本文へ移動
cccskills
無料GitHub で公開

review-experiment

Review one terminal experiment and choose the next step: merge a reproducible winner, close a useful negative or dead end, or request missing evidence.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md4.9 KB

SKILL.md(原文)

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。

Review an experiment

Use get_prs for the complete discussion and the current base and head SHAs. For code review, call get_pr_source with number, expected_base_sha, and expected_head_sha. Its first response lists changed paths. Call it again with up to eight selected paths, then read the returned artifact. It contains complete text diffs and source at the comparison merge base and head. This also works for merged PRs and private repositories; no shell credential is needed. Pass the artifact to a review subagent when appropriate. If either PR SHA changes, refresh the discussion and source before deciding. This read tool does not authorize merging an operator PR through a student-assignment workflow.

Retrieve the complete PR with get_prs. Verify its assignment, current head SHA, terminal structured result, W&B evidence, metric direction, and scientific conclusion. Then choose the appropriate next step:

  • merge a reproducible improvement;
  • close a completed control, clean negative, invalid candidate, or bounded dead end with a clear reason; or
  • request a revision when the evidence is incomplete or another bounded run is required.

Merge a winner

{
  "assignment": {
    "pr_number": 123,
    "assignment_id": "assignment-id",
    "revision_id": "current-revision-id",
    "expected_pr_head_sha": "CURRENT_PR_HEAD_SHA"
  },
  "expected_current_base_sha": "CURRENT_BASE_SHA",
  "merge_method": "squash"
}

Call merge_experiment. It refuses drafts, missing or foreign results, stale heads, blocking labels, unknown mergeability, and conflicts. It compares the assignment's base SHA with the live base branch immediately before merging. If the research base changed, reassess the exact terminal result against the event's current_base_sha.

If the conclusion still holds, record that decision before merging:

{
  "assignment": {
    "pr_number": 123,
    "assignment_id": "assignment-id",
    "revision_id": "current-revision-id",
    "expected_pr_head_sha": "CURRENT_PR_HEAD_SHA"
  },
  "expected_current_base_sha": "CURRENT_BASE_SHA",
  "reason": "Why this exact result remains valid against the current research base."
}

Call accept_result_on_current_base with that payload. Its durable acceptance is bound to the assignment, revision, result head, canonical structured result, and exact current base SHA. If any of them changes, reassess. If the conclusion no longer holds, request a new revision instead. Never invent a SHA or call gh pr merge.

Close a completed non-winner

{
  "assignment": {
    "pr_number": 123,
    "assignment_id": "assignment-id",
    "revision_id": "current-revision-id",
    "expected_pr_head_sha": "CURRENT_PR_HEAD_SHA"
  },
  "reason": "Concise scientific reason for closing this experiment."
}

Call close_experiment. Distinguish a useful negative from an invalid or incomplete run. Do not edit labels, write protocol markers, or close the PR with gh.

Request a revision

{
  "assignment": {
    "pr_number": 123,
    "assignment_id": "assignment-id",
    "revision_id": "current-revision-id",
    "expected_pr_head_sha": "CURRENT_PR_HEAD_SHA"
  },
  "new_revision_id": "new-revision-id",
  "required_base_sha": "ASSIGNED_OR_LIVE_BASE_SHA",
  "comment": "Exact missing evidence and the bounded next run required."
}

Call request_assignment_revision. Use a new stable revision ID and the exact research base SHA the next revision must use. State one concrete change or experiment and its acceptance evidence; do not close an experiment that can still answer the assigned question with one bounded correction.

Pass the assignment's recorded base_sha when the revision must preserve the tested source, including after the advisor publishes research notes. Select the exact live base SHA only when the student must incorporate that base before running. Other SHAs are rejected. Prose cannot override the recorded base: every submitted result must contain that exact commit. A result on the retained base still needs accept_result_on_current_base before merging onto a changed live base.

Record the outcome

Update the baseline or research log in the format prescribed by program.md, including the PR, metrics, run IDs and links, reproduction command, and conclusion. Commit that advisor-owned change and publish it only through:

{
  "remote_branch_sha_before_push": "REMOTE_SHA_BEFORE_PUSH",
  "local_commit_sha": "LOCAL_COMMIT_SHA"
}

Call publish_advisor_branch; it publishes only the configured advisor branch.

Review multiple candidates strongest-first and refresh the baseline between each decision.

レビュー

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。

同じリポジトリのスキル

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。

wandb/senpai372026年10月6日 更新

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。

wandb/senpai372026年10月6日 更新

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。

wandb/senpai372026年10月6日 更新

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。

wandb/senpai372026年10月6日 更新

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".

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。

wandb/senpai372026年10月6日 更新

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。

wandb/senpai372026年10月6日 更新

wandb のスキルをすべて見る

このスキルの問題を報告する