Look up any arxiv paper on alphaxiv.org to get a structured AI-generated overview. This is faster and more reliable than trying to read a raw PDF.
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。
Open GitHub Issues for human input and respond to the researcher team. Use this skill whenever you need to handle a human_issue event, respond to human issues, ask humans a question, or check team communications. Also triggers for: "any human messages?", "check issues", "respond to humans".
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。
Check GitHub Issues tagged human for messages from the research team, and respond to any that need a reply.
ADVISOR, or student name for
STUDENTADVISOR or STUDENTHuman researchers communicate with agents through GitHub Issues. Issues are
tagged with human plus team for a broadcast, the configured advisor branch
for an advisor, or student:<student-name> for a student. Your job is to check
messages routed to your exact role, respond to new ones, and skip ones you've
already handled.
Use create_human_issue when you need a research decision or help with a blocker.
Provide a stable issue_id, a concise title, and the complete body without a
role prefix. Reuse the same ID, title, and body if the call needs a retry. Changed
content requires a new ID.
The runtime adds human and your configured audience label. It mentions the
GitHub credential owner in the initial issue body when GitHub identifies that
owner as a user account. This includes service accounts registered as ordinary
users. Bot identities, tokens without a user identity, and failed lookups skip
the mention without blocking issue creation. Do not add notification mentions
yourself. Later replies do not repeat these automatic mentions.
{
"issue_id": "confirm-next-seed-budget",
"title": "Confirm the budget for another seed",
"body": "The first two seeds disagree. Can we use the remaining budget for a third seed?"
}
Read the current human_issue event. The controller supplies the issue
identity and the exact human message ID that triggered the wake. It polls
GitHub for issues addressed to you or the whole team.
Decide whether to respond:
id of the issue body or human comment you are
answering. Never substitute the issue number for a comment ID.Respond through respond_to_human_issue with the issue number, the exact
human_message_id, and the response text without a role prefix. This verified,
idempotent operation refuses closed issues, pull requests, missing human
labels, stale message IDs, Senpai protocol messages from the agent identity, and
issues not addressed to this configured advisor branch or student.
{
"issue_number": 123,
"human_message_id": 987654,
"response": "<your response>"
}
Never mutate the issue through gh or curl.
When you're done, record a structured summary of the issues you checked and responded to in the current conversation:
If there are research directives in the issues, include them in detail so they remain available for subsequent planning in this conversation.
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
Look up any arxiv paper on alphaxiv.org to get a structured AI-generated overview. This is faster and more reliable than trying to read a raw PDF.
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。
Operator-side analysis of historical ML experiment PRs in Senpai research tracks. Use this skill whenever the user asks to: analyze experiments, categorize PRs, bucket experiments, summarize what's been tried, understand experiment history, review merged vs closed results, or asks "what experiments have we run / worked / failed". Also triggers for: "pull the latest experiments", "what's been tried so far", "category breakdown of PRs", "which experiments succeeded", "noam track analysis". When a branch name is mentioned (e.g. "noam branch", "on the noam branch"), pass it as the base branch to scope the fetch to just those PRs.
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 a typed assignment branch and draft PR for one student. Use when the advisor has a concrete hypothesis and the student has no open `status:wip` or `status:review` assignment.
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 improve a Senpai target repository's program.md. Use this skill whenever the user wants to point Senpai at a fresh ML or research target repository, define the research objective, primary metric, benchmark contract, allowed edit boundaries, W&B reporting contract, or prepare a repo for autonomous advisor/student experiment loops.
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。
Choose, configure, launch, and collect bounded subagents for research and engineering decisions. Root agents and delegation-capable subagents should read this before delegating: every task requires an explicit model tier, and high-leverage work such as research ideation, round planning, plateau pivots, large research reviews, hard optimization, disputed evidence, and expensive experiment portfolios requires frontier judgment.
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。
Search the general web or scholarly publications through Exa. Use for current public information, official documentation, source code, release notes, papers, preprints, journals, or literature research.
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。