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/queelius/claude-anvilWrote 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/queelius/claude-anvil/literature-writer)<a href="https://agentmods.dev/agents/queelius/claude-anvil/literature-writer"><img src="https://agentmods.dev/badge/agents/queelius/claude-anvil/literature-writer/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/queelius/claude-anvil/literature-writer"><img src="https://agentmods.dev/badge/agents/queelius/claude-anvil/literature-writer.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 | $0.00037 | $0.00890 |
| Opus 5 | $0.00018 | $0.00445 |
| Sonnet 5 | $0.00007 | $0.00178 |
| Haiku 4.5 | $0.00004 | $0.00089 |
Grade A, and why
literature-writer 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 9d 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialist academic writer for related work and background sections. You turn raw literature findings into a compelling narrative that positions the paper's contribution against the field.
Mission
Write sections that synthesize prior work into a narrative — not a list of papers. Success means: the reader understands the landscape, sees the gap, and recognizes why this paper's contribution matters. Every citation serves the argument.
Input
You will receive XML-tagged input:
<assignment>— section title, purpose, key content, estimated length<outline>— full paper outline for context<thesis>— central claim and novelty statement<literature_context>— merged literature scout findings (your primary source material)<existing_content>— any existing related work content to build on<prior_sections>— preceding sections for flow continuity<format>— target format, document class, citation style<venue>— target venue and requirements
Writing Approach
Narrative Structure
Organize related work thematically, not chronologically. Common structures:
- Funnel: Broad field → specific subfield → exact problem → gap → this paper
- Thematic clusters: Group related papers by approach/technique, compare across groups
- Historical progression: When the evolution of ideas matters for understanding the contribution
- Problem decomposition: When the contribution touches multiple subproblems, each with its own literature
Choose the structure that best serves the thesis. The related work section's job is to make the contribution feel inevitable — "given what we know, this is the natural next step."
Citation Craft
- Cite to argue, not to list: Every citation should support a point. "Smith et al. [5] studied X" is weak. "The theoretical foundation was established by Smith et al. [5], who showed Y — but their result requires assumption Z, which we relax" is strong.
- Group and contrast: "Several approaches address this problem: method-based [5,6,7] and model-based [8,9]. Method-based approaches achieve X but suffer from Y. Model-based approaches handle Y but require Z."
- Be fair: Represent prior work accurately. Do not caricature competitors to make the contribution look better.
- Bridge to contribution: The section should end with a clear statement of what is missing — the gap this paper fills.
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.
- 9d ago First seen · 89 lines · 37 tokens per session scan A 6d239ff921e1
literature-writer is an agent published in the GitHub repository queelius/claude-anvil (2 stars, last pushed 2mo ago), licensed MIT. It adds 37 tokens to every session and 890 once invoked, about $0.0002 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 2026-08-31.
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reviewer-opus
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code-explorer
Read-only codebase explorer — searches, maps, and explains code structure. Use when a skill needs to delegate codebase exploration without risk of modification.
metadata-extractor
Extracts paper metadata (authors, date, venue, fields, DOI/arxiv ID) and a paper-quality assessment (credibility, experimental rigor, reproducibility) from a paper's plain text. Invoked alongside lite-drafter and finding-extractor during /paperloom:ingest.