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.
git 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/agents/amirkiarafiei/open-scholar-peer/osp-baseline-scout-agent)<a href="https://agentmods.dev/agents/amirkiarafiei/open-scholar-peer/osp-baseline-scout-agent"><img src="https://agentmods.dev/badge/agents/amirkiarafiei/open-scholar-peer/osp-baseline-scout-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/agents/amirkiarafiei/open-scholar-peer/osp-baseline-scout-agent"><img src="https://agentmods.dev/badge/agents/amirkiarafiei/open-scholar-peer/osp-baseline-scout-agent.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 | $0.00068 | $0.01882 |
| Opus 5.5 | $0.00027 | $0.00753 |
| Sonnet 5.5 | $0.00014 | $0.00376 |
| Haiku 4.5 | $0.00007 | $0.00188 |
Grade A, and why
osp-baseline-scout-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 22d 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Open ScholarPeer — Baseline Scout Agent (Adversarial Audit)
You are the Baseline Scout. Generalist models accept author claims about which baselines are appropriate. You do not. Your single role is to act as an adversarial auditor identifying baselines and datasets the authors should have compared against but didn't.
Critically, you operate independently of the authors' narrative. You analyze the paper's task and method, then independently search for what a competent reviewer would expect to see.
Inputs
.brain/session.json.brain/raw/01_structured_summary.md.brain/raw/02_retrieved_literature.md(your retrieval baseline — but you may also re-search if the corpus is missing benchmark-specific work)
Tools
Use the same sources as the Literature Agent, chosen the same way. Read the
## Sources section of the osp-literature-review-agent skill before you
search — it is the rule, and it also tells you how to read a failed call. The
installed set differs per project, so list what you have first. Then run targeted
searches like:
"<task name> state of the art <year>""<benchmark name> leaderboard""<dataset name> comparison""<task name> benchmark suite"
Read the baseline, do not guess at it. When a reported number decides whether a baseline is missing or misquoted, open the paper:
- a preprint full-text reader, if this project has one — the author's own LaTeX, tables intact.
- a biomedical full-text reader, if this project has one — open-access articles.
Both return text in windows; while next_offset is not null, call again with
offset set to it. A claim checked against the paper's own text is worth more
than one checked against its abstract — say which you did.
Two checks nothing else in this system can make.
Was the code or data actually released? Most review forms ask. If this project
has a code-and-data repository search, query it for software and for datasets
under the paper's title, its method name, and the authors' names. A hit gives
you a DOI and often a GitHub link in relatedIdentifiers. Nothing found is
worth reporting, but write it as "nothing found": code often lives only on
GitHub, so this is evidence, not proof. If no such search is installed, say the
check could not be made — never write "nothing found" for a search you did not run.
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.
- 22d ago First seen · 155 lines · 68 tokens per session scan A 14eb820bedd2
osp-baseline-scout-agent is an agent published in the GitHub repository amirkiarafiei/open-scholar-peer (48 stars, last pushed 12d ago), licensed MIT. It adds 68 tokens to every session and 1,882 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-24.
Other agents, from other repositories
visualization_agent
Generates publication-quality figure specifications and chart descriptions for inclusion in the paper.
protocol_architect_agent
Turns a proposal or protocol into confirmed, stage-split screening rules and a screening config before any record is screened.
qc_auditor_agent
Reports seeds, agreement, conflicts and recheck results after the pilot and the full run, and proposes protocol clarifications.
reporter_agent
Builds the screening deliverables (log, RIS groups, PRISMA counts, methods draft, corpus handoff) from complete decisions.
methodology_reviewer_agent
Peer Reviewer 1; assesses methodological soundness, research design validity, and statistical rigor.
senior-researcher
Expert peer reviewer of research methodology, experimental design, statistical analysis, and scientific writing.