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 Agentic-Assets/corbis-literature-starter-kit --skill literature-reviewgit clone --depth 1 https://github.com/Agentic-Assets/corbis-literature-starter-kitWrote 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/agentic-assets/corbis-literature-starter-kit/literature-review)<a href="https://agentmods.dev/skills/agentic-assets/corbis-literature-starter-kit/literature-review"><img src="https://agentmods.dev/badge/skills/agentic-assets/corbis-literature-starter-kit/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/agentic-assets/corbis-literature-starter-kit/literature-review"><img src="https://agentmods.dev/badge/skills/agentic-assets/corbis-literature-starter-kit/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 | $0.00060 | $0.04389 |
| Opus 5 | $0.00030 | $0.02194 |
| Sonnet 5 | $0.00012 | $0.00878 |
| Haiku 4.5 | $0.00006 | $0.00439 |
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 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 — 344 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature Review
Write a comprehensive, structured literature review on a user-specified topic. This skill produces a standalone review of what the field knows, where it disagrees, and what remains open. It is not for positioning a specific paper's contribution (use literature-positioning-map for that) or for writing a related-literature section within a manuscript (use research-paper-writer for that).
When to use
- The user wants to survey a topic or research area
- The user wants a literature review for a dissertation chapter, qualifying exam, survey paper, or personal reference
- The user wants to understand the state of knowledge on a question before starting a project
Inputs to collect
Before starting, confirm these with the user:
| Input | Required? | Default |
|---|---|---|
| Topic or research question | Yes | — |
Output format: markdown / latex-section / latex-standalone |
Yes | markdown |
Scope: quick (~15 papers, field orientation) / focused (~25 papers) / comprehensive (~50 papers) |
No | comprehensive |
Target .tex file (if latex-section) |
If applicable | — |
Existing .bib file path |
No | Auto-detect or create new |
| Known key papers to include | No | — |
| Time period filter | No | All years |
| Specific journals to emphasize | No | — |
If the user provides a topic and format in their initial message, proceed without asking. Fill defaults for anything not specified.
Workflow
Phase 0 (quick scope only): Field Orientation
If scope is quick, skip the full review workflow. Instead:
- Run the architecture search (
sortBy: "citedByCount",matchCount: 15) and frontier search (minYear: 2020,matchCount: 15). - Use
get_paper_details_batchon the top 10 results from the architecture search. - Produce a field orientation document at
output/field_orientation.md:
# Field Orientation: [Topic]
## 10 Must-Read Papers
[Ranked by citation count. For each: author (year), title, journal, 1-sentence contribution.]
## 3 Main Debates
[What the field disagrees about, with papers on each side.]
## 3 Dominant Methods
[How this field typically does empirical work.]
## 3 Common Datasets
[What data most papers use, via search_datasets.]
## 5 Frontier Questions
[What the recent papers (2020+) are working on that remains unresolved.]
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.
- 12d ago First seen · 344 lines · 60 tokens per session scan A 23020b27168c
literature-review is a skill published in the GitHub repository Agentic-Assets/corbis-literature-starter-kit (11 stars, last pushed 4mo ago), licensed MIT. It adds 60 tokens to every session and 4,389 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.
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