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 skills/librefang/librefang-registry/sqlite-expertnpx skills add librefang/librefang-registry --skill sqlite-expertgit clone --depth 1 https://github.com/librefang/librefang-registryWrote 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/skills/librefang/librefang-registry/sqlite-expert)<a href="https://agentmods.dev/skills/librefang/librefang-registry/sqlite-expert"><img src="https://agentmods.dev/badge/skills/librefang/librefang-registry/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 | $0.00019 | $0.00712 |
| Opus 5 | $0.00010 | $0.00356 |
| Sonnet 5 | $0.00004 | $0.00142 |
| Haiku 4.5 | $0.00002 | $0.00071 |
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.
This is a copy
98% identical to sqlite-expert — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SQLite Expert
A database specialist with deep expertise in SQLite internals, performance tuning, and embedded database patterns. This skill provides guidance for using SQLite effectively in applications ranging from mobile apps and IoT devices to server-side caching layers and analytical workloads, leveraging its advanced features well beyond simple key-value storage.
Key Principles
- Enable WAL mode (PRAGMA journal_mode=WAL) for concurrent read/write access; it allows readers to proceed without blocking writers and vice versa
- Use PRAGMA busy_timeout to set a reasonable wait duration (e.g., 5000ms) instead of receiving SQLITE_BUSY errors immediately on contention
- Design schemas with appropriate indexes from the start; SQLite's query planner relies heavily on index availability for efficient execution plans
- Keep transactions short and explicit; wrap related writes in BEGIN/COMMIT to ensure atomicity and reduce fsync overhead
- Understand that SQLite is serverless and single-file; its strength is simplicity and reliability, not high-concurrency multi-writer workloads
Techniques
- Set performance PRAGMAs at connection open: journal_mode=WAL, synchronous=NORMAL, cache_size=-64000 (64MB), mmap_size=268435456, temp_store=MEMORY
- Use FTS5 for full-text search: CREATE VIRTUAL TABLE docs USING fts5(title, body) with MATCH queries and bm25() ranking
- Query JSON data with the JSON1 extension: json_extract(), json_each(), json_group_array() for document-style data stored in TEXT columns
- Write recursive CTEs (WITH RECURSIVE) for tree traversal, graph walking, and generating series of values
- Use window functions (ROW_NUMBER, LAG, LEAD, SUM OVER) for running totals, rankings, and time-series analysis without self-joins
- Create covering indexes that include all columns needed by a query to enable index-only scans (verified with EXPLAIN QUERY PLAN showing COVERING INDEX)
- Implement UPSERT with INSERT ... ON CONFLICT (column) DO UPDATE SET for atomic insert-or-update operations
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 · 43 lines · 19 tokens per session scan A db4ca7a0d15c
sqlite-expert is a skill published in the GitHub repository librefang/librefang-registry (11 stars, last pushed 12d ago), licensed MIT. It adds 19 tokens to every session and 712 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to sqlite-expert, differing in 3 lines, and is treated as a copy.
Other skills, from other repositories
postgresql-expert
Expert-level PostgreSQL database administration, advanced queries, performance tuning, and production operations. Use when the user mentions database, SQL, or performance, or when the task involves Advanced Data Types, Full-Text Search, Advanced Indexes, or Advanced Queries.
sql-expert
Expert-level SQL database design, querying, optimization, and administration across PostgreSQL, MySQL, and SQL Server. Use when the user mentions database, PostgreSQL, MySQL, or query optimization, or when the task involves Database Design, Advanced Queries, Indexes and Performance, or Transactions and Concurrency.
snowflake-expert
Expert-level Snowflake data warehouse platform, virtual warehouses, data sharing, streams, tasks, and SQL optimization. Use when the user mentions data warehouse, SQL, analytics, or cloud, or when the task involves Architecture and Virtual Warehouses, Database Objects and Organization, Data Loading and Stages, or…
review-prs
Review a GitHub pull request in the googleapis/mcp-toolbox repo against the team's reviewer checklist: PR title/description conventions, linked issue, logic errors and unhandled edge cases, breaking changes, test coverage, docs updates, security (input handling), and new dependencies. Use whenever a maintainer asks…
stale-sweep
Sweep the googleapis/mcp-toolbox repo for issues and PRs with no real activity in N days (default 60), sort each by whose silence it is (the author's, ours, or nobody's), and draft the nudge or close comment. Use whenever a maintainer asks for a stale sweep, backlog cleanup, or an SLO check, e.g. "stale sweep", "find…
triage-issues
Triage GitHub issues in the googleapis/mcp-toolbox repo: propose the correct labels (type / priority / product / status), check for duplicates, verify a bug has enough info to act on, and draft a triage comment. Use whenever a maintainer asks you to triage, label, categorize, prioritize, or "look at" an issue (or a…