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Arbor agent search

Skill RUC-NLPIR/Arbor/skills/arbor-agent-search

Related-work and novelty annotation phase for Arbor. Use after a node has been experimentally validated, especially before merge decisions, to emulate SearchIdeaContext/SearchIdeaContextParallel/SearchStatus, validated-node gating, background SearchAgent behavior, and structured prior-art summaries.From its SKILL.md

Install
npx -y skills add RUC-NLPIR/Arbor --skill arbor-agent-search

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

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Arbor Search Agent

Use this for post-experiment related-work annotation. It is not for internal codebase search; use normal file tools for that.

Eligibility Gate

By default, only search nodes that are validated and effective:

  • node status is done or merged;
  • node has a numeric score;
  • score improves over current trunk_score, or over baseline_score if trunk is unavailable.

Skip pending, running, unscored, and below-trunk nodes. This keeps novelty cost tied to merge candidates.

When To Search

  • After RunExecutor returns a node with score > trunk_score.
  • Before GitMergeBranch when novelty or related work affects the decision.
  • After parallel executor results, annotate all sibling winners with SearchIdeaContextParallel.

Do not search trivial parameter tweaks, pure scale-ups, or internal codebase questions.

SearchAgent Task

The SearchAgent is a novelty scout. It does not implement, critique, or change the idea. It surveys prior work and writes a Markdown annotation to node.related_work.

Use 2-3 query angles:

  • technique class;
  • application domain;
  • key mechanism.

For ML/NLP literature, use English academic queries with words such as paper, arxiv, or survey; include one original-language query when useful.

Hard Caps

  • At most 2 search rounds.
  • Visit up to 5 pages total.
  • Keep the result short enough for a researcher to judge novelty quickly.

Final JSON Schema

When running an isolated SearchAgent, ask it to emit only:

{
  "summary": "2-4 sentences describing prior work.",
  "related_papers": [
    {
      "title": "Paper title",
      "url": "https://...",
      "one_line_relevance": "Why this is relevant."
    }
  ],
  "novelty_assessment": "novel | partial-overlap | prior-art-exists",
  "overlap_risks": "What specifically overlaps, or 'none'."
}

Render it into:

### Summary
...

### Related Papers
- [Title](url) - relevance

### Novelty
novel | partial-overlap | prior-art-exists - justification

### Overlap Risks
...

Background Behavior

Native Arbor usually runs SearchAgent in the background:

  • SearchIdeaContext returns a dispatch message immediately.
  • The coordinator continues IDEATE/DISPATCH work.
  • The result lands on node.related_work later.
  • SearchStatus reports in-flight searches.
  • Shutdown waits for pending searches to flush.

When emulating in a host that lacks background tasks, run search synchronously and update related_work before merging.

Failure Handling

Failures are non-blocking. Write a marker such as:

[search-failed: <reason>]

Treat it as no information, not evidence of novelty.

Keep looking

Skills are one crate of 627,801. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.