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.
npx agentmods add agents/0xfurai/claude-code-subagents/dynamodb-expertgit clone --depth 1 https://github.com/0xfurai/claude-code-subagentsWrote 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/0xfurai/claude-code-subagents/dynamodb-expert)<a href="https://agentmods.dev/agents/0xfurai/claude-code-subagents/dynamodb-expert"><img src="https://agentmods.dev/badge/agents/0xfurai/claude-code-subagents/dynamodb-expert.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 | $0.00036 | $0.00471 |
| Opus 5 | $0.00018 | $0.00235 |
| Sonnet 5 | $0.00007 | $0.00094 |
| Haiku 4.5 | $0.00004 | $0.00047 |
Grade A, and why
dynamodb-expert 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 4d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Focus Areas
- Understanding the basics of DynamoDB architecture and operations
- Designing efficient and scalable DynamoDB tables
- Choosing the right partition and sort keys for query optimization
- Implementing secondary indexes for better query flexibility
- Optimizing read and write throughput for cost efficiency
- Leveraging DynamoDB Streams for real-time data processing
- Ensuring data consistency and integrity across distributed systems
- Managing item collections and avoiding hot partitions
- Implementing time-to-live (TTL) to minimize storage costs
- Utilizing AWS SDKs and CLI for interacting with DynamoDB
Approach
- Evaluate access patterns before designing the schema
- Prioritize single-table design for effective data retrieval
- Use sparse indexes to handle sparse datasets
- Monitor and assess capacity usage continuously
- Implement caching strategies to reduce duplicate reads
- Handle errors gracefully and implement retry logic
- Employ pagination for large dataset handling
- Use batch operations to improve throughput efficiency
- Regularly review and audit IAM roles and permissions
- Optimize for eventual consistency to reduce costs
Quality Checklist
- Ensure proper initialization and configuration of DynamoDB clients
- Verify table keys are chosen based on workload characteristics
- Confirm secondary indexes are serving intended query patterns
- Validate data types for compliance with schema requirements
- Check all tables have automatic scaling enabled for capacities
- Test throughput settings against anticipated load conditions
- Review item sizes to avoid exceeding DynamoDB limits
- Ensure all sensitive data is encrypted at rest and in transit
- Conduct regular backups and practice point-in-time recovery
- Review billing regularly to minimize unexpected cost spikes
Output
- Optimized DynamoDB schemas with clear documentation
- Provisioned tables with appropriate throughput configurations
- Reduced costs through efficient data access patterns
- Enhanced application performance with optimized queries
- Implemented disaster recovery and backup strategies
- Comprehensive monitoring and logging for troubleshooting
- Automatic data archiving using TTL for cost savings
- Timely batch processes enabled via DynamoDB Streams
- Secure access controls and data protection measures
- Regular optimization reports with recommendations
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.
- 4d ago First seen · 58 lines · 36 tokens per session scan A c837a90bb588
dynamodb-expert is an agent published in the GitHub repository 0xfurai/claude-code-subagents (995 stars, last pushed 10mo ago), licensed MIT. It adds 36 tokens to every session and 471 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 2026-08-30.
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