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.

ソースを見る

使い方

インストールコマンドをコピーし、自分の環境へ導入する前にソースを確認します。
必要なツール、認証情報、対応環境を原文で確認します。
入力と成果物を指定し、出力を資料と照合します。

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

開始前の確認

導入にはモデル契約、API枠、ファイルへのアクセス許可は含まれません。
スター数や導入数は活動の指標であり、独立した品質・安全性試験ではありません。

リポジトリの原文

見出し、例、コード、表、リンク、参照画像を含む原文を表示しています。

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.