trace-paper-followups

trace-paper-followups is a skill for Claude Code, Codex from juliakorovsky/claude-skills. It costs 184 tokens per session (3,546 once invoked), scanned A, original, MIT.

A research-tracking workflow that starts with one paper, model, method, or architecture and examines the later papers that cite it.

In plain words
What is it for?
Use it to map follow-up research, compare how later studies changed the original idea, and write an evidence-based summary.
Why use it?
Citation lists include many papers that only mention the original work. This separates genuine extensions and improvements from passing references.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to map follow-up research, compare how later studies changed the original idea, and write an evidence-based summary.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/juliakorovsky/claude-skills/trace-paper-followups
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add juliakorovsky/claude-skills --skill trace-paper-followups
Clone the repo
git clone --depth 1 https://github.com/juliakorovsky/claude-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for trace-paper-followups

README.md
[![agentmods](https://agentmods.dev/badge/skills/juliakorovsky/claude-skills/trace-paper-followups/github.svg)](https://agentmods.dev/skills/juliakorovsky/claude-skills/trace-paper-followups)
Your own site
<a href="https://agentmods.dev/skills/juliakorovsky/claude-skills/trace-paper-followups"><img src="https://agentmods.dev/badge/skills/juliakorovsky/claude-skills/trace-paper-followups/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for trace-paper-followups

Your own site · 80×15
<a href="https://agentmods.dev/skills/juliakorovsky/claude-skills/trace-paper-followups"><img src="https://agentmods.dev/badge/skills/juliakorovsky/claude-skills/trace-paper-followups.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 184 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,546 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00184 $0.03546
Opus 5 $0.00092 $0.01773
Sonnet 5 $0.00037 $0.00709
Haiku 4.5 $0.00018 $0.00355

Measured 12d ago against content hash b1f7cb6849df, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

trace-paper-followups scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

The scan reads SKILL.md. This mod also ships 5 executable files (scripts/digest.py, scripts/download_pdfs.py, scripts/fetch_citations.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- `urllib` over a misconfigured cert store throws `CERTIFICATE_VERIFY_FAILED`; the
research/trace-paper-followups/SKILL.md · 244 lines

How it starts

The opening of the file, as written. The whole thing — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Trace what later research did with a paper

The job: start from one seed work (a paper, model, method, or architecture) and produce an honest map of the research that came after it — separating real follow-ups (things that extend or improve the seed) from the large mass of papers that only cite it in passing.

This is a pipeline of cheap automated steps wrapped around one irreducibly model-driven step: reading and judging each candidate. Citation databases and keyword filters are noisy; the value you add is reading abstracts and deciding what each paper actually did relative to the seed. Don't try to automate that judgment away.

The pipeline

Work through these in order. Each script lives in scripts/ and is run with python3. Keep every stage's output in separate files so the lineage is traceable (raw citations → judged → prose), and pick a short <slug> for the seed (e.g. sam, mamba).

1. Identify the seed and read it first

Get the seed's arXiv id (or DOI / Semantic Scholar id). If you'll be making claims about what the seed is, read the seed paper before trusting how other papers describe it — secondhand summaries drift, and a comparison built on a wrong mental model of the seed is wrong everywhere. Download it with download_pdfs.py --ids <seed-id> and digest it with digest.py.

Then write a small <slug>_seed.json profile of the seed — its name, any aliases it's known by, arxiv id, a one-line what it is, and its baseline capabilities/modalities. This is what later questions are answered against: "did anyone add video to Moshi?" can only be answered honestly if the record says Moshi has no video to begin with. Shape:

{ "slug": "moshi", "name": "Moshi", "aliases": ["Moshi", "Mimi"],
  "arxiv": "2410.00037", "what": "Full-duplex speech-text model for real-time dialogue.",
  "capabilities": ["speech-in", "speech-out", "full-duplex", "real-time"],
  "modalities": ["audio", "text"],
  "code": "https://github.com/kyutai-labs/moshi" }

Include the seed's own reference implementation (code) if it has one — set it to null if there genuinely isn't one.

Read the full file on GitHub · 244 lines

Files

What ships with it

9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 244 lines · 184 tokens per session scan A b1f7cb6849df

Subscribe to this mod's changes

trace-paper-followups is a skill published in the GitHub repository juliakorovsky/claude-skills (2 stars, last pushed 21d ago), licensed MIT. It adds 184 tokens to every session and 3,546 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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