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 LazyAGI/LazyMind --skill systematic-document-and-literature-reviewgit clone --depth 1 https://github.com/LazyAGI/LazyMindWrote 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/lazyagi/lazymind/systematic-document-and-literature-review)<a href="https://agentmods.dev/skills/lazyagi/lazymind/systematic-document-and-literature-review"><img src="https://agentmods.dev/badge/skills/lazyagi/lazymind/systematic-document-and-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/lazyagi/lazymind/systematic-document-and-literature-review"><img src="https://agentmods.dev/badge/skills/lazyagi/lazymind/systematic-document-and-literature-review.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 | $0.00082 | $0.01094 |
| Opus 5 | $0.00041 | $0.00547 |
| Sonnet 5 | $0.00016 | $0.00219 |
| Haiku 4.5 | $0.00008 | $0.00109 |
Grade A, and why
systematic-document-and-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 12d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systematic Document & Literature Review Skill
Overview
This skill produces a structured systematic review and synthesis across multiple academic papers or general documents. Given a topic query or a list of specific files/URLs, it gathers the source material, analyzes the content (objectives, methodology, key findings, limitations) sequentially, synthesizes themes, and outputs a final structured report directly to the user.
Distinct from single-document review: This skill does breadth-first synthesis across many sources. If the user hands you exactly one document or one paper URL and asks "review this", route to a standard reading or single-document review skill instead.
When to Use This Skill
Use this skill when the user wants any of the following:
- A literature survey on an academic topic ("survey transformer attention variants")
- A thematic synthesis across internal documents ("synthesize the last 5 quarterly reports from the KB and find common trends")
- A cross-document comparison ("compare the methodologies across these provided architecture design URLs")
- An overview of trends across a set of files, URLs, or an arXiv time window
Do not use this skill when:
- The user provides exactly one document/paper and asks to review it.
- The user asks a factual question that does not require synthesizing multiple sources.
Workflow
The workflow has four phases. Follow them in order.
Phase 1: Plan
Before doing any retrieval, confirm the following with the user. If any of these are unclear, ask one clarifying question that covers the missing pieces.
- Source Material: Are we searching an academic database (
arxiv_search), an internal Knowledge Base (kb_search), or reviewing specific URLs (url_fetch)? - Scope: How many sources total? (Limit to max 15-20 sources to prevent context overflow).
- Output Format: APA, IEEE, BibTeX, or Standard Professional Report (default for non-academic documents).
Phase 2: Acquire Sources
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.
- 12d ago First seen · 100 lines · 82 tokens per session scan A 9b2b2b639323
systematic-document-and-literature-review is a skill published in the GitHub repository LazyAGI/LazyMind (77 stars, last pushed today), licensed Apache-2.0. It adds 82 tokens to every session and 1,094 once invoked, about $0.0004 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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