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 m-binimran/dev-pack --skill query-optimizergit clone --depth 1 https://github.com/m-binimran/dev-packWrote 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/m-binimran/dev-pack/query-optimizer)<a href="https://agentmods.dev/skills/m-binimran/dev-pack/query-optimizer"><img src="https://agentmods.dev/badge/skills/m-binimran/dev-pack/query-optimizer/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/m-binimran/dev-pack/query-optimizer"><img src="https://agentmods.dev/badge/skills/m-binimran/dev-pack/query-optimizer.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00056 | $0.00404 |
| Opus 5.5 | $0.00022 | $0.00162 |
| Sonnet 5.5 | $0.00011 | $0.00081 |
| Haiku 4.5 | $0.00006 | $0.00040 |
Grade A, and why
query-optimizer 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 1mo 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
query-optimizer
Make the query fast based on evidence, not guesses.
Process
- Get the plan: run
EXPLAIN (ANALYZE, BUFFERS) <query>. Never optimize without it. - Read the plan top-down: find the costliest node. Look for:
Seq Scanon a big table where an index could be used.Rows Removed by Filterhigh → missing/!selective index.- Estimated vs actual rows far apart → stale stats (
ANALYZE). - Nested loop over many rows → maybe a hash/merge join is better.
- Propose the smallest fix: an index, a rewritten predicate, a
LIMIT, or pagination. - Re-measure with
EXPLAIN ANALYZEand report before/after timing. Don't claim a win without it.
Common fixes
- Composite index ordered by selectivity for multi-column filters.
- Partial index (
where active) for queries that always filter the same way. - Replace
OFFSETpagination with keyset (where id > $last) for deep pages. - Kill N+1: one query per row in app code → use a join or
IN (...)/= ANY.
Output
- The plan's bottleneck in one sentence.
- The fix (SQL/DDL).
- Before/after timing from real
EXPLAIN ANALYZEruns.
Guardrails
- An index isn't free — it slows writes. Only add what the plan justifies.
- Don't add an index that duplicates an existing one's prefix.
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.
- 1mo ago First seen · 34 lines · 56 tokens per session scan A e6dc8bd37b1e
query-optimizer is a skill published in the GitHub repository m-binimran/dev-pack (2 stars, last pushed 4mo ago), licensed MIT. It adds 56 tokens to every session and 404 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
Other skills, from other repositories
alloydb-basics
Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB Model Context Protocol (MCP) tools for automated database operations. Use when creating, configuring, or administering AlloyDB databases. Do NOT use for general PostgreSQL instances (e.g. Cloud SQL) or other GCP databases.
postgresql-table-design
Use this skill when designing or reviewing a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features.
db-repair
Auto-fix gbrain's Postgres access so the brain stays available. When any gbrain command or MCP tool result carries a GBRAINDBACCESS marker (or an operator reports the brain database is down), run the hardcoded gbrain db-repair ladder: diagnose, apply the safe tier, verify. The action is ALWAYS the hardcoded command …
dsql
Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, diagnose cluster performance, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, foreign key…
volcengine-rds-postgresql
A tool for operating PostgreSQL databases hosted by Volcano Engine's managed database service. PostgreSQL is a relational database used to store structured application data.
analyzing-insights-across-teams
Analyze PostHog insights, dashboards, or teams beyond the current project by querying the prod Postgres replicas synced into the dogfood data warehouse (US project 2, "PostHog App + Website"). Use when asked to analyze insights across all teams or projects, another team's insights, or fleet-wide insight/dashboard…