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.
npx skills add vivy-yi/awesome-skills --skill paper-collectorgit clone --depth 1 https://github.com/vivy-yi/awesome-skillsWrote 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.
[](https://agentmods.dev/skills/vivy-yi/awesome-skills/paper-collector)<a href="https://agentmods.dev/skills/vivy-yi/awesome-skills/paper-collector"><img src="https://agentmods.dev/badge/skills/vivy-yi/awesome-skills/paper-collector/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.
<a href="https://agentmods.dev/skills/vivy-yi/awesome-skills/paper-collector"><img src="https://agentmods.dev/badge/skills/vivy-yi/awesome-skills/paper-collector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00079 | $0.01212 |
| Opus 5 | $0.00039 | $0.00606 |
| Sonnet 5 | $0.00016 | $0.00242 |
| Haiku 4.5 | $0.00008 | $0.00121 |
Grade A, and why
paper-collector 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.
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.
curl -s "https://export.arxiv.org/api/query?search_query=ti:agent+skill+OR+ti:tool+agent+OR+ti:agent+framework&start=0&max_results=20&sortBy=submittedDate&sortOrder=descending" | \ How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper Collector
Collects academic papers about AI Agent Skills and saves them to papers/.
Workflow
1. Search for Relevant Papers
# Search arXiv for skill-related papers
curl -s "https://export.arxiv.org/api/query?search_query=ti:agent+skill+OR+ti:tool+agent+OR+ti:agent+framework&start=0&max_results=20&sortBy=submittedDate&sortOrder=descending" | \
python3 << 'PYEOF'
import sys
import re
from datetime import datetime
xml = sys.stdin.read()
# Extract entries
entries = re.findall(r'<entry>(.*?)</entry>', xml, re.DOTALL)
papers = []
for entry in entries:
title = re.search(r'<title>(.*?)</title>', entry, re.DOTALL)
summary = re.search(r'<summary>(.*?)</summary>', entry, re.DOTALL)
link = re.search(r'<id>(.*?)</id>', entry)
published = re.search(r'<published>(.*?)</published>', entry)
if title and link:
title_clean = ' '.join(title.group(1).split())
summary_clean = ' '.join(summary.group(1).split())[:300] if summary else ""
link_url = link.group(1)
date = published.group(1)[:10] if published else ""
papers.append({
'title': title_clean,
'summary': summary_clean,
'url': link_url,
'date': date
})
print(f"Found {len(papers)} recent papers:\n")
for p in papers[:10]:
print(f"[{p['date']}] {p['title']}")
print(f" {p['summary'][:150]}...")
print()
PYEOF
2. Also Search Google Scholar / Semantic Scholar
# Search Semantic Scholar API (free, no auth needed)
curl -s "https://api.semanticscholar.org/graph/v1/paper/search?query=agent+skill+framework&limit=20&fields=title,abstract,year,citationCount,openAccessPdf,authors" | \
python3 << 'PYEOF'
import sys
import json
data = json.load(sys.stdin)
papers = data.get('data', [])
print(f"Found {len(papers)} papers on Semantic Scholar:\n")
for p in papers[:10]:
title = p.get('title', '')
year = p.get('year', '?')
citations = p.get('citationCount', 0)
abstract = p.get('abstract', '')[:200] if p.get('abstract') else ''
pdf = p.get('openAccessPdf', {}).get('url', '') if p.get('openAccessPdf') else ''
print(f"[{year}] {title} (cited: {citations})")
if pdf:
print(f" PDF: {pdf}")
print()
PYEOF
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.
- 12d ago First seen · 166 lines · 0 tokens per session scan A 21047531068c
paper-collector is a skill published in the GitHub repository vivy-yi/awesome-skills (1 stars, last pushed 3mo ago), licensed MIT. It adds 79 tokens to every session and 1,212 once invoked, about $0.0004 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…