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/commands/galaxy-dawn/claude-scholar/promote)<a href="https://agentmods.dev/commands/galaxy-dawn/claude-scholar/promote"><img src="https://agentmods.dev/badge/commands/galaxy-dawn/claude-scholar/promote/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/commands/galaxy-dawn/claude-scholar/promote"><img src="https://agentmods.dev/badge/commands/galaxy-dawn/claude-scholar/promote.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 | $0.00013 | $0.00295 |
| Opus 5 | $0.00006 | $0.00148 |
| Sonnet 5 | $0.00003 | $0.00059 |
| Haiku 4.5 | $0.00001 | $0.00030 |
Grade A, and why
promote 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 10d 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
Generate Promotion Content
Use the post-acceptance skill to prepare accurate promotion content for an
accepted paper.
Workflow
- Ask for the paper, acceptance venue, public links, key result, and target platforms.
- Separate claims supported by the paper from broader promotional language.
- Draft platform-specific content for X, LinkedIn, blogs, or news pages.
- Check names, links, numbers, image rights, and accessibility text.
- Return editable drafts before offering any publishing step.
Optional Xquik workflow
Use Xquik only when the user asks for live X context, draft analysis, or
publishing. Load references/xquik-promotion.md from the post-acceptance
skill before using it.
- Keep public searches bounded by query, dates, and result count.
- Treat posts as public context, not scholarly evidence.
- Draft locally when Xquik MCP is unavailable.
- Show the complete account, text, links, media, and public effect before a write.
- Publish only after explicit approval for that exact payload.
- Never retry a write automatically.
Delivery
Return each draft under its target platform. Include a short fact-check list and any unresolved placeholders. If an approved X post succeeds, return its action status and public URL when available.
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.
- 10d ago First seen · 39 lines · 13 tokens per session scan A c950a272f91b
promote is a command published in the GitHub repository Galaxy-Dawn/claude-scholar (5,407 stars, last pushed 13d ago), licensed MIT. It adds 13 tokens to every session and 295 once invoked, about $0.0001 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.
Other commands, from other repositories
rb-ask
A command for asking questions about the current codebase through RepoBrain, a code knowledge tool.
rb-refresh
A command that rebuilds RepoBrain's knowledge base for the current workspace. RepoBrain is a tool that keeps searchable project information for an agent.
pr-review
Generate a PR review report aggregating quality scan, coverage, complexity, and breaking changes.
task
Start TASK phase — task decomposition.
fix
User-triggered workflow to automatically fix open issues.
brainstorm
Pre-implementation collaborative requirement exploration and design (conversational brainstorm).