Search academic papers, scholarly articles, and research publications through SandBase. Use when asked for literature review, academic citations, scholarly research, paper discovery, or scientific evidence gathering.
日本語の概要は準備中です。原文の説明を表示しています。
Generate concise, actionable meeting minutes for internal meetings. Includes metadata, attendees, agenda, decisions, action items (owner + due date), and follow-up steps.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
This Skill produces high-quality, consistent meeting minutes for internal meetings that are 60 minutes or shorter. Output is designed to be clear, actionable, and easy to convert into task trackers (e.g., GitHub Issues, Jira). The generated minutes prioritize decisions and action items so teams can move quickly from discussion to execution.
When source material is supplied as a web page or a published video, read the SandBase API map. Resolve the listed capability with sandbase_discover, inspect its returned name with sandbase_inspect, then follow execute_as to call sandbase_run(name: "<returned name>", arguments: { ... }) using only the current schema. For async results, poll sandbase_run_get with the returned run_id within the task budget; report pending or failed runs without automatically resubmitting them.
Use this skill when:
Before generating minutes, the agent MUST ask up to three clarifying questions if any of these are missing:
If the user responds "no transcript" or "no agenda," proceed but mark source material as "ad-hoc notes" and flag potential gaps.
You MUST produce meeting minutes following this exact structure. If information is unavailable, use TBD or Unknown and explain how to obtain it.
Bullet list of agenda items, in order:
A concise one-paragraph summary (1–3 sentences) of the meeting's objective and high-level outcome.
Each as a separate bullet:
Table-style bullets; must include owner and due date:
Example:
Brief, factual, timestamp optional:
TBD and note the missing info source.DO:
DON'T:
Prompt to generate minutes from transcript:
"Generate meeting minutes from the following meeting transcript. Meeting title: 'Platform Weekly Sync'. Date: 2026-02-10. Duration: 45 minutes. Organizer: Priya (Platform Lead). Transcript: <paste transcript>. Follow the Strict Minutes Schema. Highlight decisions and create action items with owners and due dates where implied."
Prompt to generate minutes from notes:
"I have raw notes from a 30-minute design review. Title: 'Feature Y Design Review'. Date: 2026-02-11. Notes: <paste notes>. Produce concise minutes following the Strict Minutes Schema. Ask up to 3 clarifying questions if critical fields are missing."
- Title:
- Date:
- Organizer:
- Present:
- Summary:
- Decisions:
- Decision 1 — Who — Effective:
- Action Items:
- [A1] Action — Owner — Due — Acceptance Criteria
- Next Steps / Next Meeting:
Use the Strict Minutes Schema above.
A generated minutes document is acceptable if:
None.TBD.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Search academic papers, scholarly articles, and research publications through SandBase. Use when asked for literature review, academic citations, scholarly research, paper discovery, or scientific evidence gathering.
日本語の概要は準備中です。原文の説明を表示しています。
Research emerging academic trends by combining scholarly databases, web sources, and news to identify rising research areas, breakthrough papers, and shifting scientific consensus. Ideal for R&D teams tracking frontier science.
日本語の概要は準備中です。原文の説明を表示しています。
Create, implement, or review accessibility review work with format, accessibility, performance, and visual-verification controls. Use when the requested deliverable depends on accessibility review.
日本語の概要は準備中です。原文の説明を表示しています。
Plan, implement, or review agentic eval work in an existing codebase with compatibility, security, and verification controls. Use when the user explicitly requests agentic eval work.
日本語の概要は準備中です。原文の説明を表示しています。
Create or review ai seo deliverables with audience, evidence, voice, and conversion-quality controls. Use when the user explicitly asks for ai seo work.
日本語の概要は準備中です。原文の説明を表示しています。
Apply airflow dag patterns in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses airflow dag patterns or its strengths fit the task.
日本語の概要は準備中です。原文の説明を表示しています。