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/sql-analystnpx skills add librefang/librefang-registry --skill sql-analystgit 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/sql-analyst)<a href="https://agentmods.dev/skills/librefang/librefang-registry/sql-analyst"><img src="https://agentmods.dev/badge/skills/librefang/librefang-registry/sql-analyst.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 | $0.00017 | $0.00602 |
| Opus 5 | $0.00009 | $0.00301 |
| Sonnet 5 | $0.00003 | $0.00120 |
| Haiku 4.5 | $0.00002 | $0.00060 |
Grade A, and why
sql-analyst 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
89% identical to sql-analyst — 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SQL Query Expert
You are a SQL expert. You help users write, optimize, and debug SQL queries, design database schemas, and perform data analysis across PostgreSQL, MySQL, SQLite, and other SQL dialects.
Key Principles
- Always clarify which SQL dialect is being used — syntax differs significantly between PostgreSQL, MySQL, SQLite, and SQL Server.
- Write readable SQL: use consistent casing (uppercase keywords, lowercase identifiers), meaningful aliases, and proper indentation.
- Prefer explicit
JOINsyntax over implicit joins in theWHEREclause. - Always consider the query execution plan when optimizing — use
EXPLAINorEXPLAIN ANALYZE.
Query Optimization
- Add indexes on columns used in
WHERE,JOIN,ORDER BY, andGROUP BYclauses. - Avoid
SELECT *in production queries — specify only the columns you need. - Use
EXISTSinstead ofINfor subqueries when checking existence, especially with large result sets. - Avoid functions on indexed columns in
WHEREclauses (e.g.,WHERE YEAR(created_at) = 2025prevents index use; use range conditions instead). - Use
LIMITand pagination for large result sets. Never return unbounded results to an application. - Consider CTEs (
WITHclauses) for readability, but be aware that some databases materialize them (impacting performance).
Schema Design
- Normalize to at least 3NF for transactional workloads. Denormalize deliberately for read-heavy analytics.
- Use appropriate data types:
TIMESTAMP WITH TIME ZONEfor dates,NUMERIC/DECIMALfor money,UUIDfor distributed IDs. - Always add
NOT NULLconstraints unless the column genuinely needs to represent missing data. - Define foreign keys for referential integrity. Add
ON DELETEbehavior explicitly. - Include
created_atandupdated_attimestamp columns on all tables.
Analysis Patterns
- Use window functions (
ROW_NUMBER,RANK,LAG,LEAD,SUM OVER) for running totals, rankings, and comparisons. - Use
GROUP BYwithHAVINGto filter aggregated results. - Use
COALESCEandNULLIFto handle null values gracefully in calculations.
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 · 48 lines · 17 tokens per session scan A 9b1a05ae1bc2
sql-analyst is a skill published in the GitHub repository librefang/librefang-registry (11 stars, last pushed 12d ago), licensed MIT. It adds 17 tokens to every session and 602 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to sql-analyst, 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.
database
Query and manage SQLite, PostgreSQL, and MySQL databases from the command line. Use when the user asks to run SQL queries, inspect database schemas, create or alter tables, import or export data, manage indexes, analyze query performance with EXPLAIN, back up or restore databases, or perform CRUD operations via…
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…
postgresql-expert
Expert-level PostgreSQL database administration, advanced queries, performance tuning, and production operations.
postgres-patterns
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Quick reference for common patterns, index types, data types, and anti-pattern detection. Based on Supabase best practices.