Paper Discussion Full
SkillDev toolsUse when the user wants the full multi-stage paper discussion workflow, a comprehensive structured discussion of one paper, or an equivalent full-discussion request in another language.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Paper Discussion Full skill
What this skill tells your AI
The instructions your AI receives, as published by spectrai-initiative/innoclaw in .claude/skills/paper-discussion-full/SKILL.md and read by ahel’s review.
Use this skill when the user wants the full structured discussion workflow for one paper rather than a simple Q&A exchange.
Goal
Produce a comprehensive, evidence-grounded discussion report for one paper by emulating the full discussion pipeline:
- Moderator
- Librarian
- Skeptic
- Reproducer
- Convergence
- Final Scribe Report
Workflow
- Identify the target paper. If it is missing, ask for the title, URL, or PDF link.
- Use
readPaperto ground the analysis in the full paper whenever possible. - If the user explicitly wants related-work comparison, use
searchArticlesto retrieve nearby papers; otherwise stay tightly focused on the selected paper. - Reason through the following stages in order and expose the stage outputs clearly:
- Agenda
- Evidence Summary
- Critical Analysis
- Reproducibility Check
- Convergence
- Final Report
- Keep every stage grounded in available evidence. When evidence is missing, say so explicitly.
Stage Expectations
Agenda
- Define the discussion focus.
- Name the main evaluation axes: novelty, evidence quality, methodology, reproducibility, limitations.
Evidence Summary
- State the core claim, method, setup, and reported results.
- Separate explicit evidence from inference.
- When referencing external work for comparison, cite it using
searchArticlesresults.
Critical Analysis
- Challenge overclaims, weak baselines, missing ablations, and threats to validity.
- Mark issue severity as
Critical,Moderate, orMinor. - When identifying missing baselines or comparing to external methods, cite specific papers found via
searchArticles.
Reproducibility Check
- Judge whether the paper is easily, partially, or poorly reproducible.
- List what is specified versus what is missing.
- Propose a minimal reproduction recipe.
Convergence
- Summarize agreement, disagreement, and unresolved questions.
Final Report
Use this exact structure:
Paper Discussion Report
1. Paper Snapshot
2. Key Claims
3. Strengths
4. Weaknesses / Risks
5. Reproducibility Assessment
6. Open Questions
7. Recommended Next Actions
End with:
Overall take: ...
8. References
Quality Rules
- Do not fabricate details not present in the paper context. All external references must come from
searchArticlesresults, never from model memory. - Keep criticism specific and technically grounded.
- Preserve nuance rather than collapsing everything into a single score.
- If paper text cannot be retrieved, state that the report is based on limited context.
Citation Policy
- Any claim about related work, competing methods, or external benchmarks MUST include a citation retrieved via
searchArticles. Do NOT cite from memory. - When the discussion references methods or results not in the seed paper, call
searchArticlesfirst and cite what is returned. - If no supporting reference is found, mark the claim: [Unverified — no supporting reference found via search].
- The target paper itself must be cited formally at the top of the report.
Inline Citation & Reference Format
Use numbered inline citations in the text body (e.g., [1], [2]) and collect full references in the ## 8. References section. All references MUST be rendered in markdown so they are clickable and well-formatted:
Inline example:
该方法在 ImageNet 上超越了 ViT [1],但在小数据集上的泛化能力受到质疑 [2]。
References section example:
## 8. References
1. **Dosovitskiy, A. et al.** (2021). *An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.* ICLR 2021. [arXiv:2010.11929](https://arxiv.org/abs/2010.11929)
2. **Liu, Z. et al.** (2021). *Swin Transformer: Hierarchical Vision Transformer using Shifted Windows.* ICCV 2021. [DOI:10.1109/ICCV48922.2021.00986](https://doi.org/10.1109/ICCV48922.2021.00986)
- Each reference line MUST include: Author(s) (Year). Title. Venue/Journal. Linked DOI or URL when available from
searchArticles. - Use markdown bold for authors, italic for title, and
[text](url)for clickable DOI/URL links. - Number references sequentially as they first appear in the text.
Signals
- GitHub stars
- 391
- Forks
- 28
- Last commit
- Aug 2026
Advanced
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paper-discussion-full- Source
- github.com/spectrai-initiative/innoclaw