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/verify)<a href="https://agentmods.dev/commands/galaxy-dawn/claude-scholar/verify"><img src="https://agentmods.dev/badge/commands/galaxy-dawn/claude-scholar/verify.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00317 |
| Opus 5 | $0.00000 | $0.00159 |
| Sonnet 5 | $0.00000 | $0.00063 |
| Haiku 4.5 | $0.00000 | $0.00032 |
Grade A, and why
verify 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 8d 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
Verification Command
Run comprehensive verification on current codebase state.
Instructions
Execute verification in this exact order:
-
Type Check
- Run mypy src/
- Report all errors with file:line
-
Lint Check
- Run ruff check .
- Report warnings and errors
-
Test Suite
- Run pytest
- Report pass/fail count
- Report coverage percentage (pytest --cov)
-
Security Check
- Run pip-audit
- Check for hardcoded secrets (grep -r "sk-" etc.)
-
Print Audit
- Search for print() in source files
- Report locations
-
Git Status
- Show uncommitted changes
- Show files modified since last commit
Output
Produce a concise verification report:
VERIFICATION: [PASS/FAIL]
Types: [OK/X errors]
Lint: [OK/X issues]
Tests: [X/Y passed, Z% coverage]
Security: [OK/X vulnerabilities]
Secrets: [OK/X found]
Prints: [OK/X print() statements]
Ready for commit: [YES/NO]
If any critical issues, list them with fix suggestions.
Arguments
$ARGUMENTS can be:
quick- Only types + lintfull- All checks (default)pre-commit- Checks relevant for commitspre-pr- Full checks plus security scan
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.
- 8d ago First seen · 60 lines · 0 tokens per session scan A 7ac76472789e
verify is a command published in the GitHub repository Galaxy-Dawn/claude-scholar (5,349 stars, last pushed 11d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 317 tokens. 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
fix
User-triggered workflow to automatically fix open issues.
quality
Run full Fettle quality scan on the current project.
audit
Run comprehensive parallel audit — dispatches specialized agents by scope (frontend, backend, infra, security).
lint
Auto-detect and run project linters — supports Go, TypeScript, Python, Rust, and more.
pair
AI pair programming — switch between Driver, Navigator, TDD, Review, and Debug modes.
baseline
Manage violation baselines for gradual adoption.