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 WenyuChiou/research-hub --skill paper-summarizegit clone --depth 1 https://github.com/WenyuChiou/research-hubWrote 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/wenyuchiou/research-hub/paper-summarize)<a href="https://agentmods.dev/skills/wenyuchiou/research-hub/paper-summarize"><img src="https://agentmods.dev/badge/skills/wenyuchiou/research-hub/paper-summarize/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/wenyuchiou/research-hub/paper-summarize"><img src="https://agentmods.dev/badge/skills/wenyuchiou/research-hub/paper-summarize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00195 | $0.01543 |
| Opus 5 | $0.00097 | $0.00772 |
| Sonnet 5 | $0.00039 | $0.00309 |
| Haiku 4.5 | $0.00019 | $0.00154 |
Grade A, and why
paper-summarize scanned grade A with 0 findings 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 11d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
paper-summarize
The auto pipeline ingests metadata + abstract only — Summary / Key Findings / Methodology / Relevance stay as [TODO] skeletons in both Obsidian and Zotero. Cluster-level summarization (NotebookLM brief, crystals) does NOT fill per-paper notes. So after auto, the user has nothing scannable per paper without opening the PDF.
This skill fills that gap. One LLM call per paper, JSON-validated, written to both vault systems atomically (rollback the markdown change if Zotero write fails so the two stay in sync).
When to use
Trigger phrases:
- "Summarize the papers in cluster X."
- "Fill the TODO Key Findings for X."
- "I just ran
auto Xand the notes are empty — give me real summaries." - "Update Zotero notes for cluster X with what each paper actually says."
Not for:
- Generating a single CLUSTER-LEVEL summary — that's
research-hub notebooklm generate(NotebookLM brief). - Filling Q&A on the cluster — that's
research-hub crystal emit/apply. - Reading PDFs — abstract-only by design. PDF parsing is out of scope; the LLM is told to mark "[PDF needed]" if abstract is too thin.
- Verifying brief vs source — that's
notebooklm-brief-verifier.
Inputs
- Cluster slug (must already exist in the vault under
raw/<slug>/) - Optional LLM CLI override (
claude,codex,gemini,opencode,aichat,cursor, or configured custom adapter) - Optional
--applyflag (default off, dry-run)
The skill reads each paper's frontmatter (DOI, year, zotero-key) + the ## Abstract body block. Papers with empty abstract get a "PDF needed" marker rather than hallucinated findings.
Outputs
For each paper, three sections are rewritten:
- Obsidian markdown at
raw/<cluster>/<paper-slug>.md:## Key Findingscallout block (3–5 bullets)## Methodologycallout block (one sentence)## Relevancecallout block (1–2 sentences linking to the cluster topic)- Anchor IDs (
^findings,^methodology,^relevance) preserved.
What ships with it
1 file 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.
- 11d ago First seen · 108 lines · 195 tokens per session scan A 385162d00efc
paper-summarize is a skill published in the GitHub repository WenyuChiou/research-hub (54 stars, last pushed 2d ago), licensed MIT. It adds 195 tokens to every session and 1,543 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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