, quality_rubric, stopping_policy]
constraints: [eligible universe, provenance fields, and stopping evidence must be explicit]

Procedure

State the question, target population or domain, comparison, outcomes, and time boundaries.
Define eligible evidence, exclusion rules, source-independence requirements, and extraction fields.
Specify batch boundaries, novelty dimensions, and relative stopping evidence.
Record unresolved scope choices before acquisition begins.

If the protocol fixes inclusion, exclusion, and stopping rules, consider select-seed-evidence as the next tactic.

Output contract

yaml

produces: [evidence_protocol, eligible_universe, query_concepts, screening_rules, provenance_requirements, stopping_evidence]
delta_fields: [decisions, assumption_updates, uncertainties, open_questions]

Quality gates

The eligible universe and exclusion rules are operational.
Stopping evidence names numerator, denominator, batch increment, source references, direction, threshold, and rationale when relative quantities apply.