firstp1ck/pi-coding-agent-forge/paper-summarizer

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Agents should invoke this skill for academic or technical papers, arXiv/PubMed/IEEE/ACM links, PDFs, methodology review, limitations, practical implications, or extracting findings for engineering decisions.

Install

npx vskill@latest install firstp1ck/pi-coding-agent-forge/paper-summarizer

SKILL.md

Paper Summarizer

Extract actionable insights from academic and technical papers.

Summary Format

markdown
# Paper Summary: <Paper Title>
**Authors:** [Author list]
**Published:** [Journal/Conference, Date]
**Link:** [URL]
**Quality:** Peer-reviewed / Preprint / Workshop paper
## TL;DR
[1-2 sentence summary of the key contribution]
## Problem
[What problem does this paper address? Why does it matter?]
## Approach
[Methodology in plain language — what did they do?]
## Key Findings
Anchor each finding to the paper so readers can verify. Use **§** for sections, **Fig.** / **Table** when the evidence is visual or tabular.
1.**[Finding 1]:** [Description with key metrics/numbers] — *Evidence:* §[N] [section name]; [Fig. X / Table Y if applicable]
2.**[Finding 2]:** [Description] — *Evidence:* §[N] …
3.**[Finding 3]:** [Description] — *Evidence:* §[N] …
## Claim–evidence map
| # | Claim (one line) | Where in paper | Type |
|---|------------------|----------------|------|
| 1 | [Claim] | §3.2 Results, Table 2 | Empirical |
| 2 | [Claim] | §1 Introduction | Stated goal |
| 3 | [Claim] | Fig. 4 | Qualitative |
Use this table for **citation audit** alignment (`workspace-researcher/AGENTS.md`). If the PDF has no section numbers, use **page** or **heading text** instead of §.
## Practical Implications
[What does this mean for practitioners? How can we use these findings?]
-For our stack: [Specific applicability to Rust/TS/Python work]
-For our projects: [How this might inform current work]
## Limitations
-[Limitation 1: e.g., small sample size, specific domain]
-[Limitation 2: e.g., not replicated, theoretical only]
## Related Work
-[Paper 1] — [How it relates]
-[Paper 2] — [How it relates]
## Verdict
**Reliability:** High / Medium / Low
**Relevance to us:** High / Medium / Low
**Action:** Apply directly / Consider for future / Interesting but not actionable

Process

Step 1 — Access the Paper
  • Check arXiv, PubMed, Google Scholar for open-access versions
  • If behind a paywall, note this and work with the abstract and any available supplementary material
  • Check for author's personal page (often has preprints)
Step 2 — Read Strategically
  1. Abstract — Get the overview
  2. Introduction (last paragraph) — Usually states the contribution
  3. Figures and tables — Often convey key results
  4. Conclusion — Summary of findings and limitations
  5. Methodology — If the findings are relevant enough to dig deeper
Step 3 — Extract claims with locations

Before paraphrasing implications, list atomic claims the paper makes (results, bounds, contributions). For each: section / figure / table reference (or page). Prefer primary evidence (results section) over abstract-only restatement.

Step 4 — Extract Practical Value

The most important question: "What can we do differently because of this paper?"

  • If the answer is "nothing" — still summarize, but note low actionability
  • If the answer is specific — tie each implication to a row in Claim–evidence map where possible
Step 5 — Assess Reliability
FactorAssessment
Peer review statusPublished / Preprint / Workshop
ReplicationReplicated / Single study / Theoretical
Sample sizeAdequate / Small / N/A
Methodology rigorStrong / Moderate / Weak
Author credibilityEstablished / New / Anonymous
Conflicts of interestNone apparent / Funded by [X] / Vendor paper

_Scout skill — Academic paper summarization and insight extraction · P1 claim–evidence map: 2026-04-10_

Security

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  • Model reviewPassed

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