Borrowing it
Nothing to install: this file belongs to omar-A-hassan/medsci-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/omar-A-hassan/medsci-agent/main/.opencode/skills/literature-review/SKILL.mdgit clone --depth 1 https://github.com/omar-A-hassan/medsci-agentWrote 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/omar-a-hassan/medsci-agent/literature-review)<a href="https://agentmods.dev/skills/omar-a-hassan/medsci-agent/literature-review"><img src="https://agentmods.dev/badge/skills/omar-a-hassan/medsci-agent/literature-review/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/omar-a-hassan/medsci-agent/literature-review"><img src="https://agentmods.dev/badge/skills/omar-a-hassan/medsci-agent/literature-review.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 | $0.00018 | $0.00496 |
| Opus 5.5 | $0.00007 | $0.00198 |
| Sonnet 5.5 | $0.00004 | $0.00099 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
literature-review 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 2mo 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.
What it actually says
Systematic Literature Review
Overview
A systematic review follows a structured, reproducible methodology to identify, evaluate, and synthesize all relevant evidence on a research question. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) provides the reporting standard.
Search Strategy
- Define PICO: Population, Intervention, Comparison, Outcome.
- Build search query: Combine MeSH terms and free-text with Boolean operators.
- Select databases: PubMed, Scopus, Web of Science, Cochrane, Embase.
- Document everything: Record date, database, exact query, and result count.
PubMed Query Example
("breast cancer"[MeSH] OR "breast neoplasms"[tiab])
AND ("immunotherapy"[MeSH] OR "checkpoint inhibitor"[tiab])
AND ("overall survival"[tiab] OR "progression-free survival"[tiab])
Programmatic PubMed Access
from Bio import Entrez
Entrez.email = "[email protected]"
handle = Entrez.esearch(db="pubmed", term="CRISPR AND cancer", retmax=100)
record = Entrez.read(handle)
pmids = record["IdList"]
handle = Entrez.efetch(db="pubmed", id=pmids[:10], rettype="xml")
records = Entrez.read(handle)
PRISMA Flow
- Identification: Total records from all databases.
- Screening: Remove duplicates, screen titles/abstracts.
- Eligibility: Full-text review against inclusion/exclusion criteria.
- Included: Final studies for qualitative/quantitative synthesis.
Key Details
- Register protocol on PROSPERO before starting.
- Use reference managers (Zotero, EndNote) for deduplication.
- Risk of bias: use Cochrane RoB 2 (RCTs) or ROBINS-I (observational).
- For meta-analysis, extract effect sizes (OR, HR, SMD) with confidence intervals.
- Report PRISMA 2020 checklist and flow diagram in final publication.
- Screening tools: Rayyan, ASReview (AI-assisted), Covidence.
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.
- 2mo ago First seen · 50 lines · 18 tokens per session scan A 953b636d737e
literature-review is a skill published in the GitHub repository omar-A-hassan/medsci-agent (17 stars, last pushed 2mo ago), licensed MIT. It adds 18 tokens to every session and 496 once invoked, about $0.0001 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 2026-08-30.
literature-review compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| literature-reviewomar-A-hassan/medsci-agent | Skill | 17 | 2mo ago | MIT | A | 18 | OpenCode |
| build-expression-treejimmc414/claude-code-plugin-marketplace | Skill | 4 | yesterday | MIT | A | 24 | Claude Code |
| find-convex-hulljimmc414/claude-code-plugin-marketplace | Skill | 4 | yesterday | MIT | A | 31 | Claude Code |
| dfam-checkearthtojake/text-to-cad | Skill | 26k | yesterday | MIT | A | 117 | Claude Code, Codex |
| peer-reviewxintaofei/codeg | Skill | 4.2k | 6d ago | Apache-2.0 | A | 71 | Claude Code |
| scientific-critical-thinkingxintaofei/codeg | Skill | 4.2k | 6d ago | Apache-2.0 | A | 63 | Claude Code |
| tooluniverse-variant-analysismims-harvard/ToolUniverse | Skill | 1.8k | yesterday | Apache-2.0 | A | 317 | Claude Code |