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 fanfan-de/anybox --skill neon-postgres-egress-optimizergit clone --depth 1 https://github.com/fanfan-de/anyboxWrote 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/fanfan-de/anybox/neon-postgres-egress-optimizer)<a href="https://agentmods.dev/skills/fanfan-de/anybox/neon-postgres-egress-optimizer"><img src="https://agentmods.dev/badge/skills/fanfan-de/anybox/neon-postgres-egress-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/fanfan-de/anybox/neon-postgres-egress-optimizer"><img src="https://agentmods.dev/badge/skills/fanfan-de/anybox/neon-postgres-egress-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 | $0.00117 | $0.01787 |
| Opus 5 | $0.00059 | $0.00894 |
| Sonnet 5 | $0.00023 | $0.00357 |
| Haiku 4.5 | $0.00012 | $0.00179 |
Grade A, and why
neon-postgres-egress-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 7d 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
86% identical to neon-postgres-egress-optimizer — 62 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 — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Postgres Egress Optimizer
Guide the user through diagnosing and fixing application-side query patterns that cause excessive data transfer (egress) from their Postgres database. Most high egress bills come from the application fetching more data than it uses.
Step 1: Diagnose
Identify which queries transfer the most data. The primary tool is the pg_stat_statements extension.
Check if pg_stat_statements is available
SELECT 1 FROM pg_stat_statements LIMIT 1;
If this errors, the extension needs to be created:
CREATE EXTENSION IF NOT EXISTS pg_stat_statements;
On Neon, it is available by default but may need this CREATE EXTENSION step.
Handle empty stats
Stats are cleared when a Neon compute scales to zero and restarts. If the stats are empty or the compute recently woke up:
- Reset the stats to start a clean measurement window:
SELECT pg_stat_statements_reset(); - Let the application run under representative traffic for at least an hour.
- Return and run the diagnostic queries below.
If the user has stats from a production database, use those. If they have no access to production stats, proceed to Step 2 and analyze the codebase directly — code-level patterns are often sufficient to identify the worst offenders.
Diagnostic queries
Run these to identify the top egress contributors. Focus on queries that return many rows, return wide rows (JSONB, TEXT, BYTEA columns), or are called very frequently.
Queries returning the most total rows:
SELECT query, calls, rows AS total_rows, rows / calls AS avg_rows_per_call
FROM pg_stat_statements
WHERE calls > 0
ORDER BY rows DESC
LIMIT 10;
Queries returning the most rows per execution (poorly scoped SELECTs, missing pagination):
SELECT query, calls, rows AS total_rows, rows / calls AS avg_rows_per_call
FROM pg_stat_statements
WHERE calls > 0
ORDER BY avg_rows_per_call DESC
LIMIT 10;
Most frequently called queries (candidates for caching):
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 213 lines · 117 tokens per session scan A e7ce04569ec1
neon-postgres-egress-optimizer is a skill published in the GitHub repository fanfan-de/anybox (57 stars, last pushed 28d ago), licensed MIT. It adds 117 tokens to every session and 1,787 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to neon-postgres-egress-optimizer, differing in 62 lines, and is treated as a copy.
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