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Paper tutorial briefing

Skill StaryMoon/ai-researcher-skills/skills/paper-tutorial-briefing

Practical skill pack for AI research agents: paper briefing, experiment planning, rebuttal drafting, radar maintenance, and GitHub upkeep.

Install
npx -y skills add StaryMoon/ai-researcher-skills --skill paper-tutorial-briefing

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

One thing to look at

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SKILL.md

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Paper Tutorial Briefing

Purpose

Turn an AI paper into a rigorous but readable tutorial briefing. The goal is not to paraphrase the abstract; the goal is to help a researcher understand what the paper changes, what evidence supports it, and what should be tried locally next.

When To Use

Use this skill when the user gives a paper PDF, arXiv link, title, project page, README, or local paper note and asks for a technical explanation, tutorial, daily briefing entry, or research direction.

Inputs

  • Paper PDF, URL, title, or extracted text.
  • Optional code repository or project page.
  • Optional local research context, baseline, metric, or dataset.
  • Optional target audience such as beginner, reviewer, implementer, or project maintainer.

Workflow

  1. Identify the paper metadata: title, venue or preprint status, authors if available, task, model family, and main artifact.
  2. Produce a one-sentence takeaway that states the technical move, not the marketing claim.
  3. Extract the contribution stack: problem setting, key mechanism, training or inference recipe, evidence, and stated limitations.
  4. Build an evidence map. Separate paper-reported metrics, qualitative figures, ablations, and any local evidence.
  5. Explain the method with one concrete implementation mental model: tensors, modules, prompts, losses, memory, data flow, or evaluation loop.
  6. Identify reproduction risk: missing details, compute assumptions, hidden preprocessing, dataset ambiguity, or metric mismatch.
  7. End with next actions: shortest faithful experiment, stop rule, and what result would justify adding it to a repo or briefing.

Output

Use this structure unless the user asks otherwise:

  • One-Sentence Takeaway
  • Why This Paper Exists
  • Core Mechanism
  • Evidence Map
  • Implementation Notes
  • Reproduction Risks
  • Next Local Actions

Quality Gates

  • Do not claim results were reproduced unless local commands or logs prove it.
  • Mark uncertainty explicitly: paper claim, local evidence, or inference.
  • Prefer named metrics, datasets, and ablations over vague praise.
  • If the paper text is unavailable, say what is missing and base the briefing only on accessible sources.

Keep looking

Skills are one crate of 328,083. 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.