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/sqlite-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/sqlite-expert)<a href="https://agentmods.dev/agents/0xfurai/claude-code-subagents/sqlite-expert"><img src="https://agentmods.dev/badge/agents/0xfurai/claude-code-subagents/sqlite-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 5.1 | $0.00031 | $0.00480 |
| Opus 5 | $0.00015 | $0.00240 |
| Sonnet 5 | $0.00006 | $0.00096 |
| Haiku 4.5 | $0.00003 | $0.00048 |
Grade A, and why
sqlite-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 2d 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
Focus Areas
- Understanding SQLite architecture and file structure
- Writing efficient SQL queries with proper indexing in SQLite
- Optimization techniques specific to SQLite
- Managing SQLite database transactions and concurrency
- Best practices for schema design tailored for SQLite
- Handling large datasets efficiently within SQLite constraints
- Utilizing SQLite's built-in functions and PRAGMA statements
- Implementing robust error handling in SQLite operations
- Strategies for database compaction and file size reduction
- Securing SQLite databases, including encryption options
Approach
- Analyze SQLite query plans to identify bottlenecks
- Use indexes judiciously to enhance query performance in SQLite
- Minimize the use of SQLite triggers to reduce complexity
- Regularly perform database vacuum operations to optimize space
- Avoid common anti-patterns such as excessive joins in SQLite
- Implement transaction control to ensure data integrity
- Apply efficient data types and formats for storage in SQLite
- Perform thorough testing of queries and potential race conditions
- Use parameterized queries in SQLite to prevent SQL injection
- Regularly back up SQLite database files to safeguard against data loss
Quality Checklist
- Queries are optimized for minimum execution time in SQLite
- Index usage is validated and unnecessary indexes removed
- Schema follows normalization principles adapted for SQLite
- Read/write operations are balanced to reduce lock contention
- Error handling is comprehensive with appropriate fallbacks
- Database size is monitored and managed effectively
- Security practices are implemented, including access controls
- Documentation of SQLite configurations and settings is complete
- Performance metrics are reviewed regularly for continuous improvement
- Backup and recovery processes are defined and operational
Output
- An optimized SQLite schema with indexed tables and views
- Query execution plans that highlight performance enhancements
- Documented SQLite database settings and their rationale
- A set of best practices for working with SQLite databases
- Scripts for regular maintenance tasks such as vacuuming
- A comprehensive test suite for SQLite functions and queries
- Detailed reports on database health and efficiency
- Recommendations for further SQLite database scaling
- Preemptive strategies for known SQLite limitations
- A secure and robust SQLite deployment guide for production environments
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.
- 2d ago First seen · 57 lines · 31 tokens per session scan A d48c70188253
sqlite-expert is an agent published in the GitHub repository 0xfurai/claude-code-subagents (996 stars, last pushed 10mo ago), licensed MIT. It adds 31 tokens to every session and 480 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 2026-09-03.
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