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 skills add nimadorostkar/Claude-Skills-collection --skill sqlgit clone --depth 1 https://github.com/nimadorostkar/Claude-Skills-collectionWrote 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/nimadorostkar/claude-skills-collection/sql)<a href="https://agentmods.dev/skills/nimadorostkar/claude-skills-collection/sql"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/sql/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/skills/nimadorostkar/claude-skills-collection/sql"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/sql.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00033 | $0.00912 |
| Opus 5 | $0.00016 | $0.00456 |
| Sonnet 5 | $0.00007 | $0.00182 |
| Haiku 4.5 | $0.00003 | $0.00091 |
Grade A, and why
sql 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 9d 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SQL
Purpose
Write SQL that the planner can execute efficiently, and read execution plans well enough to know why it did not.
When to Use
- Writing non-trivial queries: aggregations, window functions, recursive CTEs.
- Diagnosing a slow query.
- Designing indexes for a known access pattern.
- Choosing a transaction isolation level.
- Reviewing migrations for lock risk.
Capabilities
- Query authoring: joins, CTEs, window functions, lateral joins, upserts.
- Index design: composite ordering, covering indexes, partial indexes.
- Plan reading:
EXPLAIN (ANALYZE, BUFFERS)and the shapes that signal trouble. - Isolation levels and the anomalies each one permits.
- Safe migrations: concurrent index builds, backfills, lock avoidance.
Inputs
- The query, the schema, and the row counts of the tables involved.
- Existing indexes.
- The actual execution plan, not a guess about it.
Outputs
- A rewritten query, an index, or both — with a before/after plan.
- Migration statements that do not hold long locks.
Workflow
- Get the plan —
EXPLAIN (ANALYZE, BUFFERS). Never optimize a query you have not profiled. - Find the expensive node — Look for sequential scans on large tables, nested loops with high row counts, and estimates that diverge from actuals by an order of magnitude.
- Fix the cause — Bad estimate means stale statistics. Sequential scan on a selective filter means a missing index. High row counts through a join means the filter is applied too late.
- Index deliberately — Column order in a composite index is equality columns first, then the range or sort column.
- Re-measure — Confirm with a fresh plan, and check that write throughput did not regress.
Best Practices
- An index on
(a, b)serves queries filtering ona, and onaandb— but not onbalone. - Wrapping an indexed column in a function (
WHERE lower(email) = ...) disables the index unless the index is on the expression. SELECT *in application code prevents index-only scans and breaks when the schema changes.- Never run an unbounded
UPDATEorDELETEon a large table in one transaction — batch it. CREATE INDEX CONCURRENTLYin production; the plain form locks writes for the duration.- Prefer keyset pagination (
WHERE id > :last) overOFFSET— offset cost grows linearly with page depth.
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.
- 9d ago First seen · 97 lines · 33 tokens per session scan A 95cf27905161
sql is a skill published in the GitHub repository nimadorostkar/Claude-Skills-collection (26 stars, last pushed 25d ago), licensed MIT. It adds 33 tokens to every session and 912 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.
Other skills, from other repositories
offensive-sqli
SQL injection testing skill for offensive security assessments and bug bounty hunting. Covers error-based, UNION-based, boolean/time-based blind, out-of-band, second-order, NoSQL, GraphQL, WebSocket, and JSON-operator SQLi. Includes WAF bypass techniques, database-specific exploitation (MySQL, MSSQL, PostgreSQL…
database-security
Prevent SQL and NoSQL injection, unsafe ORM and raw-query use, over-privileged database identities, weak tenant isolation, and unauthenticated database transport. Use when generating SQL or raw query strings, NoSQL filters, ORM models or queries, database migration files, or connection strings.
go-database
Use when writing, reviewing, or debugging Go code that talks to a SQL database (PostgreSQL, MySQL, MariaDB, SQLite). Covers library choice (database/sql, sqlx, sqlc, pgx, GORM trade-offs), parameterized queries, context propagation, NULL handling, scanning, transactions and isolation, connection pool tuning, and…
aql-authoring
This skill should be used when the user asks to "write an AQL query", "optimize an AQL query", "review AQL", or "query openEHR data" — the multi-step authoring/optimization workflow for AQL (Archetype Query Language) over openEHR clinical data. For a one-off explanation of an existing query or a single AQL…
neo-dotnet-ef-core
Use this skill when the task involves Entity Framework Core models, DbContext, migrations, LINQ queries, change tracking, database providers, performance tuning, or data access review in .NET projects.
obsidian-bases
Create and edit Obsidian Bases (.base files) with views, filters, formulas, and summaries. Use when working with .base files, creating database-like views of notes, or when the user mentions Bases, table views, card views, filters, or formulas in Obsidian.