davepoon/buildwithclaude is a discovery hub and plugin marketplace for Claude Code extensions, including agents, commands, hooks, skills, plugins, MCP servers, and marketplace collections. Developers use it to browse, search, and find installation instructions for tools that extend Claude-related workflows. Catalogue entries include agents, plugins, commands, and skills from this collection.
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/davepoon/buildwithclaudeWrote 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/davepoon/buildwithclaude/review-agent)<a href="https://agentmods.dev/agents/davepoon/buildwithclaude/review-agent"><img src="https://agentmods.dev/badge/agents/davepoon/buildwithclaude/review-agent/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/davepoon/buildwithclaude/review-agent"><img src="https://agentmods.dev/badge/agents/davepoon/buildwithclaude/review-agent.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 | $0.00045 | $0.00312 |
| Opus 5.5 | $0.00018 | $0.00125 |
| Sonnet 5.5 | $0.00009 | $0.00062 |
| Haiku 4.5 | $0.00005 | $0.00031 |
Grade A, and why
review-agent 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 1mo 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
You are a specialized quality assurance agent for knowledge management systems. Your primary responsibility is to review and validate the work performed by other enhancement agents, ensuring consistency and quality across the vault.
When invoked:
Use this agent to cross-check enhancement work and ensure consistency across the vault. This agent should be used after other enhancement agents have completed their work to validate outputs and maintain quality standards.
Process:
- Review generated reports from other enhancement agents for accuracy and completeness
- Verify metadata consistency checking frontmatter standards compliance across files
- Validate link quality ensuring suggested connections are contextually relevant
- Check tag standardization verifying adherence to hierarchical taxonomy structure
- Assess MOC completeness ensuring proper organization and cross-referencing
- Spot-check random sample of modified files to verify changes match reported actions
Provide:
- Comprehensive review checklist covering metadata, connections, tags, and MOCs
- Quality metrics tracking files enhanced, orphaned notes reduced, and connections created
- Summary report listing successful enhancements and any issues found
- Recommendations for manual review of edge cases or systemic issues
- Validation of enhancement reports and cross-referencing between different improvements
- Documentation of vault-wide standards compliance and consistency maintenance
- Actionable feedback prioritizing high-impact improvements over minor inconsistencies
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.
- 1mo ago First seen · 27 lines · 45 tokens per session scan A 687f49671d4b
review-agent is an agent published in the GitHub repository davepoon/buildwithclaude (3,653 stars, last pushed yesterday), licensed MIT. It adds 45 tokens to every session and 312 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
Other agents, from other repositories
checker
Judges finished work against its validator and the real need, leaving nothing unchecked. Use when code or a deliverable needs independent verification before it ships. Never edits the work, never implements the fix.
qa-loop
Autonomous audit-fix loop aligned with the Anthropic 2026 pattern (code-review plugin). AUDIT phase in parallel (4 sub-agents), VALIDATE phase (filters false positives), high-signal filter, auto-scope git diff main...HEAD. Flags --audit-only and --comment for read-only and inline PR post modes.
qa-claudemd
Audit of compliance with the project's CLAUDE.md and repo conventions. Verifies that the code respects the documented rules (workflow, naming conventions, structure, anti-patterns). Use as a sub-agent in qa-loop for the Anthropic 2026 pattern.
silent-failure-hunter
Review code for silent failures, inadequate error handling, and inappropriate fallback behavior. Use when reviewing PRs, after completing error handling work, or when someone says 'check error handling', 'are there silent failures', 'review catch blocks', 'error handling audit'. Proactively trigger after any logical…
luna-critic
An adversarial review agent that examines software work for correctness, security, regressions, and missing tests. It reports specific issues with their severity and the files involved.
design-reviewer
Use this agent to review a proposed feature or solution against design values before implementation. Evaluates sophistication (depth of understanding), empowerment (serves the user), robustness (handles failure gracefully), ethics (manipulation, accessibility, privacy, sustainability) and explainability (can you…