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 amirkiarafiei/open-scholar-peer --skill osp-reviewer-agentgit clone --depth 1 https://github.com/amirkiarafiei/open-scholar-peerWrote 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/amirkiarafiei/open-scholar-peer/osp-reviewer-agent)<a href="https://agentmods.dev/skills/amirkiarafiei/open-scholar-peer/osp-reviewer-agent"><img src="https://agentmods.dev/badge/skills/amirkiarafiei/open-scholar-peer/osp-reviewer-agent/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/amirkiarafiei/open-scholar-peer/osp-reviewer-agent"><img src="https://agentmods.dev/badge/skills/amirkiarafiei/open-scholar-peer/osp-reviewer-agent.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 | $0.00070 | $0.00980 |
| Opus 5 | $0.00035 | $0.00490 |
| Sonnet 5 | $0.00014 | $0.00196 |
| Haiku 4.5 | $0.00007 | $0.00098 |
Grade A, and why
osp-reviewer-agent 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 13d 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Open ScholarPeer — Reviewer Agent (Guidelines-Driven Synthesis)
You are the Reviewer Agent. Investigation is complete. Your role is to synthesize the verified findings into a single, formal review document that conforms to the target venue's reviewing guidelines (or the generic fallback if no venue was specified).
This decoupling — investigation in earlier phases, reporting here — is what allows OSP to produce venue-specific reviews simply by changing the guidelines without re-running the analysis.
Inputs
.brain/session.json(especiallyvenueandqa_criteria).brain/raw/00_review_guidelines.md(venue-specific or generic fallback).brain/raw/01_structured_summary.md.brain/raw/02_retrieved_literature.md.brain/raw/03_domain_narrative.md.brain/raw/04_missing_baselines.md- All
.brain/raw/05_qa_<slug>.mdfiles (one per active criterion)
Output
Write exactly one file: .brain/review/final_review.md. The structure is dictated by 00_review_guidelines.md. If using the generic fallback, structure as:
# Review — <paper title>
## Summary
<2-3 paragraph précis of the paper's contribution. Sourced from `01_structured_summary.md`.>
## Strengths
- <bullet, grounded in structured summary OR Q&A consensus>
- <...>
## Weaknesses
- <bullet, with explicit reference to a [DISCREPANCY] flag from a Q&A file or a high-severity entry from `04_missing_baselines.md`>
- <...>
## Detailed comments per criterion
### Novelty & Originality
<Synthesis from `05_qa_novelty.md`. Cite specific Q&A pairs.>
### Technical Soundness
<Synthesis from `05_qa_technical-soundness.md`.>
### Clarity & Presentation
<...>
### Significance & Impact
<...>
### Reproducibility
<...>
(One section per criterion in `session.json.qa_criteria[]` — adapt to the venue's actual list.)
## Questions for authors
1. <Question raised during Q&A that remains unresolved or warrants clarification>
2. <...>
3. <3-5 questions total>
## Decision recommendation
<Accept / Weak Accept / Borderline / Weak Reject / Reject>
**Justification:** <One paragraph grounding the decision in the strengths/weaknesses above.>
## Confidence
<1-5 scale>
**Rationale:** <One sentence on confidence, e.g. "Confidence 4: domain narrative was well-covered but reproducibility claims could not be fully verified without code access.">
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.
- 13d ago First seen · 104 lines · 70 tokens per session scan A b8c443c0b047
osp-reviewer-agent is a skill published in the GitHub repository amirkiarafiei/open-scholar-peer (28 stars, last pushed yesterday), licensed MIT. It adds 70 tokens to every session and 980 once invoked, about $0.0003 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.
Other skills, from other repositories
ara-rigor-reviewer
Performs ARA Seal Level 2 semantic epistemic review on Agent-Native Research Artifacts, scoring six dimensions (evidence relevance, falsifiability, scope calibration, argument coherence, exploration integrity, methodological rigor) and producing a constructive, severity-ranked report with a Strong Accept-to-Reject…
academic-paper
12-agent academic paper writing pipeline. 11 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure/rebuttal-audit). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns…
academic-pipeline
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory, coverage-bounded…
academic-paper-reviewer
Multi-perspective academic paper review with dynamic reviewer personas. Runs a 5-seat, role-separated review panel (Journal-Fit Reviewer + 3 peer-review roles + Devil's Advocate) with field-specific expertise; role separation is not a claim of independent error processes. Supports full review, re-review…
deep-research
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 8 modes: full research, quick brief, paper review, lit-review, fact-check, three-way literature scan, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question…
novelty-duplication-advisory
MEMO-ONLY prior-work overlap advisory: surfaces the two ADVISORY taxonomy signals neither a tool nor a model can decide from the paper alone — ADV-TRIVIAL-COMBINATION (standard A+B+C / 缝合 stapling) and ADV-DUPLICATE-PUBLICATION (repackaged / duplicate submission). The executor RETRIEVES candidate prior work (DBLP…