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 kinhluan/skills --skill research-watchgit clone --depth 1 https://github.com/kinhluan/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/kinhluan/skills/research-watch)<a href="https://agentmods.dev/skills/kinhluan/skills/research-watch"><img src="https://agentmods.dev/badge/skills/kinhluan/skills/research-watch/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/kinhluan/skills/research-watch"><img src="https://agentmods.dev/badge/skills/kinhluan/skills/research-watch.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 | $0.00064 | $0.01917 |
| Opus 5 | $0.00032 | $0.00958 |
| Sonnet 5 | $0.00013 | $0.00383 |
| Haiku 4.5 | $0.00006 | $0.00192 |
Grade A, and why
research-watch 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 10d 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 "https://api.semanticscholar.org/graph/v1/paper/search?query=mechanistic+interpretability&fields=title,authors,year,abstract,citationCount&publicationDateOrYear=2024:2025" How it starts
The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Watch
Stay current without drowning in papers.
Set up intelligent monitoring for research topics, authors, venues, or keywords. Get notified when relevant new work appears, with automatic relevance scoring and synthesis.
"The literature moves fast. Your knowledge should move faster." — Anonymous Researcher
1. Watch Types
1.1 Topic Watch
Monitor a research topic for new papers:
Topic: "mechanistic interpretability"
Keywords: ["mechanistic interpretability", "circuit tracing", "activation patching"]
Venues: [NeurIPS, ICML, ICLR, arXiv cs.LG]
Frequency: weekly
Relevance scoring:
| Score | Criteria | Action |
|---|---|---|
| 90-100 | Directly addresses your research question | Read immediately |
| 70-89 | Related method or application | Read within 2 days |
| 50-69 | Same field, tangential topic | Skim abstract |
| < 50 | Same broad area | Skip, but log for completeness |
1.2 Author Watch
Track specific researchers:
Authors: ["Yann LeCun", "Yoshua Bengio", "Geoffrey Hinton"]
Rationale: "Foundational figures in deep learning"
Alert on: new papers, preprints, blog posts
1.3 Venue Watch
Monitor specific conferences/journals:
Venues: ["NeurIPS", "ICML", "ICLR", "JMLR"]
Filter: papers matching [your keywords]
Alert: when proceedings published
1.4 Citation Watch
Track who cites your work or key papers:
Target papers: [your-paper-id, foundational-paper-id]
Alert on: new citations
Include: citation context (how they cite you)
2. Setup Protocol
Step 1 — Define Watch Scope
Watch Name: [descriptive name]
Type: [topic / author / venue / citation]
Query: [keywords, authors, or paper IDs]
Sources: [arXiv / Semantic Scholar / Google Scholar / PubMed]
Frequency: [daily / weekly / monthly]
Step 2 — Configure Filters
Exclude noise:
- Negative keywords: ["survey", "review", "tutorial"] (if you want only original research)
- Minimum citations: [0 for new work, 10 for established work]
- Date range: [last 30 days / last 90 days / all time]
What ships with it
3 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.
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.
- 10d ago First seen · 267 lines · 64 tokens per session scan A c638eebc4317
research-watch is a skill published in the GitHub repository kinhluan/skills (4 stars, last pushed 13d ago), licensed MIT. It adds 64 tokens to every session and 1,917 once invoked, about $0.0003 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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