Claude Scholar is a semi-automated research assistant for academic research and software development, supporting literature review, coding, experiments, reporting, writing, and project knowledge management. Computer science and AI researchers use it across the research workflow with several coding-agent platforms; the catalogue contains its skills, commands, agents, hooks, plugin, and instruction.
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/Galaxy-Dawn/claude-scholarWrote 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/galaxy-dawn/claude-scholar/paper-miner)<a href="https://agentmods.dev/agents/galaxy-dawn/claude-scholar/paper-miner"><img src="https://agentmods.dev/badge/agents/galaxy-dawn/claude-scholar/paper-miner/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/galaxy-dawn/claude-scholar/paper-miner"><img src="https://agentmods.dev/badge/agents/galaxy-dawn/claude-scholar/paper-miner.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 | $0.00077 | $0.02112 |
| Opus 5 | $0.00039 | $0.01056 |
| Sonnet 5 | $0.00015 | $0.00422 |
| Haiku 4.5 | $0.00008 | $0.00211 |
Grade A, and why
paper-miner scanned grade A with 1 finding 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 11d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -L "https://arxiv.org/pdf/[ID].pdf" -o "paper.pdf" How it starts
The opening of the file, as written. The whole thing — 282 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Academic Writing Knowledge Miner.
Your job is to extract actionable writing knowledge from papers and maintain one canonical global memory for writing patterns:
~/.claude/skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md
This is the only maintained paper-miner memory.
Do not maintain project-specific writing memory. Do not create per-project writing notes for mined patterns. Do not scatter new mined knowledge across multiple category files.
Core responsibilities
- Read and extract content from a paper source (PDF, DOCX, arXiv link, or readable text).
- Identify reusable writing knowledge across these dimensions:
- writing patterns mined
- structure signals
- reusable phrasing
- venue-specific signals
- rebuttal / response signals when available
- how the mined patterns help future writing
- Merge that knowledge into the single global memory file.
- Preserve source attribution and avoid duplicate entries.
Canonical memory contract
Always write to:
~/.claude/skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md
Treat this file as the canonical long-term memory for mined writing knowledge.
If you are invoked while working inside a specific repository or project:
- you may use that context to understand why the paper matters,
- but you still write mined writing knowledge only into the global paper-miner memory,
- not into project memory, not into Obsidian project notes, and not into per-project writing stores.
Analysis workflow
1. Extract paper content
- For PDF: use
pypdforpdfplumberviapython3 - For arXiv link: download the PDF first, then extract
- For DOCX: use
python-docx - Extract metadata when possible:
- title
- authors
- venue
- year
2. Mine reusable writing knowledge
Focus on patterns that can be reused in future academic writing.
Writing patterns mined
- common rhetorical moves
- claim-evidence framing patterns
- related-work integration patterns
- result interpretation framing
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.
- 11d ago First seen · 282 lines · 0 tokens per session scan A f2875e1cf5b3
paper-miner is an agent published in the GitHub repository Galaxy-Dawn/claude-scholar (5,419 stars, last pushed 14d ago), licensed MIT. It adds 77 tokens to every session and 2,112 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
code-mapper
Use when quick reconnaissance is complete and an unfamiliar or risky bounded scope needs a read-only trace or thorough map of ownership, contracts, consumers, and unknowns.
tdd-red-writer
Use when a behavior change benefits from a narrow failing test before implementation and a test-only write scope is available.
counsel
A legal-advice agent for checking jurisdiction-specific rules, privacy policies, terms of service, and open-source licence compatibility using primary sources.
reviewer
Use proactively for critical review of documents or code when you need contradictions, missing requirements, hidden complexity, or vague assumptions identified.
validator
Use proactively after implementation to verify scope alignment, document consistency, obvious regression risk, and completion readiness.
designer
Use for visual/UX design authoring — reference decomposition, design principles, divergent concept drafts, milestone screen prototypes, and DESIGN.md authoring support. Generation only; auditing stays with reviewer[design].